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    <h1 class="p-name no-ref" id="title">Web Neural Network API</h1>
-   <p id="w3c-state"><a href="https://www.w3.org/standards/types#ED">Editor’s Draft</a>, <time class="dt-updated" datetime="2024-07-27">27 July 2024</time></p>
+   <p id="w3c-state"><a href="https://www.w3.org/standards/types#ED">Editor’s Draft</a>, <time class="dt-updated" datetime="2024-07-30">30 July 2024</time></p>
    <details open>
     <summary>More details about this document</summary>
     <div data-fill-with="spec-metadata">
@@ -1544,6 +1544,8 @@ <h3 class="heading settled" data-level="6.1" id="programming-model-overview"><sp
    <p>The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①">MLGraphBuilder</a></code> interface serves as a builder (factory) to construct a <a data-link-type="dfn" href="#computational-graph" id="ref-for-computational-graph">computational graph</a> (its <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-graph">graph</dfn>) that is then compiled to create an <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph①">MLGraph</a></code>.</p>
    <p>In WebNN, a <a data-link-type="dfn" href="#computational-graph" id="ref-for-computational-graph①">computational graph</a> is composed of <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="operators">operators</dfn> which act on data, and are the nodes of the graph. <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand">MLOperand</a></code>s are a representation of data that flows within the computational graph, and are the edges of the graph. <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①">MLOperand</a></code>s include a <a data-link-type="dfn" href="#computational-graph" id="ref-for-computational-graph②">computational graph</a>'s <dfn class="dfn-paneled" data-dfn-for="computational graph" data-dfn-type="dfn" data-noexport id="computational-graph-input">input</dfn> values for inference, <dfn class="dfn-paneled" data-dfn-for="computational graph" data-dfn-type="dfn" data-noexport id="computational-graph-constants">constants</dfn> (including trained weights) used for inference, intermediate values (often referred to as activations) computed during inference, as well as the output values of inference. An <a data-link-type="dfn" href="#operators" id="ref-for-operators">operator</a>'s <dfn class="dfn-paneled" data-dfn-for="operator" data-dfn-type="dfn" data-noexport id="operator-input">input</dfn> is one or more <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②">MLOperand</a></code>s. An <a data-link-type="dfn" href="#operators" id="ref-for-operators①">operator</a>'s <dfn class="dfn-paneled" data-dfn-for="operator" data-dfn-type="dfn" data-noexport id="operator-output">output</dfn> is one or more <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③">MLOperand</a></code>s. <a data-link-type="dfn" href="#operators" id="ref-for-operators②">Operators</a> have operator-specific parameters that control their behavior, which can include zero or more <dfn class="dfn-paneled" data-dfn-for="operator" data-dfn-type="dfn" data-lt="activation|activation function" data-noexport id="operator-activation">activation functions</dfn>.</p>
    <p>A key part of the <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②">MLGraphBuilder</a></code> interface are methods such as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gemm" id="ref-for-dom-mlgraphbuilder-gemm">gemm()</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu" id="ref-for-dom-mlgraphbuilder-relu">relu()</a></code> which create an <a data-link-type="dfn" href="#operators" id="ref-for-operators③">operator</a> which represents the actual operation to perform on the input data when the computation is run, and return a new <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④">MLOperand</a></code> holding the operator. Methods that create an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤">MLOperand</a></code> connect any <a data-link-type="dfn" href="#operator-input" id="ref-for-operator-input">inputs</a> and <a data-link-type="dfn" href="#operator-activation" id="ref-for-operator-activation">activations</a> to the operator. Each method invocation returns a distinct new value, without changing the value of any other <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥">MLOperand</a></code>.</p>
+   <p>An <a data-link-type="dfn" href="#operators" id="ref-for-operators④">operator</a> has a <dfn class="dfn-paneled" data-dfn-for="operator" data-dfn-type="dfn" data-noexport id="operator-label">label</dfn>, a string which may be included in diagnostics such as <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-exception" id="ref-for-dfn-exception">exception</a> messages. When an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤">operator</a> is created its <a data-link-type="dfn" href="#operator-label" id="ref-for-operator-label">label</a> is initialized in an <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined">implementation-defined</a> manner and may include the passed <code class="idl"><a data-link-type="idl" href="#dom-mloperatoroptions-label" id="ref-for-dom-mloperatoroptions-label">label</a></code>.</p>
+   <p class="note" role="note"><span class="marker">Note:</span> Implementations are encouraged to use the <code class="idl"><a data-link-type="idl" href="#dom-mloperatoroptions-label" id="ref-for-dom-mloperatoroptions-label①">label</a></code> provided by developers to enhance error messages and improve debuggability, including both synchronous errors during graph construction and for errors that occur during asynchronous <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build">build()</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute②">compute()</a></code> operations.</p>
    <p>At inference time, every <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦">MLOperand</a></code> will be bound to a tensor (the actual data), which are essentially multidimensional arrays. The representation of the tensors is implementation dependent, but it typically includes the array data stored in some buffer (memory) and some metadata describing the array data (such as its shape).</p>
    <p>Operations within the computational graph have functional semantics. This allows the implementation
 to potentially share the array data between multiple tensors. For example, the implementation
@@ -1552,9 +1554,9 @@ <h3 class="heading settled" data-level="6.1" id="programming-model-overview"><sp
 the entire data is shared, while in the case of slice, a part of the input data is shared.)
 The implementation may use views, as above, for intermediate values.</p>
    <p>Before the execution, the computation graph that is used to compute one or more specified outputs needs to be converted, compiled, and optimized. The key purpose of the compilation step is to enable optimizations that span two or more operations, such as operation or loop fusion. The user agent may also perform these optimizations during graph conversion.</p>
-   <p>The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③">MLGraphBuilder</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build">build()</a></code> method compiles the graph in the background without blocking the calling thread, and returns a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-promise" id="ref-for-idl-promise">Promise</a></code> that resolves to an <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph②">MLGraph</a></code>. Each <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④">MLGraphBuilder</a></code> can build at most one <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph③">MLGraph</a></code>.</p>
-   <p>The <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph④">MLGraph</a></code> underlying implementation will be composed of platform-specific representations of operators and operands which correspond to the <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤">MLGraphBuilder</a></code>'s <a data-link-type="dfn" href="#operators" id="ref-for-operators④">operators</a> and <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧">MLOperand</a></code>s, but which are not script-visible and may be compositions or decompositions of the graph as constructed by script.</p>
-   <p>Once the <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph⑤">MLGraph</a></code> is constructed, the <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext③">MLContext</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute②">compute()</a></code> method performs the execution of the graph asynchronously either on a parallel timeline in a separate worker thread for the CPU execution or on a GPU timeline in a GPU command queue. This method returns immediately without blocking the calling thread while the actual execution is offloaded to a different timeline. The caller supplies the input values using <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnamedarraybufferviews" id="ref-for-typedefdef-mlnamedarraybufferviews">MLNamedArrayBufferViews</a></code>, binding the input <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨">MLOperand</a></code>s to their values. The caller then supplies pre-allocated buffers for output <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⓪">MLOperand</a></code>s using <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnamedarraybufferviews" id="ref-for-typedefdef-mlnamedarraybufferviews①">MLNamedArrayBufferViews</a></code>. The execution produces the results of the computation from all the inputs bound to the graph. The computation results will be placed at the bound outputs at the time the operation is successfully completed on the offloaded timeline at which time the calling thread is signaled. This type of execution supports both the CPU and GPU device.</p>
+   <p>The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③">MLGraphBuilder</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build①">build()</a></code> method compiles the graph in the background without blocking the calling thread, and returns a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-promise" id="ref-for-idl-promise">Promise</a></code> that resolves to an <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph②">MLGraph</a></code>. Each <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④">MLGraphBuilder</a></code> can build at most one <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph③">MLGraph</a></code>.</p>
+   <p>The <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph④">MLGraph</a></code> underlying implementation will be composed of platform-specific representations of operators and operands which correspond to the <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤">MLGraphBuilder</a></code>'s <a data-link-type="dfn" href="#operators" id="ref-for-operators⑥">operators</a> and <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧">MLOperand</a></code>s, but which are not script-visible and may be compositions or decompositions of the graph as constructed by script.</p>
+   <p>Once the <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph⑤">MLGraph</a></code> is constructed, the <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext③">MLContext</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute③">compute()</a></code> method performs the execution of the graph asynchronously either on a parallel timeline in a separate worker thread for the CPU execution or on a GPU timeline in a GPU command queue. This method returns immediately without blocking the calling thread while the actual execution is offloaded to a different timeline. The caller supplies the input values using <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnamedarraybufferviews" id="ref-for-typedefdef-mlnamedarraybufferviews">MLNamedArrayBufferViews</a></code>, binding the input <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨">MLOperand</a></code>s to their values. The caller then supplies pre-allocated buffers for output <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⓪">MLOperand</a></code>s using <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnamedarraybufferviews" id="ref-for-typedefdef-mlnamedarraybufferviews①">MLNamedArrayBufferViews</a></code>. The execution produces the results of the computation from all the inputs bound to the graph. The computation results will be placed at the bound outputs at the time the operation is successfully completed on the offloaded timeline at which time the calling thread is signaled. This type of execution supports both the CPU and GPU device.</p>
    <h3 class="heading settled" data-level="6.2" id="programming-model-device-selection"><span class="secno">6.2. </span><span class="content">Device Selection</span><a class="self-link" href="#programming-model-device-selection"></a></h3>
    <p>An <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext④">MLContext</a></code> interface represents a global state of neural network execution. One of the important context states is the underlying execution device that manages the resources and facilitates the compilation and the eventual execution of the neural network graph. In addition to the default method of creation with <code class="idl"><a data-link-type="idl" href="#dictdef-mlcontextoptions" id="ref-for-dictdef-mlcontextoptions①">MLContextOptions</a></code>, an <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext⑤">MLContext</a></code> could also be created from a specific <code class="idl"><a data-link-type="idl" href="https://gpuweb.github.io/gpuweb/#gpudevice" id="ref-for-gpudevice②">GPUDevice</a></code> that is already in use by the application.</p>
    <p>In a situation when a GPU context executes a graph with a constant or an input in the system memory as an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#ArrayBufferView" id="ref-for-ArrayBufferView">ArrayBufferView</a></code>, the input content is automatically uploaded from the system memory to the GPU memory, and downloaded back to the system memory of an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#ArrayBufferView" id="ref-for-ArrayBufferView①">ArrayBufferView</a></code> output buffer at the end of the graph execution. This data upload and download cycles will only occur whenever the execution device requires the data to be copied out of and back into the system memory, such as in the case of the GPU. It doesn’t occur when the device is a CPU device. Additionally, the result of the graph execution is in a known layout format. While the execution may be optimized for a native memory access pattern in an intermediate result within the graph, the output of the last operation of the graph must convert the content back to a known layout format at the end of the graph in order to maintain the expected behavior from the caller’s perspective.</p>
@@ -1720,7 +1722,7 @@ <h3 class="heading settled" data-level="7.3" id="api-mlcontext"><span class="sec
 
 [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#SecureContext" id="ref-for-SecureContext②"><c- g>SecureContext</c-></a>, <a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#Exposed" id="ref-for-Exposed①"><c- g>Exposed</c-></a>=(<c- n>Window</c->, <c- n>DedicatedWorker</c->)]
 <c- b>interface</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="interface" data-export id="mlcontext"><code><c- g>MLContext</c-></code></dfn> {
-  <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-promise" id="ref-for-idl-promise③"><c- b>Promise</c-></a>&lt;<a data-link-type="idl-name" href="#dictdef-mlcomputeresult" id="ref-for-dictdef-mlcomputeresult"><c- n>MLComputeResult</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute③"><c- g>compute</c-></a>(
+  <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-promise" id="ref-for-idl-promise③"><c- b>Promise</c-></a>&lt;<a data-link-type="idl-name" href="#dictdef-mlcomputeresult" id="ref-for-dictdef-mlcomputeresult"><c- n>MLComputeResult</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute④"><c- g>compute</c-></a>(
       <a data-link-type="idl-name" href="#mlgraph" id="ref-for-mlgraph⑦"><c- n>MLGraph</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlcontext-compute-graph-inputs-outputs-graph" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-graph"><c- g>graph</c-></a>, <a data-link-type="idl-name" href="#typedefdef-mlnamedarraybufferviews" id="ref-for-typedefdef-mlnamedarraybufferviews④"><c- n>MLNamedArrayBufferViews</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlcontext-compute-graph-inputs-outputs-inputs" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-inputs"><c- g>inputs</c-></a>, <a data-link-type="idl-name" href="#typedefdef-mlnamedarraybufferviews" id="ref-for-typedefdef-mlnamedarraybufferviews⑤"><c- n>MLNamedArrayBufferViews</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlcontext-compute-graph-inputs-outputs-outputs" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-outputs"><c- g>outputs</c-></a>);
 };
 </pre>
@@ -1842,7 +1844,7 @@ <h4 class="heading settled" data-level="7.3.1" id="mlnamedarraybufferviews-trans
       <p>Return <var>transferredViews</var>.</p>
     </ol>
    </details>
-   <h4 class="heading settled" data-level="7.3.2" id="api-mlcontext-compute"><span class="secno">7.3.2. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute④">compute()</a></code></span><a class="self-link" href="#api-mlcontext-compute"></a></h4>
+   <h4 class="heading settled" data-level="7.3.2" id="api-mlcontext-compute"><span class="secno">7.3.2. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute⑤">compute()</a></code></span><a class="self-link" href="#api-mlcontext-compute"></a></h4>
     Asynchronously carries out the computational workload of a compiled graph <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph⑨">MLGraph</a></code> on a separate timeline, either on a worker thread for the CPU execution, or on a GPU/NPU timeline for submitting a workload onto the command queue. The asynchronous nature of this call avoids blocking the calling thread while the computation for result is ongoing. This method of execution requires an <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext①⑨">MLContext</a></code> created with <code class="idl"><a data-link-type="idl" href="#dictdef-mlcontextoptions" id="ref-for-dictdef-mlcontextoptions⑨">MLContextOptions</a></code>. Otherwise, it <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw">throws</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#operationerror" id="ref-for-operationerror②">OperationError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException⑥">DOMException</a></code>. 
    <div class="note" role="note"> In accordance with the <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#arraybufferview-write" id="ref-for-arraybufferview-write">Web IDL warning</a>, to prevent the calling thread from modifying the input and output resources while the computation is ongoing, this method <a data-link-type="dfn" href="#mlnamedarraybufferviews-transfer" id="ref-for-mlnamedarraybufferviews-transfer">transfers</a> the input and output <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnamedarraybufferviews" id="ref-for-typedefdef-mlnamedarraybufferviews①③">MLNamedArrayBufferViews</a></code> to new views that share the same backing memory allocations. The transferred views are returned to the caller via the promise fulfillment with the computation result written into the backing memory of the output views. </div>
    <div>
@@ -1857,7 +1859,7 @@ <h4 class="heading settled" data-level="7.3.2" id="api-mlcontext-compute"><span
     </ul>
     <p><strong>Returns:</strong> <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-promise" id="ref-for-idl-promise④">Promise</a></code>&lt;<code class="idl"><a data-link-type="idl" href="#dictdef-mlcomputeresult" id="ref-for-dictdef-mlcomputeresult①">MLComputeResult</a></code>>.</p>
    </div>
-   <p class="note" role="note"><span class="marker">Note:</span> Invocations of <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute⑤">compute()</a></code> will fail if any of the <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-graph" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-graph①">graph</a></code>'s inputs are not provided as <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-inputs" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-inputs①">inputs</a></code>, or if any requested <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-outputs" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-outputs①">outputs</a></code> do not match the <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-graph" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-graph②">graph</a></code>'s outputs.</p>
+   <p class="note" role="note"><span class="marker">Note:</span> Invocations of <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute" id="ref-for-dom-mlcontext-compute⑥">compute()</a></code> will fail if any of the <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-graph" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-graph①">graph</a></code>'s inputs are not provided as <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-inputs" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-inputs①">inputs</a></code>, or if any requested <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-outputs" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-outputs①">outputs</a></code> do not match the <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-compute-graph-inputs-outputs-graph" id="ref-for-dom-mlcontext-compute-graph-inputs-outputs-graph②">graph</a></code>'s outputs.</p>
    <details class="algorithm" data-algorithm="compute(graph, inputs, outputs)" data-algorithm-for="MLContext" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLContext" data-dfn-type="method" data-export id="dom-mlcontext-compute"><code>compute(<var>graph</var>, <var>inputs</var>, <var>outputs</var>)</code></dfn> method steps are: </summary>
     <ol>
@@ -2055,6 +2057,10 @@ <h3 class="heading settled" data-level="7.6" id="api-mloperand"><span class="sec
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①"><c- b>sequence</c-></a>&lt;<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mloperand-shape" id="ref-for-dom-mloperand-shape"><c- g>shape</c-></a>();
 };
 
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mloperatoroptions"><code><c- g>MLOperatorOptions</c-></code></dfn> {
+  <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-USVString" id="ref-for-idl-USVString③"><c- b>USVString</c-></a> <a class="idl-code" data-default="&quot;&quot;" data-link-type="dict-member" data-type="USVString" href="#dom-mloperatoroptions-label" id="ref-for-dom-mloperatoroptions-label②"><c- g>label</c-></a> = "";
+};
+
 <c- b>typedef</c-> (<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-bigint" id="ref-for-idl-bigint"><c- b>bigint</c-></a> <c- b>or</c-> <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unrestricted-double" id="ref-for-idl-unrestricted-double"><c- b>unrestricted</c-> <c- b>double</c-></a>) <a class="idl-code" data-link-type="typedef" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber"><c- g>MLNumber</c-></a>;
 </pre>
    <div class="internal-slots">
@@ -2069,22 +2075,28 @@ <h3 class="heading settled" data-level="7.6" id="api-mloperand"><span class="sec
      <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLOperand" data-dfn-type="attribute" data-export id="dom-mloperand-name-slot"><code>[[name]]</code></dfn> of type <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string">string</a>
      <dd data-md>
       <p>The <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②">MLOperand</a></code>'s name (only for input operands).</p>
-     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLOperand" data-dfn-type="attribute" data-export id="dom-mloperand-operator-slot"><code>[[operator]]</code></dfn> of type <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤">operator</a>
+     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLOperand" data-dfn-type="attribute" data-export id="dom-mloperand-operator-slot"><code>[[operator]]</code></dfn> of type <a data-link-type="dfn" href="#operators" id="ref-for-operators⑦">operator</a>
      <dd data-md>
-      <p>Reference to <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③">MLOperand</a></code>'s corresponding <a data-link-type="dfn" href="#operators" id="ref-for-operators⑥">operator</a>.</p>
+      <p>Reference to <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③">MLOperand</a></code>'s corresponding <a data-link-type="dfn" href="#operators" id="ref-for-operators⑧">operator</a>.</p>
     </dl>
    </div>
    <p>An <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②④">MLOperand</a></code>'s <dfn class="dfn-paneled" data-dfn-for="MLOperand" data-dfn-type="dfn" data-noexport id="mloperand-shape">shape</dfn> is its <code class="idl"><a data-link-type="idl" href="#dom-mloperand-descriptor-slot" id="ref-for-dom-mloperand-descriptor-slot">[[descriptor]]</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mloperanddescriptor-dimensions" id="ref-for-dom-mloperanddescriptor-dimensions⑥">dimensions</a></code>.</p>
    <p>An <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤">MLOperand</a></code>'s <dfn class="dfn-paneled" data-dfn-for="MLOperand" data-dfn-type="dfn" data-noexport id="mloperand-rank">rank</dfn> is its <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape">shape</a>'s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size①">size</a>.</p>
    <p>An <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑥">MLOperand</a></code>'s <dfn class="dfn-paneled" data-dfn-for="MLOperand" data-dfn-type="dfn" data-noexport id="mloperand-datatype">dataType</dfn> is its <code class="idl"><a data-link-type="idl" href="#dom-mloperand-descriptor-slot" id="ref-for-dom-mloperand-descriptor-slot①">[[descriptor]]</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mloperanddescriptor-datatype" id="ref-for-dom-mloperanddescriptor-datatype④">dataType</a></code>.</p>
    <p>Since the <code class="idl"><a data-link-type="idl" href="#dom-mloperand-builder-slot" id="ref-for-dom-mloperand-builder-slot">[[builder]]</a></code> object is bound by the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-mlgraphbuilder" id="ref-for-dom-mlgraphbuilder-mlgraphbuilder">MLGraphBuilder()</a></code> constructor to an <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②②">MLContext</a></code> object, an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦">MLOperand</a></code> is also always bound to the same <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②③">MLContext</a></code> object.</p>
-   <h4 class="heading settled" data-level="7.6.1" id="api-mloperand-create"><span class="secno">7.6.1. </span><span class="content">Creating an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑧">MLOperand</a></code></span><a class="self-link" href="#api-mloperand-create"></a></h4>
-    The <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨">MLOperand</a></code> objects are created by the methods of <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑦">MLGraphBuilder</a></code>, internally using the following algorithms. 
+   <p><code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions">MLOperatorOptions</a></code> has the following members:</p>
+   <dl>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLOperatorOptions" data-dfn-type="dict-member" data-export id="dom-mloperatoroptions-label"><code>label</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-USVString" id="ref-for-idl-USVString④">USVString</a>, defaulting to <code>""</code></span>
+    <dd data-md>
+     <p>Optionally provided when an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑨">operator</a> is created using <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑦">MLGraphBuilder</a></code> methods that create <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑧">MLOperand</a></code>s. The implementation may use this value to initialize the <a data-link-type="dfn" href="#operators" id="ref-for-operators①⓪">operator</a>'s <a data-link-type="dfn" href="#operator-label" id="ref-for-operator-label①">label</a>.</p>
+   </dl>
+   <h4 class="heading settled" data-level="7.6.1" id="api-mloperand-create"><span class="secno">7.6.1. </span><span class="content">Creating an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨">MLOperand</a></code></span><a class="self-link" href="#api-mloperand-create"></a></h4>
+    The <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪">MLOperand</a></code> objects are created by the methods of <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑧">MLGraphBuilder</a></code>, internally using the following algorithms. 
    <details class="algorithm" data-algorithm="create an MLOperand" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="create-an-mloperand">create an MLOperand</dfn> given <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑧">MLGraphBuilder</a></code> <var>builder</var> and <code class="idl"><a data-link-type="idl" href="#dictdef-mloperanddescriptor" id="ref-for-dictdef-mloperanddescriptor①③">MLOperandDescriptor</a></code> <var>desc</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="create-an-mloperand">create an MLOperand</dfn> given <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑨">MLGraphBuilder</a></code> <var>builder</var> and <code class="idl"><a data-link-type="idl" href="#dictdef-mloperanddescriptor" id="ref-for-dictdef-mloperanddescriptor①③">MLOperandDescriptor</a></code> <var>desc</var>, run the following steps: </summary>
     <ol>
      <li data-md>
-      <p>Let <var>operand</var> be a new <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪">MLOperand</a></code>.</p>
+      <p>Let <var>operand</var> be a new <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①">MLOperand</a></code>.</p>
      <li data-md>
       <p>Set <var>operand</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-builder-slot" id="ref-for-dom-mloperand-builder-slot①">[[builder]]</a></code> to <var>builder</var>.</p>
      <li data-md>
@@ -2094,10 +2106,10 @@ <h4 class="heading settled" data-level="7.6.1" id="api-mloperand-create"><span c
     </ol>
    </details>
    <details class="algorithm" data-algorithm="copy an MLOperand" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="copy-an-mloperand">copy an MLOperand</dfn> given <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①">MLOperand</a></code> <var>operand</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="copy-an-mloperand">copy an MLOperand</dfn> given <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②">MLOperand</a></code> <var>operand</var>, run the following steps: </summary>
     <ol>
      <li data-md>
-      <p>Let <var>result</var> be a new <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②">MLOperand</a></code>.</p>
+      <p>Let <var>result</var> be a new <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③③">MLOperand</a></code>.</p>
      <li data-md>
       <p>Set <var>result</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-builder-slot" id="ref-for-dom-mloperand-builder-slot②">[[builder]]</a></code> to <var>operand</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-builder-slot" id="ref-for-dom-mloperand-builder-slot③">[[builder]]</a></code>.</p>
      <li data-md>
@@ -2108,13 +2120,13 @@ <h4 class="heading settled" data-level="7.6.1" id="api-mloperand-create"><span c
       <p>Return <var>result</var>.</p>
     </ol>
    </details>
-   <p class="algorithm" data-algorithm="validate operand" data-algorithm-for="MLGraphBuilder"> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-validate-operand">validate operand</dfn> given <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑨">MLGraphBuilder</a></code> <var>builder</var> and <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③③">MLOperand</a></code> <var>operand</var>, return true if <var>operand</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-builder-slot" id="ref-for-dom-mloperand-builder-slot④">[[builder]]</a></code> is <var>builder</var>, and false otherwise. </p>
+   <p class="algorithm" data-algorithm="validate operand" data-algorithm-for="MLGraphBuilder"> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-validate-operand">validate operand</dfn> given <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⓪">MLGraphBuilder</a></code> <var>builder</var> and <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④">MLOperand</a></code> <var>operand</var>, return true if <var>operand</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-builder-slot" id="ref-for-dom-mloperand-builder-slot④">[[builder]]</a></code> is <var>builder</var>, and false otherwise. </p>
    <h5 class="heading settled" data-level="7.6.1.1" id="api-mlnumber-typedef"><span class="secno">7.6.1.1. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber①">MLNumber</a></code></span><a class="self-link" href="#api-mlnumber-typedef"></a></h5>
-   <p><dfn class="dfn-paneled idl-code" data-dfn-type="typedef" data-export id="typedefdef-mlnumber"><code>MLNumber</code></dfn> is used when specifying the type of a numeric option for an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④">MLOperand</a></code> which can be of any <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype⑤">MLOperandDataType</a></code>, including both 64-bit integer types (<code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint64" id="ref-for-dom-mloperanddatatype-uint64">"uint64"</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64">"int64"</a></code>) and 32-bit floating point (<code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32">"float32"</a></code>). Implementations process the value according to the corresponding <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype⑥">MLOperandDataType</a></code>. For example, if <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp">clamp(input, options)</a></code> is called with an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤">MLOperand</a></code> with <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype">dataType</a> <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32">"uint32"</a></code>, the <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber②">MLNumber</a></code> parameters are explicitly <a data-link-type="dfn" href="#cast" id="ref-for-cast">cast</a> to <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②">unsigned long</a></code>.</p>
+   <p><dfn class="dfn-paneled idl-code" data-dfn-type="typedef" data-export id="typedefdef-mlnumber"><code>MLNumber</code></dfn> is used when specifying the type of a numeric option for an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤">MLOperand</a></code> which can be of any <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype⑤">MLOperandDataType</a></code>, including both 64-bit integer types (<code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint64" id="ref-for-dom-mloperanddatatype-uint64">"uint64"</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64">"int64"</a></code>) and 32-bit floating point (<code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32">"float32"</a></code>). Implementations process the value according to the corresponding <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype⑥">MLOperandDataType</a></code>. For example, if <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp">clamp(input, options)</a></code> is called with an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥">MLOperand</a></code> with <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype">dataType</a> <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32">"uint32"</a></code>, the <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber②">MLNumber</a></code> parameters are explicitly <a data-link-type="dfn" href="#cast" id="ref-for-cast">cast</a> to <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②">unsigned long</a></code>.</p>
    <div class="note" role="note"> Specifying the option as <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double">double</a></code> would lose accuracy when passing values over 2<sup>53</sup>, and specifying <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-long-long" id="ref-for-idl-long-long">long long</a></code> would disallow values over 2<sup>63</sup>. </div>
    <p class="issue" id="issue-63bb2306"><a class="self-link" href="#issue-63bb2306"></a> Support for unions of <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-bigint" id="ref-for-idl-bigint①">bigint</a></code> and <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-numeric-type" id="ref-for-dfn-numeric-type">numeric types</a> is new in <a data-link-type="biblio" href="#biblio-webidl" title="Web IDL Standard">[WEBIDL]</a>, and implementation support is also limited. Prototype implementations are encouraged to provide feedback for this approach. <a href="https://github.com/whatwg/webidl/issues/1388">[Issue #whatwg/webidl#1388]</a></p>
    <h4 class="heading settled" data-level="7.6.2" id="api-mloperand-datatype"><span class="secno">7.6.2. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#dom-mloperand-datatype" id="ref-for-dom-mloperand-datatype①">dataType()</a></code></span><a class="self-link" href="#api-mloperand-datatype"></a></h4>
-    Returns the data type of the <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥">MLOperand</a></code>. 
+    Returns the data type of the <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦">MLOperand</a></code>. 
    <div> <strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype⑦">MLOperandDataType</a></code>. The data type of the operand. </div>
    <details class="algorithm" data-algorithm="dataType()" data-algorithm-for="MLOperand" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLOperand" data-dfn-type="method" data-export id="dom-mloperand-datatype"><code>dataType()</code></dfn> method steps are: </summary>
@@ -2124,7 +2136,7 @@ <h4 class="heading settled" data-level="7.6.2" id="api-mloperand-datatype"><span
     </ol>
    </details>
    <h4 class="heading settled" data-level="7.6.3" id="api-mloperand-shape"><span class="secno">7.6.3. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#dom-mloperand-shape" id="ref-for-dom-mloperand-shape①">shape()</a></code></span><a class="self-link" href="#api-mloperand-shape"></a></h4>
-    Returns the shape of the <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦">MLOperand</a></code>. 
+    Returns the shape of the <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧">MLOperand</a></code>. 
    <div> <strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③">unsigned long</a></code>>. The shape of the operand. </div>
    <details class="algorithm" data-algorithm="shape()" data-algorithm-for="MLOperand" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLOperand" data-dfn-type="method" data-export id="dom-mloperand-shape"><code>shape()</code></dfn> method steps are: </summary>
@@ -2133,9 +2145,9 @@ <h4 class="heading settled" data-level="7.6.3" id="api-mloperand-shape"><span cl
       <p>Return <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑧">this</a>'s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape①">shape</a>.</p>
     </ol>
    </details>
-   <h3 class="heading settled" data-level="7.7" id="api-mlgraphbuilder"><span class="secno">7.7. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⓪">MLGraphBuilder</a></code> interface</span><a class="self-link" href="#api-mlgraphbuilder"></a></h3>
-   <p>The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①①">MLGraphBuilder</a></code> interface defines a set of operations as identified by the <a href="#usecases">§ 2 Use cases</a> that can be composed into a computational graph. It also represents the intermediate state of a graph building session.</p>
-<pre class="idl highlight def"><c- b>typedef</c-> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-record" id="ref-for-idl-record③"><c- b>record</c-></a>&lt;<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-USVString" id="ref-for-idl-USVString③"><c- b>USVString</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧"><c- n>MLOperand</c-></a>> <dfn class="dfn-paneled idl-code" data-dfn-type="typedef" data-export id="typedefdef-mlnamedoperands"><code><c- g>MLNamedOperands</c-></code></dfn>;
+   <h3 class="heading settled" data-level="7.7" id="api-mlgraphbuilder"><span class="secno">7.7. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①①">MLGraphBuilder</a></code> interface</span><a class="self-link" href="#api-mlgraphbuilder"></a></h3>
+   <p>The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①②">MLGraphBuilder</a></code> interface defines a set of operations as identified by the <a href="#usecases">§ 2 Use cases</a> that can be composed into a computational graph. It also represents the intermediate state of a graph building session.</p>
+<pre class="idl highlight def"><c- b>typedef</c-> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-record" id="ref-for-idl-record③"><c- b>record</c-></a>&lt;<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-USVString" id="ref-for-idl-USVString⑤"><c- b>USVString</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨"><c- n>MLOperand</c-></a>> <dfn class="dfn-paneled idl-code" data-dfn-type="typedef" data-export id="typedefdef-mlnamedoperands"><code><c- g>MLNamedOperands</c-></code></dfn>;
 
 [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#SecureContext" id="ref-for-SecureContext⑤"><c- g>SecureContext</c-></a>, <a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#Exposed" id="ref-for-Exposed④"><c- g>Exposed</c-></a>=(<c- n>Window</c->, <c- n>DedicatedWorker</c->)]
 <c- b>interface</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="interface" data-export id="mlgraphbuilder"><code><c- g>MLGraphBuilder</c-></code></dfn> {
@@ -2143,36 +2155,36 @@ <h3 class="heading settled" data-level="7.7" id="api-mlgraphbuilder"><span class
   <a class="idl-code" data-link-type="constructor" href="#dom-mlgraphbuilder-mlgraphbuilder" id="ref-for-dom-mlgraphbuilder-mlgraphbuilder①"><c- g>constructor</c-></a>(<a data-link-type="idl-name" href="#mlcontext" id="ref-for-mlcontext②④"><c- n>MLContext</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constructor-context-context" id="ref-for-dom-mlgraphbuilder-constructor-context-context"><c- g>context</c-></a>);
 
   // Create an operand for a graph input.
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-input" id="ref-for-dom-mlgraphbuilder-input"><c- g>input</c-></a>(<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-USVString" id="ref-for-idl-USVString④"><c- b>USVString</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-input-name-descriptor-name" id="ref-for-dom-mlgraphbuilder-input-name-descriptor-name"><c- g>name</c-></a>, <a data-link-type="idl-name" href="#dictdef-mloperanddescriptor" id="ref-for-dictdef-mloperanddescriptor①④"><c- n>MLOperandDescriptor</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-input-name-descriptor-descriptor" id="ref-for-dom-mlgraphbuilder-input-name-descriptor-descriptor"><c- g>descriptor</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-input" id="ref-for-dom-mlgraphbuilder-input"><c- g>input</c-></a>(<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-USVString" id="ref-for-idl-USVString⑥"><c- b>USVString</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-input-name-descriptor-name" id="ref-for-dom-mlgraphbuilder-input-name-descriptor-name"><c- g>name</c-></a>, <a data-link-type="idl-name" href="#dictdef-mloperanddescriptor" id="ref-for-dictdef-mloperanddescriptor①④"><c- n>MLOperandDescriptor</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-input-name-descriptor-descriptor" id="ref-for-dom-mlgraphbuilder-input-name-descriptor-descriptor"><c- g>descriptor</c-></a>);
 
   // Create an operand for a graph constant.
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-constant" id="ref-for-dom-mlgraphbuilder-constant"><c- g>constant</c-></a>(<a data-link-type="idl-name" href="#dictdef-mloperanddescriptor" id="ref-for-dictdef-mloperanddescriptor①⑤"><c- n>MLOperandDescriptor</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-descriptor-bufferview-descriptor" id="ref-for-dom-mlgraphbuilder-constant-descriptor-bufferview-descriptor"><c- g>descriptor</c-></a>, <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#ArrayBufferView" id="ref-for-ArrayBufferView⑨"><c- n>ArrayBufferView</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-descriptor-bufferview-bufferview" id="ref-for-dom-mlgraphbuilder-constant-descriptor-bufferview-bufferview"><c- g>bufferView</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-constant" id="ref-for-dom-mlgraphbuilder-constant"><c- g>constant</c-></a>(<a data-link-type="idl-name" href="#dictdef-mloperanddescriptor" id="ref-for-dictdef-mloperanddescriptor①⑤"><c- n>MLOperandDescriptor</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-descriptor-bufferview-descriptor" id="ref-for-dom-mlgraphbuilder-constant-descriptor-bufferview-descriptor"><c- g>descriptor</c-></a>, <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#ArrayBufferView" id="ref-for-ArrayBufferView⑨"><c- n>ArrayBufferView</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-descriptor-bufferview-bufferview" id="ref-for-dom-mlgraphbuilder-constant-descriptor-bufferview-bufferview"><c- g>bufferView</c-></a>);
 
   // Create a scalar operand from the specified number of the specified type.
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-constant-type-value" id="ref-for-dom-mlgraphbuilder-constant-type-value"><c- g>constant</c-></a>(<a data-link-type="idl-name" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype⑧"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-type-value-type" id="ref-for-dom-mlgraphbuilder-constant-type-value-type"><c- g>type</c-></a>, <a data-link-type="idl-name" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber③"><c- n>MLNumber</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-type-value-value" id="ref-for-dom-mlgraphbuilder-constant-type-value-value"><c- g>value</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-constant-type-value" id="ref-for-dom-mlgraphbuilder-constant-type-value"><c- g>constant</c-></a>(<a data-link-type="idl-name" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype⑧"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-type-value-type" id="ref-for-dom-mlgraphbuilder-constant-type-value-type"><c- g>type</c-></a>, <a data-link-type="idl-name" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber③"><c- n>MLNumber</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-constant-type-value-value" id="ref-for-dom-mlgraphbuilder-constant-type-value-value"><c- g>value</c-></a>);
 
   // Compile the graph up to the specified output operands asynchronously.
-  <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-promise" id="ref-for-idl-promise⑤"><c- b>Promise</c-></a>&lt;<a data-link-type="idl-name" href="#mlgraph" id="ref-for-mlgraph①⑧"><c- n>MLGraph</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build①"><c- g>build</c-></a>(<a data-link-type="idl-name" href="#typedefdef-mlnamedoperands" id="ref-for-typedefdef-mlnamedoperands"><c- n>MLNamedOperands</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-build-outputs-outputs" id="ref-for-dom-mlgraphbuilder-build-outputs-outputs"><c- g>outputs</c-></a>);
+  <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-promise" id="ref-for-idl-promise⑤"><c- b>Promise</c-></a>&lt;<a data-link-type="idl-name" href="#mlgraph" id="ref-for-mlgraph①⑧"><c- n>MLGraph</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build②"><c- g>build</c-></a>(<a data-link-type="idl-name" href="#typedefdef-mlnamedoperands" id="ref-for-typedefdef-mlnamedoperands"><c- n>MLNamedOperands</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-build-outputs-outputs" id="ref-for-dom-mlgraphbuilder-build-outputs-outputs"><c- g>outputs</c-></a>);
 };
 </pre>
-   <div class="note" role="note"> The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①②">MLGraphBuilder</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build②">build()</a></code> method compiles the graph builder state up to the specified output operands into a compiled graph according to the type of <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑤">MLContext</a></code> that creates it. When the <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-contexttype-slot" id="ref-for-dom-mlcontext-contexttype-slot⑤">[[contextType]]</a></code> of the <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑥">MLContext</a></code> is set to "<a data-link-type="dfn" href="#context-type-default" id="ref-for-context-type-default③">default</a>", the compiled graph is initialized right before the <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph①⑨">MLGraph</a></code> is returned. This graph initialization stage is important for optimal performance of the subsequent graph executions. It typically involves a process known as "weight preprocessing" where all the constant inputs to the graph are preprocessed and cached at the operating system level for subsequent graph execution calls. The initializing inputs are typically the constant weight data specified through the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-constant" id="ref-for-dom-mlgraphbuilder-constant①">constant()</a></code> method as constant operands during graph construction time. </div>
+   <div class="note" role="note"> The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①③">MLGraphBuilder</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build③">build()</a></code> method compiles the graph builder state up to the specified output operands into a compiled graph according to the type of <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑤">MLContext</a></code> that creates it. When the <code class="idl"><a data-link-type="idl" href="#dom-mlcontext-contexttype-slot" id="ref-for-dom-mlcontext-contexttype-slot⑤">[[contextType]]</a></code> of the <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑥">MLContext</a></code> is set to "<a data-link-type="dfn" href="#context-type-default" id="ref-for-context-type-default③">default</a>", the compiled graph is initialized right before the <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph①⑨">MLGraph</a></code> is returned. This graph initialization stage is important for optimal performance of the subsequent graph executions. It typically involves a process known as "weight preprocessing" where all the constant inputs to the graph are preprocessed and cached at the operating system level for subsequent graph execution calls. The initializing inputs are typically the constant weight data specified through the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-constant" id="ref-for-dom-mlgraphbuilder-constant①">constant()</a></code> method as constant operands during graph construction time. </div>
    <div class="internal-slots">
-     <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①③">MLGraphBuilder</a></code> has the following internal slots: 
+     <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①④">MLGraphBuilder</a></code> has the following internal slots: 
     <dl>
      <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="attribute" data-export id="dom-mlgraphbuilder-context-slot"><code>[[context]]</code></dfn> of type <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑦">MLContext</a></code>
      <dd data-md>
-      <p>The context of type <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑧">MLContext</a></code> associated with this <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①④">MLGraphBuilder</a></code>.</p>
+      <p>The context of type <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑧">MLContext</a></code> associated with this <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑤">MLGraphBuilder</a></code>.</p>
      <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="attribute" data-export id="dom-mlgraphbuilder-hasbuilt-slot"><code>[[hasBuilt]]</code></dfn> of type <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean">boolean</a></code>
      <dd data-md>
-      <p>Whether <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑤">MLGraphBuilder</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build③">build()</a></code> has been called. Once built, the <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑥">MLGraphBuilder</a></code> can no longer create <a data-link-type="dfn" href="#operators" id="ref-for-operators⑦">operators</a> or compile <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph②⓪">MLGraph</a></code>s.</p>
+      <p>Whether <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑥">MLGraphBuilder</a></code>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build" id="ref-for-dom-mlgraphbuilder-build④">build()</a></code> has been called. Once built, the <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑦">MLGraphBuilder</a></code> can no longer create <a data-link-type="dfn" href="#operators" id="ref-for-operators①①">operators</a> or compile <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph②⓪">MLGraph</a></code>s.</p>
     </dl>
    </div>
-   <h4 class="heading settled" data-level="7.7.1" id="api-mlgraphbuilder-constructor"><span class="secno">7.7.1. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑦">MLGraphBuilder</a></code> constructor</span><a class="self-link" href="#api-mlgraphbuilder-constructor"></a></h4>
+   <h4 class="heading settled" data-level="7.7.1" id="api-mlgraphbuilder-constructor"><span class="secno">7.7.1. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑧">MLGraphBuilder</a></code> constructor</span><a class="self-link" href="#api-mlgraphbuilder-constructor"></a></h4>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/constructor(context)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-constructor-context-context"><code>context</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑨">MLContext</a></code>. The context to associate with the <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑧">MLGraphBuilder</a></code>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/constructor(context)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-constructor-context-context"><code>context</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mlcontext" id="ref-for-mlcontext②⑨">MLContext</a></code>. The context to associate with the <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑨">MLGraphBuilder</a></code>.</p>
     </ul>
    </div>
    <details class="algorithm" data-algorithm="MLGraphBuilder(context)" data-algorithm-for="MLGraphBuilder" open>
@@ -2187,7 +2199,7 @@ <h4 class="heading settled" data-level="7.7.1" id="api-mlgraphbuilder-constructo
     </ol>
    </details>
    <h4 class="heading settled" data-level="7.7.2" id="api-mlgraphbuilder-input"><span class="secno">7.7.2. </span><span class="content">input operands</span><a class="self-link" href="#api-mlgraphbuilder-input"></a></h4>
-   <p>Create a named <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④②">MLOperand</a></code> based on a descriptor, that can be used as an input.</p>
+   <p>Create a named <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④③">MLOperand</a></code> based on a descriptor, that can be used as an input.</p>
    <div>
      <strong>Arguments:</strong> 
     <ul>
@@ -2196,7 +2208,7 @@ <h4 class="heading settled" data-level="7.7.2" id="api-mlgraphbuilder-input"><sp
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/input(name, descriptor)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-input-name-descriptor-descriptor"><code>descriptor</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperanddescriptor" id="ref-for-dictdef-mloperanddescriptor①⑥">MLOperandDescriptor</a></code> object.</p>
     </ul>
-     <strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④③">MLOperand</a></code>. 
+     <strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④④">MLOperand</a></code>. 
    </div>
    <details class="algorithm" data-algorithm="input(name, descriptor)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-input"><code>input(<var>name</var>, <var>descriptor</var>)</code></dfn> method steps are: </summary>
@@ -2206,7 +2218,7 @@ <h4 class="heading settled" data-level="7.7.2" id="api-mlgraphbuilder-input"><sp
      <li data-md>
       <p>If <var>name</var> is empty, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑧">TypeError</a></code>.</p>
      <li data-md>
-      <p>If any <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④④">MLOperand</a></code>s in <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①③">this</a>'s <a data-link-type="dfn" href="#mlgraphbuilder-graph" id="ref-for-mlgraphbuilder-graph">graph</a>'s <a data-link-type="dfn" href="#computational-graph-input" id="ref-for-computational-graph-input">inputs</a> have a <code class="idl"><a data-link-type="idl" href="#dom-mloperand-name-slot" id="ref-for-dom-mloperand-name-slot③">[[name]]</a></code> equal to <var>name</var>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑨">TypeError</a></code>.</p>
+      <p>If any <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑤">MLOperand</a></code>s in <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①③">this</a>'s <a data-link-type="dfn" href="#mlgraphbuilder-graph" id="ref-for-mlgraphbuilder-graph">graph</a>'s <a data-link-type="dfn" href="#computational-graph-input" id="ref-for-computational-graph-input">inputs</a> have a <code class="idl"><a data-link-type="idl" href="#dom-mloperand-name-slot" id="ref-for-dom-mloperand-name-slot③">[[name]]</a></code> equal to <var>name</var>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑨">TypeError</a></code>.</p>
      <li data-md>
       <p>If <a data-link-type="dfn" href="#mloperanddescriptor-check-dimensions" id="ref-for-mloperanddescriptor-check-dimensions">checking dimensions</a> given <var>descriptor</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑤">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⓪">TypeError</a></code>.</p>
      <li data-md>
@@ -2223,11 +2235,11 @@ <h4 class="heading settled" data-level="7.7.2" id="api-mlgraphbuilder-input"><sp
       <p>Return <var>operand</var>.</p>
     </ol>
    </details>
-   <div class="note" role="note"> The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder①⑨">MLGraphBuilder</a></code> API allows creating an <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph②①">MLGraph</a></code> without input operands. If the underlying platform doesn’t support that, implementations may add a stub input, or pass constants as inputs to the graph. </div>
+   <div class="note" role="note"> The <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⓪">MLGraphBuilder</a></code> API allows creating an <code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph②①">MLGraph</a></code> without input operands. If the underlying platform doesn’t support that, implementations may add a stub input, or pass constants as inputs to the graph. </div>
    <h4 class="heading settled" data-level="7.7.3" id="api-mlgraphbuilder-constant"><span class="secno">7.7.3. </span><span class="content">constant operands</span><a class="self-link" href="#api-mlgraphbuilder-constant"></a></h4>
-    Create a constant <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑤">MLOperand</a></code> that can be used in <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⓪">MLGraphBuilder</a></code> methods. 
+    Create a constant <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑥">MLOperand</a></code> that can be used in <code class="idl"><a data-link-type="idl" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②①">MLGraphBuilder</a></code> methods. 
    <h5 class="heading settled" data-level="7.7.3.1" id="api-mlgraphbuilder-constant-bufferview"><span class="secno">7.7.3.1. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-constant" id="ref-for-dom-mlgraphbuilder-constant②">constant(descriptor, bufferView)</a></code></span><a class="self-link" href="#api-mlgraphbuilder-constant-bufferview"></a></h5>
-    Create a constant <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑥">MLOperand</a></code> of the specified data type and shape that contains the initializing data. 
+    Create a constant <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑦">MLOperand</a></code> of the specified data type and shape that contains the initializing data. 
    <div>
      <strong>Arguments:</strong> 
     <ul>
@@ -2236,7 +2248,7 @@ <h5 class="heading settled" data-level="7.7.3.1" id="api-mlgraphbuilder-constant
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/constant(descriptor, bufferView)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-constant-descriptor-bufferview-bufferview"><code>bufferView</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#ArrayBufferView" id="ref-for-ArrayBufferView①⓪">ArrayBufferView</a></code>. The view of the buffer containing the initializing data.</p>
     </ul>
-     <strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑦">MLOperand</a></code>. The constant output tensor. 
+     <strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑧">MLOperand</a></code>. The constant output tensor. 
    </div>
    <details class="algorithm" data-algorithm="constant(descriptor, bufferView)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-constant"><code>constant(<var>descriptor</var>, <var>bufferView</var>)</code></dfn> method steps are: </summary>
@@ -2262,7 +2274,7 @@ <h5 class="heading settled" data-level="7.7.3.1" id="api-mlgraphbuilder-constant
     </ol>
    </details>
    <h5 class="heading settled" data-level="7.7.3.2" id="api-mlgraphbuilder-constant-type-value"><span class="secno">7.7.3.2. </span><span class="content"><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-constant-type-value" id="ref-for-dom-mlgraphbuilder-constant-type-value①">constant(type, value)</a></code></span><a class="self-link" href="#api-mlgraphbuilder-constant-type-value"></a></h5>
-    Create a scalar constant <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑧">MLOperand</a></code> of the specified value and data type. 
+    Create a scalar constant <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑨">MLOperand</a></code> of the specified value and data type. 
    <div class="note" role="note"> Data truncation will occur when the specified value exceeds the range of the specified output data type e.g. when a floating point value is assigned to an <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8">"int8"</a></code> data type, etc. </div>
    <div>
      <strong>Arguments:</strong> 
@@ -2272,7 +2284,7 @@ <h5 class="heading settled" data-level="7.7.3.2" id="api-mlgraphbuilder-constant
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/constant(type, value)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-constant-type-value-value"><code>value</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber④">MLNumber</a></code>. The value of the constant.</p>
     </ul>
-     <strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⑨">MLOperand</a></code>. The constant output. 
+     <strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⓪">MLOperand</a></code>. The constant output. 
    </div>
    <details class="algorithm" data-algorithm="constant(type, value)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-constant-type-value"><code>constant(<var>type</var>, <var>value</var>)</code></dfn> method steps are: </summary>
@@ -2301,7 +2313,7 @@ <h4 class="heading settled" data-level="7.7.4" id="api-mlgraphbuilder-build"><sp
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/build(outputs)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-build-outputs-outputs"><code>outputs</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnamedoperands" id="ref-for-typedefdef-mlnamedoperands①">MLNamedOperands</a></code>. Identifies the <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⓪">MLOperand</a></code>s that will be the outputs of the graph.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/build(outputs)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-build-outputs-outputs"><code>outputs</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnamedoperands" id="ref-for-typedefdef-mlnamedoperands①">MLNamedOperands</a></code>. Identifies the <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤①">MLOperand</a></code>s that will be the outputs of the graph.</p>
     </ul>
      <strong>Returns:</strong> Promise&lt;<code class="idl"><a data-link-type="idl" href="#mlgraph" id="ref-for-mlgraph②②">MLGraph</a></code>>. 
    </div>
@@ -2375,7 +2387,7 @@ <h4 class="heading settled" data-level="7.7.4" id="api-mlgraphbuilder-build"><sp
       <p>Run the following steps <a data-link-type="dfn" href="https://html.spec.whatwg.org/multipage/infrastructure.html#in-parallel" id="ref-for-in-parallel③">in parallel</a>:</p>
       <ol>
        <li data-md>
-        <p>Let <var>graphImpl</var> be the result of converting <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this②⑨">this</a>'s <a data-link-type="dfn" href="#mlgraphbuilder-graph" id="ref-for-mlgraphbuilder-graph⑦">graph</a> with <var>operands</var>, <var>operators</var>, <var>inputs</var>, and <var>outputs</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-getting-the-values" id="ref-for-map-getting-the-values①">values</a> into an <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined">implementation-defined</a> format which can be interpreted by the underlying platform.</p>
+        <p>Let <var>graphImpl</var> be the result of converting <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this②⑨">this</a>'s <a data-link-type="dfn" href="#mlgraphbuilder-graph" id="ref-for-mlgraphbuilder-graph⑦">graph</a> with <var>operands</var>, <var>operators</var>, <var>inputs</var>, and <var>outputs</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-getting-the-values" id="ref-for-map-getting-the-values①">values</a> into an <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined①">implementation-defined</a> format which can be interpreted by the underlying platform.</p>
         <ol>
          <li data-md>
           <p>If the underlying platform does not support a requested feature, then <a data-link-type="dfn" href="#queue-an-ml-task" id="ref-for-queue-an-ml-task⑥">queue an ML task</a> with <var>global</var> to <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#reject" id="ref-for-reject①⑧">reject</a> <var>promise</var> with an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#operationerror" id="ref-for-operationerror④">OperationError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException①③">DOMException</a></code>, and abort these steps.</p>
@@ -2394,15 +2406,15 @@ <h4 class="heading settled" data-level="7.7.4" id="api-mlgraphbuilder-build"><sp
    <p class="note" role="note"><span class="marker">NOTE:</span> Specifying an <a data-link-type="dfn" href="#computational-graph-input" id="ref-for-computational-graph-input④">input</a> operand or <a data-link-type="dfn" href="#computational-graph-constants" id="ref-for-computational-graph-constants④">constant</a> operand as a graph <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-build-outputs-outputs" id="ref-for-dom-mlgraphbuilder-build-outputs-outputs①">output</a></code> results in an error, as this is usually an incorrect usage of the API. Callers can work around this by introducing an <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-identity" id="ref-for-dom-mlgraphbuilder-identity">identity()</a></code> operator.</p>
    <h4 class="heading settled" data-level="7.7.5" id="api-mlgraphbuilder-argminmax"><span class="secno">7.7.5. </span><span class="content">argMin/argMax operations</span><a class="self-link" href="#api-mlgraphbuilder-argminmax"></a></h4>
     Return the index location of the minimum or maximum values of all the input values along the axis. In case of ties, the identity of the return value is implementation dependent. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlargminmaxoptions"><code><c- g>MLArgMinMaxOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlargminmaxoptions"><code><c- g>MLArgMinMaxOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlargminmaxoptions-keepdimensions" id="ref-for-dom-mlargminmaxoptions-keepdimensions"><c- g>keepDimensions</c-></a> = <c- b>false</c->;
   <a data-link-type="idl-name" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①⓪"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-default="&quot;int32&quot;" data-link-type="dict-member" data-type="MLOperandDataType" href="#dom-mlargminmaxoptions-outputdatatype" id="ref-for-dom-mlargminmaxoptions-outputdatatype"><c- g>outputDataType</c-></a> = "int32";
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②①"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-argmin" id="ref-for-dom-mlgraphbuilder-argmin"><c- g>argMin</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-input"><c- g>input</c-></a>, [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-axis" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-axis"><c- g>axis</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②②"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-argmin" id="ref-for-dom-mlgraphbuilder-argmin"><c- g>argMin</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-input"><c- g>input</c-></a>, [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-axis" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-axis"><c- g>axis</c-></a>,
                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlargminmaxoptions" id="ref-for-dictdef-mlargminmaxoptions"><c- n>MLArgMinMaxOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-options" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-options"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-argmax" id="ref-for-dom-mlgraphbuilder-argmax"><c- g>argMax</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-input①"><c- g>input</c-></a>, [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-axis" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-axis①"><c- g>axis</c-></a>,
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-argmax" id="ref-for-dom-mlgraphbuilder-argmax"><c- g>argMax</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-input①"><c- g>input</c-></a>, [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-axis" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-axis①"><c- g>axis</c-></a>,
                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlargminmaxoptions" id="ref-for-dictdef-mlargminmaxoptions①"><c- n>MLArgMinMaxOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-options" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-options①"><c- g>options</c-></a> = {});
 };
 </pre>
@@ -2419,16 +2431,16 @@ <h4 class="heading settled" data-level="7.7.5" id="api-mlgraphbuilder-argminmax"
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/argMin(input, axis, options), MLGraphBuilder/argMax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-argmin-input-axis-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑤">MLOperand</a></code>. The input N-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/argMin(input, axis, options), MLGraphBuilder/argMax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-argmin-input-axis-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑥">MLOperand</a></code>. The input N-D tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/argMin(input, axis, options), MLGraphBuilder/argMax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-argmin-input-axis-options-axis"><code>axis</code></dfn>: The dimension to reduce. The value must be in the range [0, N-1] where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank">rank</a> of the input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/argMin(input, axis, options), MLGraphBuilder/argMax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-argmin-input-axis-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlargminmaxoptions" id="ref-for-dictdef-mlargminmaxoptions③">MLArgMinMaxOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑥">MLOperand</a></code>. The N-D tensor of the reduced shape. The values must be of type <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlargminmaxoptions-outputdatatype" id="ref-for-dom-mlargminmaxoptions-outputdatatype①">outputDataType</a></code> in the range [0, N-1] where N is the size of the input dimension specified by axis.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑦">MLOperand</a></code>. The N-D tensor of the reduced shape. The values must be of type <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlargminmaxoptions-outputdatatype" id="ref-for-dom-mlargminmaxoptions-outputdatatype①">outputDataType</a></code> in the range [0, N-1] where N is the size of the input dimension specified by axis.</p>
    </div>
    <details class="algorithm" data-algorithm="argminmax-op" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="argminmax-op" data-noexport id="mlgraphbuilder-argminmax-op">create argMin/argMax operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string②">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑦">MLOperand</a></code> <var>input</var>, <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥">unsigned long</a></code> <var>axis</var>, and <code class="idl"><a data-link-type="idl" href="#dictdef-mlargminmaxoptions" id="ref-for-dictdef-mlargminmaxoptions④">MLArgMinMaxOptions</a></code> <var>options</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="argminmax-op" data-noexport id="mlgraphbuilder-argminmax-op">create argMin/argMax operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string②">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑧">MLOperand</a></code> <var>input</var>, <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥">unsigned long</a></code> <var>axis</var>, and <code class="idl"><a data-link-type="idl" href="#dictdef-mlargminmaxoptions" id="ref-for-dictdef-mlargminmaxoptions④">MLArgMinMaxOptions</a></code> <var>options</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#assert" id="ref-for-assert①">Assert</a>: <var>op</var> is one of "argMin", "argMax".</p>
@@ -2446,7 +2458,7 @@ <h4 class="heading settled" data-level="7.7.5" id="api-mlgraphbuilder-argminmax"
       <p><em>Make graph connections:</em></p>
       <ol>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑧">operator</a> for the <var>op</var> operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①②">operator</a> for the <var>op</var> operation, given <var>options</var>.</p>
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand③">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this③③">this</a> and <var>desc</var>.</p>
        <li data-md>
@@ -2491,24 +2503,24 @@ <h4 class="heading settled" data-level="7.7.5" id="api-mlgraphbuilder-argminmax"
    </details>
    <h4 class="heading settled" data-level="7.7.6" id="api-mlgraphbuilder-batchnorm"><span class="secno">7.7.6. </span><span class="content">batchNormalization</span><a class="self-link" href="#api-mlgraphbuilder-batchnorm"></a></h4>
     Normalize the values of the input tensor using <a data-link-type="biblio" href="#biblio-batch-normalization" title="Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift">[Batch-Normalization]</a>. For each input feature, the mean and variance values of that feature are computed across all the samples in the batch dimension while the model is trained. These mean and variance values are then subsequently given to this operation during model inference. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlbatchnormalizationoptions"><code><c- g>MLBatchNormalizationOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlbatchnormalizationoptions-scale" id="ref-for-dom-mlbatchnormalizationoptions-scale"><c- g>scale</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlbatchnormalizationoptions-bias" id="ref-for-dom-mlbatchnormalizationoptions-bias"><c- g>bias</c-></a>;
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlbatchnormalizationoptions"><code><c- g>MLBatchNormalizationOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑤⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlbatchnormalizationoptions-scale" id="ref-for-dom-mlbatchnormalizationoptions-scale"><c- g>scale</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlbatchnormalizationoptions-bias" id="ref-for-dom-mlbatchnormalizationoptions-bias"><c- g>bias</c-></a>;
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑦"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlbatchnormalizationoptions-axis" id="ref-for-dom-mlbatchnormalizationoptions-axis"><c- g>axis</c-></a> = 1;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①"><c- b>double</c-></a> <a class="idl-code" data-default="1e-5" data-link-type="dict-member" data-type="double" href="#dom-mlbatchnormalizationoptions-epsilon" id="ref-for-dom-mlbatchnormalizationoptions-epsilon"><c- g>epsilon</c-></a> = 1e-5;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②②"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-batchnormalization" id="ref-for-dom-mlgraphbuilder-batchnormalization"><c- g>batchNormalization</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean"><c- g>mean</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance"><c- g>variance</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②③"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-batchnormalization" id="ref-for-dom-mlgraphbuilder-batchnormalization"><c- g>batchNormalization</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean"><c- g>mean</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance"><c- g>variance</c-></a>,
                                <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlbatchnormalizationoptions" id="ref-for-dictdef-mlbatchnormalizationoptions"><c- n>MLBatchNormalizationOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-options" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlbatchnormalizationoptions" id="ref-for-dictdef-mlbatchnormalizationoptions①">MLBatchNormalizationOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLBatchNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlbatchnormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥④">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLBatchNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlbatchnormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥⑤">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D tensor of the scaling values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③">size</a> is equal to the size of the input dimension denoted by <code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-axis" id="ref-for-dom-mlbatchnormalizationoptions-axis①">axis</a></code>.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLBatchNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlbatchnormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥⑤">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLBatchNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlbatchnormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑥⑥">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D tensor of the bias values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④">size</a> is equal to the size of the input dimension denoted by <code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-axis" id="ref-for-dom-mlbatchnormalizationoptions-axis②">axis</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLBatchNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlbatchnormalizationoptions-axis"><code>axis</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑧">unsigned long</a>, defaulting to <code>1</code></span>
@@ -2522,15 +2534,15 @@ <h4 class="heading settled" data-level="7.7.6" id="api-mlgraphbuilder-batchnorm"
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥⑥">MLOperand</a></code>. The input N-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥⑦">MLOperand</a></code>. The input N-D tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean"><code>mean</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥⑦">MLOperand</a></code>. Specifies the 1-D tensor of the mean values of the input features across the batch. Its <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size⑤">size</a> is equal to the size of the input dimension denoted by <code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-axis" id="ref-for-dom-mlbatchnormalizationoptions-axis③">axis</a></code>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean"><code>mean</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥⑧">MLOperand</a></code>. Specifies the 1-D tensor of the mean values of the input features across the batch. Its <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size⑤">size</a> is equal to the size of the input dimension denoted by <code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-axis" id="ref-for-dom-mlbatchnormalizationoptions-axis③">axis</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance"><code>variance</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥⑧">MLOperand</a></code>. The 1-D tensor of the variance values of the input features across the batch whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size⑥">size</a> is equal to the size of the input dimension denoted by <code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-axis" id="ref-for-dom-mlbatchnormalizationoptions-axis④">axis</a></code>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance"><code>variance</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥⑨">MLOperand</a></code>. The 1-D tensor of the variance values of the input features across the batch whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size⑥">size</a> is equal to the size of the input dimension denoted by <code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-axis" id="ref-for-dom-mlbatchnormalizationoptions-axis④">axis</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlbatchnormalizationoptions" id="ref-for-dictdef-mlbatchnormalizationoptions②">MLBatchNormalizationOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑥⑨">MLOperand</a></code>. The batch-normalized N-D tensor of the same shape as <em>input</em>.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⓪">MLOperand</a></code>. The batch-normalized N-D tensor of the same shape as <em>input</em>.</p>
    </div>
    <details class="algorithm" data-algorithm="batchNormalization(input, mean, variance, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="batchNormalization(input, mean, variance, options)|batchNormalization(input, mean, variance)" id="dom-mlgraphbuilder-batchnormalization"><code>batchNormalization(<var>input</var>, <var>mean</var>, <var>variance</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -2573,7 +2585,7 @@ <h4 class="heading settled" data-level="7.7.6" id="api-mlgraphbuilder-batchnorm"
       <p><em>Make graph connections:</em></p>
       <ol>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑨">operator</a> for the "batchNormalization" operation, given <var>input</var>, <var>mean</var>, <var>variance</var> and <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①③">operator</a> for the "batchNormalization" operation, given <var>input</var>, <var>mean</var>, <var>variance</var> and <var>options</var>.</p>
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand④">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this③⑥">this</a> and <var>input</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-descriptor-slot" id="ref-for-dom-mloperand-descriptor-slot⑦">[[descriptor]]</a></code>.</p>
        <li data-md>
@@ -2611,23 +2623,27 @@ <h4 class="heading settled" data-level="7.7.6" id="api-mlgraphbuilder-batchnorm"
    </div>
    <h4 class="heading settled" data-level="7.7.7" id="api-mlgraphbuilder-cast"><span class="secno">7.7.7. </span><span class="content">cast</span><a class="self-link" href="#api-mlgraphbuilder-cast"></a></h4>
     Cast each element in the input tensor to the target data type. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②③"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast"><c- g>cast</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①③"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-type" id="ref-for-dom-mlgraphbuilder-cast-input-type-type"><c- g>type</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②④"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast"><c- g>cast</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input"><c- g>input</c-></a>,
+                 <a data-link-type="idl-name" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①③"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-options-type" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-type"><c- g>type</c-></a>,
+                 <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-options-options" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/cast(input, type)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-cast-input-type-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦②">MLOperand</a></code>. The input N-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/cast(input, type, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-cast-input-type-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦③">MLOperand</a></code>. The input N-D tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/cast(input, type)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-cast-input-type-type"><code>type</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①④">MLOperandDataType</a></code>. The target data type.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/cast(input, type, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-cast-input-type-options-type"><code>type</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①④">MLOperandDataType</a></code>. The target data type.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/cast(input, type, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-cast-input-type-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦③">MLOperand</a></code>. The N-D tensor of the same shape as <em>input</em> with each element casted to the target data type.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦④">MLOperand</a></code>. The N-D tensor of the same shape as <em>input</em> with each element casted to the target data type.</p>
    </div>
-   <p>Casting between <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①⑤">MLOperandDataType</a></code>s is specified for some cases and <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined①">implementation-defined</a> in other cases, according to the following table:</p>
+   <p>Casting between <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①⑤">MLOperandDataType</a></code>s is specified for some cases and <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined②">implementation-defined</a> in other cases, according to the following table:</p>
    <table class="grid">
-    <caption> Behavior of the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast①">cast()</a></code> operation given the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-input①">input</a></code>'s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①②">dataType</a> (rows) and target <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-type" id="ref-for-dom-mlgraphbuilder-cast-input-type-type①">type</a></code> (columns). </caption>
+    <caption> Behavior of the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast①">cast()</a></code> operation given the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input①">input</a></code>'s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①②">dataType</a> (rows) and target <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-type" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-type①">type</a></code> (columns). </caption>
     <tbody>
      <tr>
       <th class="split"> <span class="top-right">Target type</span> <span class="bottom-left">Input type</span> 
@@ -2640,7 +2656,7 @@ <h4 class="heading settled" data-level="7.7.7" id="api-mlgraphbuilder-cast"><spa
        <p>If out of range, +/-Infinity.</p>
       <td>
         If in range, truncated. 
-       <p>If out of range, <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined②">implementation-defined</a>.</p>
+       <p>If out of range, <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined③">implementation-defined</a>.</p>
      <tr>
       <th> <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32①">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32②">"uint32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64②">"int64"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint64" id="ref-for-dom-mloperanddatatype-uint64②">"uint64"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8②">"int8"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8①">"uint8"</a></code> 
       <td>
@@ -2650,9 +2666,9 @@ <h4 class="heading settled" data-level="7.7.7" id="api-mlgraphbuilder-cast"><spa
         If in range, same value. 
        <p>If out of range, lowest N bits reinterpreted as target type, assuming two’s complement for signed types.</p>
    </table>
-   <p class="note" role="note"><span class="marker">NOTE:</span> For example, casting -1 from <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8③">"int8"</a></code> to <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8②">"uint8"</a></code> is specified to yield 255. But casting -1 from <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④">"float32"</a></code> to <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8③">"uint8"</a></code> is <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined③">implementation-defined</a>.</p>
-   <details class="algorithm" data-algorithm="cast(input, type)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-cast"><code>cast(<var>input</var>, <var>type</var>)</code></dfn> method steps are: </summary>
+   <p class="note" role="note"><span class="marker">NOTE:</span> For example, casting -1 from <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8③">"int8"</a></code> to <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8②">"uint8"</a></code> is specified to yield 255. But casting -1 from <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④">"float32"</a></code> to <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8③">"uint8"</a></code> is <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined④">implementation-defined</a>.</p>
+   <details class="algorithm" data-algorithm="cast(input, type, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="cast(input, type, options)|cast(input, type)" id="dom-mlgraphbuilder-cast"><code>cast(<var>input</var>, <var>type</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this③⑦">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot⑧">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⓪">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror⑥">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException①⑥">DOMException</a></code>.</p>
@@ -2662,7 +2678,7 @@ <h4 class="heading settled" data-level="7.7.7" id="api-mlgraphbuilder-cast"><spa
       <p><em>Make graph connections:</em></p>
       <ol>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⓪">operator</a> for the "cast" operation, given <var>type</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①④">operator</a> for the "cast" operation, given <var>type</var> and <var>options</var>.</p>
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
@@ -2678,13 +2694,13 @@ <h4 class="heading settled" data-level="7.7.7" id="api-mlgraphbuilder-cast"><spa
    </details>
    <h4 class="heading settled" data-level="7.7.8" id="api-mlgraphbuilder-clamp"><span class="secno">7.7.8. </span><span class="content">clamp</span><a class="self-link" href="#api-mlgraphbuilder-clamp"></a></h4>
     Clamp the input tensor element-wise within a range specified by the minimum and maximum values. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlclampoptions"><code><c- g>MLClampOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlclampoptions"><code><c- g>MLClampOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber⑤"><c- n>MLNumber</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLNumber" href="#dom-mlclampoptions-minvalue" id="ref-for-dom-mlclampoptions-minvalue"><c- g>minValue</c-></a>;
   <a data-link-type="idl-name" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber⑥"><c- n>MLNumber</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLNumber" href="#dom-mlclampoptions-maxvalue" id="ref-for-dom-mlclampoptions-maxvalue"><c- g>maxValue</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②④"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp①"><c- g>clamp</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlclampoptions" id="ref-for-dictdef-mlclampoptions"><c- n>MLClampOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-clamp-input-options-options" id="ref-for-dom-mlgraphbuilder-clamp-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑤"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp①"><c- g>clamp</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlclampoptions" id="ref-for-dictdef-mlclampoptions"><c- n>MLClampOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-clamp-input-options-options" id="ref-for-dom-mlgraphbuilder-clamp-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlclampoptions" id="ref-for-dictdef-mlclampoptions①">MLClampOptions</a></code> has the following members:</p>
@@ -2700,14 +2716,14 @@ <h4 class="heading settled" data-level="7.7.8" id="api-mlgraphbuilder-clamp"><sp
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/clamp(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-clamp-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑥">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/clamp(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-clamp-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑦">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/clamp(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-clamp-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlclampoptions" id="ref-for-dictdef-mlclampoptions②">MLClampOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
      <strong>Returns:</strong> 
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑦">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑧">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
    <details class="algorithm" data-algorithm="clamp(input, options)" data-algorithm-for="MLGraphBuilder" open>
@@ -2733,7 +2749,7 @@ <h4 class="heading settled" data-level="7.7.8" id="api-mlgraphbuilder-clamp"><sp
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①①">operator</a> for the "clamp" operation, given <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlclampoptions-minvalue" id="ref-for-dom-mlclampoptions-minvalue④">minValue</a></code> and <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlclampoptions-maxvalue" id="ref-for-dom-mlclampoptions-maxvalue④">maxValue</a></code>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑤">operator</a> for the "clamp" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot⑤">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -2773,26 +2789,30 @@ <h4 class="heading settled" data-level="7.7.8" id="api-mlgraphbuilder-clamp"><sp
    </div>
    <h4 class="heading settled" data-level="7.7.9" id="api-mlgraphbuilder-concat"><span class="secno">7.7.9. </span><span class="content">concat</span><a class="self-link" href="#api-mlgraphbuilder-concat"></a></h4>
     Concatenates the input tensors along a given axis. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑤"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-concat" id="ref-for-dom-mlgraphbuilder-concat"><c- g>concat</c-></a>(<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦⑨"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-inputs" id="ref-for-dom-mlgraphbuilder-concat-inputs-axis-inputs"><c- g>inputs</c-></a>, [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange④"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑨"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-axis" id="ref-for-dom-mlgraphbuilder-concat-inputs-axis-axis"><c- g>axis</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑥"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑦⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-concat" id="ref-for-dom-mlgraphbuilder-concat"><c- g>concat</c-></a>(<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧⓪"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-options-inputs" id="ref-for-dom-mlgraphbuilder-concat-inputs-axis-options-inputs"><c- g>inputs</c-></a>,
+                   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange④"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑨"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-options-axis" id="ref-for-dom-mlgraphbuilder-concat-inputs-axis-options-axis"><c- g>axis</c-></a>,
+                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-options-options" id="ref-for-dom-mlgraphbuilder-concat-inputs-axis-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/concat(inputs, axis)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-concat-inputs-axis-inputs"><code>inputs</code></dfn>: a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧⓪">MLOperand</a></code>>. All input tensors must have the
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/concat(inputs, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-concat-inputs-axis-options-inputs"><code>inputs</code></dfn>: a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧①">MLOperand</a></code>>. All input tensors must have the
 same shape, except for the size of the dimension to concatenate on.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/concat(inputs, axis)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-concat-inputs-axis-axis"><code>axis</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①⓪">unsigned long</a></code> scalar. The axis that the inputs concatenate along. Its value must be in the range [0, N-1] where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③">rank</a> of the input tensors.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/concat(inputs, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-concat-inputs-axis-options-axis"><code>axis</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①⓪">unsigned long</a></code> scalar. The axis that the inputs concatenate along. Its value must be in the range [0, N-1] where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③">rank</a> of the input tensors.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/concat(inputs, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-concat-inputs-axis-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧①">MLOperand</a></code>. The concatenated tensor of all the inputs along
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧②">MLOperand</a></code>. The concatenated tensor of all the inputs along
     the <em>axis</em>. The output tensor has the same shape except on the dimension
     that all the inputs concatenated along. The size of that dimension is
     computed as the sum of all the input sizes of the same dimension.</p>
    </div>
-   <details class="algorithm" data-algorithm="concat(inputs, axis)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-concat"><code>concat(<var>inputs</var>, <var>axis</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="concat(inputs, axis, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="concat(inputs, axis, options)|concat(inputs, axis)" id="dom-mlgraphbuilder-concat"><code>concat(<var>inputs</var>, <var>axis</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this④①">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot①⓪">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror⑧">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException①⑧">DOMException</a></code>.</p>
@@ -2841,7 +2861,7 @@ <h4 class="heading settled" data-level="7.7.9" id="api-mlgraphbuilder-concat"><s
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand⑤">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this④③">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①②">operator</a> for the "concat" operation, given <var>inputs</var> and <var>axis</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑥">operator</a> for the "concat" operation, given <var>inputs</var>, <var>axis</var>, and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot⑥">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -2862,19 +2882,19 @@ <h4 class="heading settled" data-level="7.7.10" id="api-mlgraphbuilder-conv2d"><
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLConv2dFilterOperandLayout" data-dfn-type="enum-value" data-export id="dom-mlconv2dfilteroperandlayout-ihwo"><code><c- s>"ihwo"</c-></code></dfn>
 };
 
-<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlconv2doptions"><code><c- g>MLConv2dOptions</c-></code></dfn> {
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlconv2doptions"><code><c- g>MLConv2dOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑤"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange⑤"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①①"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconv2doptions-padding" id="ref-for-dom-mlconv2doptions-padding"><c- g>padding</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑥"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange⑥"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①②"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconv2doptions-strides" id="ref-for-dom-mlconv2doptions-strides"><c- g>strides</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑦"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange⑦"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①③"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconv2doptions-dilations" id="ref-for-dom-mlconv2doptions-dilations"><c- g>dilations</c-></a>;
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange⑧"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①④"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups"><c- g>groups</c-></a> = 1;
   <a data-link-type="idl-name" href="#enumdef-mlinputoperandlayout" id="ref-for-enumdef-mlinputoperandlayout"><c- n>MLInputOperandLayout</c-></a> <a class="idl-code" data-default="&quot;nchw&quot;" data-link-type="dict-member" data-type="MLInputOperandLayout" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout"><c- g>inputLayout</c-></a> = "nchw";
   <a data-link-type="idl-name" href="#enumdef-mlconv2dfilteroperandlayout" id="ref-for-enumdef-mlconv2dfilteroperandlayout"><c- n>MLConv2dFilterOperandLayout</c-></a> <a class="idl-code" data-default="&quot;oihw&quot;" data-link-type="dict-member" data-type="MLConv2dFilterOperandLayout" href="#dom-mlconv2doptions-filterlayout" id="ref-for-dom-mlconv2doptions-filterlayout"><c- g>filterLayout</c-></a> = "oihw";
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlconv2doptions-bias" id="ref-for-dom-mlconv2doptions-bias"><c- g>bias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlconv2doptions-bias" id="ref-for-dom-mlconv2doptions-bias"><c- g>bias</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑥"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-conv2d" id="ref-for-dom-mlgraphbuilder-conv2d"><c- g>conv2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-conv2d-input-filter-options-input" id="ref-for-dom-mlgraphbuilder-conv2d-input-filter-options-input"><c- g>input</c-></a>,
-                   <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-conv2d-input-filter-options-filter" id="ref-for-dom-mlgraphbuilder-conv2d-input-filter-options-filter"><c- g>filter</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑦"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-conv2d" id="ref-for-dom-mlgraphbuilder-conv2d"><c- g>conv2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-conv2d-input-filter-options-input" id="ref-for-dom-mlgraphbuilder-conv2d-input-filter-options-input"><c- g>input</c-></a>,
+                   <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-conv2d-input-filter-options-filter" id="ref-for-dom-mlgraphbuilder-conv2d-input-filter-options-filter"><c- g>filter</c-></a>,
                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlconv2doptions" id="ref-for-dictdef-mlconv2doptions"><c- n>MLConv2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-conv2d-input-filter-options-options" id="ref-for-dom-mlgraphbuilder-conv2d-input-filter-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
@@ -2931,7 +2951,7 @@ <h4 class="heading settled" data-level="7.7.10" id="api-mlgraphbuilder-conv2d"><
       <li data-md>
        <p><code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-ihwo" id="ref-for-dom-mlconv2dfilteroperandlayout-ihwo">"ihwo"</a></code>: <em>[inputChannels/groups, height, width, outputChannels]</em></p>
      </ul>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLConv2dOptions" data-dfn-type="dict-member" data-export id="dom-mlconv2doptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧⑥">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLConv2dOptions" data-dfn-type="dict-member" data-export id="dom-mlconv2doptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑧⑦">MLOperand</a></span>
     <dd data-md>
      <p>An additional 1-D tensor with the shape of <em>[outputChannels]</em> whose values are to be added to the convolution result.</p>
    </dl>
@@ -2939,15 +2959,15 @@ <h4 class="heading settled" data-level="7.7.10" id="api-mlgraphbuilder-conv2d"><
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧⑦">MLOperand</a></code>. The input 4-D tensor. The logical shape
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧⑧">MLOperand</a></code>. The input 4-D tensor. The logical shape
 is interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout①">inputLayout</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-filter"><code>filter</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧⑧">MLOperand</a></code>. The filter 4-D tensor. The logical shape is
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-filter"><code>filter</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧⑨">MLOperand</a></code>. The filter 4-D tensor. The logical shape is
 interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-filterlayout" id="ref-for-dom-mlconv2doptions-filterlayout①">filterLayout</a></code> and <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups①">groups</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mlconv2doptions" id="ref-for-dictdef-mlconv2doptions②">MLConv2dOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧⑨">MLOperand</a></code>. The output 4-D tensor that contains the convolution result. The output shape is interpreted according to the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout②">inputLayout</a></code> value. More specifically, the spatial dimensions or the sizes of the last two dimensions of the output tensor for the <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw③">"nchw"</a></code> input layout can be calculated as follows:</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⓪">MLOperand</a></code>. The output 4-D tensor that contains the convolution result. The output shape is interpreted according to the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout②">inputLayout</a></code> value. More specifically, the spatial dimensions or the sizes of the last two dimensions of the output tensor for the <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw③">"nchw"</a></code> input layout can be calculated as follows:</p>
     <p><code>outputSize = 1 + (inputSize - (filterSize - 1) * dilation - 1 + beginningPadding + endingPadding) / stride</code></p>
    </div>
    <div class="note" role="note"> A <em>depthwise</em> conv2d operation is a variant of grouped convolution, used in models like the MobileNet, where the <em>options.groups</em> = inputChannels = outputChannels and the shape of filter tensor is <em>[options.groups, 1, height, width]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-oihw" id="ref-for-dom-mlconv2dfilteroperandlayout-oihw①">"oihw"</a></code> layout, <em>[height, width, 1, options.groups]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-hwio" id="ref-for-dom-mlconv2dfilteroperandlayout-hwio①">"hwio"</a></code> layout, <em>[options.groups, height, width, 1]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-ohwi" id="ref-for-dom-mlconv2dfilteroperandlayout-ohwi①">"ohwi"</a></code> layout and <em>[1, height, width, options.groups]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-ihwo" id="ref-for-dom-mlconv2dfilteroperandlayout-ihwo①">"ihwo"</a></code> layout. </div>
@@ -3128,7 +3148,7 @@ <h4 class="heading settled" data-level="7.7.10" id="api-mlgraphbuilder-conv2d"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand⑥">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this④⑥">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①③">operator</a> for the "conv2d" operation, given <var>options</var> and <var>filter</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑦">operator</a> for the "conv2d" operation, given <var>options</var> and <var>filter</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot⑦">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -3150,7 +3170,7 @@ <h4 class="heading settled" data-level="7.7.11" id="api-mlgraphbuilder-convtrans
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLConvTranspose2dFilterOperandLayout" data-dfn-type="enum-value" data-export id="dom-mlconvtranspose2dfilteroperandlayout-ohwi"><code><c- s>"ohwi"</c-></code></dfn>
 };
 
-<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlconvtranspose2doptions"><code><c- g>MLConvTranspose2dOptions</c-></code></dfn> {
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlconvtranspose2doptions"><code><c- g>MLConvTranspose2dOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑨"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑧"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange⑨"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①⑥"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconvtranspose2doptions-padding" id="ref-for-dom-mlconvtranspose2doptions-padding"><c- g>padding</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑨"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①⓪"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①⑦"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconvtranspose2doptions-strides" id="ref-for-dom-mlconvtranspose2doptions-strides"><c- g>strides</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⓪"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long①⑧"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconvtranspose2doptions-dilations" id="ref-for-dom-mlconvtranspose2doptions-dilations"><c- g>dilations</c-></a>;
@@ -3159,11 +3179,11 @@ <h4 class="heading settled" data-level="7.7.11" id="api-mlgraphbuilder-convtrans
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①④"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②①"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlconvtranspose2doptions-groups" id="ref-for-dom-mlconvtranspose2doptions-groups"><c- g>groups</c-></a> = 1;
   <a data-link-type="idl-name" href="#enumdef-mlinputoperandlayout" id="ref-for-enumdef-mlinputoperandlayout②"><c- n>MLInputOperandLayout</c-></a> <a class="idl-code" data-default="&quot;nchw&quot;" data-link-type="dict-member" data-type="MLInputOperandLayout" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout"><c- g>inputLayout</c-></a> = "nchw";
   <a data-link-type="idl-name" href="#enumdef-mlconvtranspose2dfilteroperandlayout" id="ref-for-enumdef-mlconvtranspose2dfilteroperandlayout"><c- n>MLConvTranspose2dFilterOperandLayout</c-></a> <a class="idl-code" data-default="&quot;iohw&quot;" data-link-type="dict-member" data-type="MLConvTranspose2dFilterOperandLayout" href="#dom-mlconvtranspose2doptions-filterlayout" id="ref-for-dom-mlconvtranspose2doptions-filterlayout"><c- g>filterLayout</c-></a> = "iohw";
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlconvtranspose2doptions-bias" id="ref-for-dom-mlconvtranspose2doptions-bias"><c- g>bias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlconvtranspose2doptions-bias" id="ref-for-dom-mlconvtranspose2doptions-bias"><c- g>bias</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑦"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-convtranspose2d" id="ref-for-dom-mlgraphbuilder-convtranspose2d"><c- g>convTranspose2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-convtranspose2d-input-filter-options-input" id="ref-for-dom-mlgraphbuilder-convtranspose2d-input-filter-options-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-convtranspose2d-input-filter-options-filter" id="ref-for-dom-mlgraphbuilder-convtranspose2d-input-filter-options-filter"><c- g>filter</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑧"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-convtranspose2d" id="ref-for-dom-mlgraphbuilder-convtranspose2d"><c- g>convTranspose2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-convtranspose2d-input-filter-options-input" id="ref-for-dom-mlgraphbuilder-convtranspose2d-input-filter-options-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-convtranspose2d-input-filter-options-filter" id="ref-for-dom-mlgraphbuilder-convtranspose2d-input-filter-options-filter"><c- g>filter</c-></a>,
                             <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlconvtranspose2doptions" id="ref-for-dictdef-mlconvtranspose2doptions"><c- n>MLConvTranspose2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-convtranspose2d-input-filter-options-options" id="ref-for-dom-mlgraphbuilder-convtranspose2d-input-filter-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
@@ -3229,7 +3249,7 @@ <h4 class="heading settled" data-level="7.7.11" id="api-mlgraphbuilder-convtrans
       <li data-md>
        <p><code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2dfilteroperandlayout-ohwi" id="ref-for-dom-mlconvtranspose2dfilteroperandlayout-ohwi">"ohwi"</a></code>: <em>[outputChannels/groups, height, width, inputChannels]</em></p>
      </ul>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLConvTranspose2dOptions" data-dfn-type="dict-member" data-export id="dom-mlconvtranspose2doptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨④">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLConvTranspose2dOptions" data-dfn-type="dict-member" data-export id="dom-mlconvtranspose2doptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨⑤">MLOperand</a></span>
     <dd data-md>
      <p>An additional 1-D tensor with the shape of <em>[outputChannels]</em> whose values are to be added to the convolution result.</p>
    </dl>
@@ -3237,15 +3257,15 @@ <h4 class="heading settled" data-level="7.7.11" id="api-mlgraphbuilder-convtrans
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑤">MLOperand</a></code>. The input 4-D tensor. The logical shape
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑥">MLOperand</a></code>. The input 4-D tensor. The logical shape
 is interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout①">inputLayout</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-filter"><code>filter</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑥">MLOperand</a></code>. The filter 4-D tensor. The logical shape is
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-filter"><code>filter</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑦">MLOperand</a></code>. The filter 4-D tensor. The logical shape is
 interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-filterlayout" id="ref-for-dom-mlconvtranspose2doptions-filterlayout①">filterLayout</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-groups" id="ref-for-dom-mlconvtranspose2doptions-groups①">groups</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlconvtranspose2doptions" id="ref-for-dictdef-mlconvtranspose2doptions②">MLConvTranspose2dOptions</a></code>.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑦">MLOperand</a></code>. The output 4-D tensor that contains the transposed convolution result. The output shape is interpreted according to the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout②">inputLayout</a></code> value. More specifically, unless the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputsizes" id="ref-for-dom-mlconvtranspose2doptions-outputsizes①">outputSizes</a></code> values are explicitly specified, the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputpadding" id="ref-for-dom-mlconvtranspose2doptions-outputpadding②">outputPadding</a></code> may be needed to compute the spatial dimension values of the output tensor as follows:</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑧">MLOperand</a></code>. The output 4-D tensor that contains the transposed convolution result. The output shape is interpreted according to the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout②">inputLayout</a></code> value. More specifically, unless the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputsizes" id="ref-for-dom-mlconvtranspose2doptions-outputsizes①">outputSizes</a></code> values are explicitly specified, the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputpadding" id="ref-for-dom-mlconvtranspose2doptions-outputpadding②">outputPadding</a></code> may be needed to compute the spatial dimension values of the output tensor as follows:</p>
     <p><code>outputSize = (inputSize - 1) * stride + (filterSize - 1) * dilation + 1 - beginningPadding - endingPadding + outputPadding</code></p>
    </div>
    <details class="algorithm" data-algorithm="calculate convtranspose output size" data-algorithm-for="MLGraphBuilder" open>
@@ -3431,7 +3451,7 @@ <h4 class="heading settled" data-level="7.7.11" id="api-mlgraphbuilder-convtrans
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand⑦">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this④⑨">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①④">operator</a> for the "convTranspose2d" operation, given <var>options</var> and <var>filter</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑧">operator</a> for the "convTranspose2d" operation, given <var>options</var> and <var>filter</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot⑧">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -3448,25 +3468,27 @@ <h4 class="heading settled" data-level="7.7.11" id="api-mlgraphbuilder-convtrans
    <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><span class="secno">7.7.12. </span><span class="content">Element-wise binary operations</span><a class="self-link" href="#api-mlgraphbuilder-binary"></a></h4>
     Compute the element-wise binary addition, subtraction, multiplication, division, power, maximum and minimum of the two input tensors. 
    <p>The operation will be broadcast according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The input tensors must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable">bidirectionally broadcastable</a>. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①②">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①③">rank</a> of the input tensors. For each dimension of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑧"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-add" id="ref-for-dom-mlgraphbuilder-add"><c- g>add</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a" id="ref-for-dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b" id="ref-for-dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sub" id="ref-for-dom-mlgraphbuilder-sub"><c- g>sub</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a" id="ref-for-dom-mlgraphbuilder-add-a-b-a①"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b" id="ref-for-dom-mlgraphbuilder-add-a-b-b①"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-mul" id="ref-for-dom-mlgraphbuilder-mul"><c- g>mul</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a" id="ref-for-dom-mlgraphbuilder-add-a-b-a②"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b" id="ref-for-dom-mlgraphbuilder-add-a-b-b②"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-div" id="ref-for-dom-mlgraphbuilder-div"><c- g>div</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a" id="ref-for-dom-mlgraphbuilder-add-a-b-a③"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b" id="ref-for-dom-mlgraphbuilder-add-a-b-b③"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-max" id="ref-for-dom-mlgraphbuilder-max"><c- g>max</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a" id="ref-for-dom-mlgraphbuilder-add-a-b-a④"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b" id="ref-for-dom-mlgraphbuilder-add-a-b-b④"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-min" id="ref-for-dom-mlgraphbuilder-min"><c- g>min</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a" id="ref-for-dom-mlgraphbuilder-add-a-b-a⑤"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b" id="ref-for-dom-mlgraphbuilder-add-a-b-b⑤"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-pow" id="ref-for-dom-mlgraphbuilder-pow"><c- g>pow</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a" id="ref-for-dom-mlgraphbuilder-add-a-b-a⑥"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b" id="ref-for-dom-mlgraphbuilder-add-a-b-b⑥"><c- g>b</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑨"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-add" id="ref-for-dom-mlgraphbuilder-add"><c- g>add</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a" id="ref-for-dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b" id="ref-for-dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①⓪"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options" id="ref-for-dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sub" id="ref-for-dom-mlgraphbuilder-sub"><c- g>sub</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a" id="ref-for-dom-mlgraphbuilder-add-a-b-options-a①"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b" id="ref-for-dom-mlgraphbuilder-add-a-b-options-b①"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①①"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options" id="ref-for-dom-mlgraphbuilder-add-a-b-options-options①"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-mul" id="ref-for-dom-mlgraphbuilder-mul"><c- g>mul</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a" id="ref-for-dom-mlgraphbuilder-add-a-b-options-a②"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b" id="ref-for-dom-mlgraphbuilder-add-a-b-options-b②"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①②"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options" id="ref-for-dom-mlgraphbuilder-add-a-b-options-options②"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-div" id="ref-for-dom-mlgraphbuilder-div"><c- g>div</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⓪⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a" id="ref-for-dom-mlgraphbuilder-add-a-b-options-a③"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b" id="ref-for-dom-mlgraphbuilder-add-a-b-options-b③"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①③"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options" id="ref-for-dom-mlgraphbuilder-add-a-b-options-options③"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-max" id="ref-for-dom-mlgraphbuilder-max"><c- g>max</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a" id="ref-for-dom-mlgraphbuilder-add-a-b-options-a④"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b" id="ref-for-dom-mlgraphbuilder-add-a-b-options-b④"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①④"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options" id="ref-for-dom-mlgraphbuilder-add-a-b-options-options④"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-min" id="ref-for-dom-mlgraphbuilder-min"><c- g>min</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a" id="ref-for-dom-mlgraphbuilder-add-a-b-options-a⑤"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b" id="ref-for-dom-mlgraphbuilder-add-a-b-options-b⑤"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①⑤"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options" id="ref-for-dom-mlgraphbuilder-add-a-b-options-options⑤"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-pow" id="ref-for-dom-mlgraphbuilder-pow"><c- g>pow</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a" id="ref-for-dom-mlgraphbuilder-add-a-b-options-a⑥"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①①⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b" id="ref-for-dom-mlgraphbuilder-add-a-b-options-b⑥"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①⑥"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options" id="ref-for-dom-mlgraphbuilder-add-a-b-options-options⑥"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/add(a, b), MLGraphBuilder/sub(a, b), MLGraphBuilder/mul(a, b), MLGraphBuilder/div(a, b), MLGraphBuilder/max(a, b), MLGraphBuilder/min(a, b), MLGraphBuilder/pow(a, b)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-add-a-b-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①①⑨">MLOperand</a></code>. The first input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/add(a, b, options), MLGraphBuilder/sub(a, b, options), MLGraphBuilder/mul(a, b, options), MLGraphBuilder/div(a, b, options), MLGraphBuilder/max(a, b, options), MLGraphBuilder/min(a, b, options), MLGraphBuilder/pow(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-add-a-b-options-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②⓪">MLOperand</a></code>. The first input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/add(a, b, options), MLGraphBuilder/sub(a, b, options), MLGraphBuilder/mul(a, b, options), MLGraphBuilder/div(a, b, options), MLGraphBuilder/max(a, b, options), MLGraphBuilder/min(a, b, options), MLGraphBuilder/pow(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-add-a-b-options-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②①">MLOperand</a></code>. The second input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/add(a, b), MLGraphBuilder/sub(a, b), MLGraphBuilder/mul(a, b), MLGraphBuilder/div(a, b), MLGraphBuilder/max(a, b), MLGraphBuilder/min(a, b), MLGraphBuilder/pow(a, b)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-add-a-b-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②⓪">MLOperand</a></code>. The second input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/add(a, b, options), MLGraphBuilder/sub(a, b, options), MLGraphBuilder/mul(a, b, options), MLGraphBuilder/div(a, b, options), MLGraphBuilder/max(a, b, options), MLGraphBuilder/min(a, b, options), MLGraphBuilder/pow(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-add-a-b-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①⑦">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②①">MLOperand</a></code>. The output tensor that contains the result of
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②②">MLOperand</a></code>. The output tensor that contains the result of
     element-wise binary operation of the two input tensors.</p>
    </div>
    <div>
@@ -3489,7 +3511,7 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
     </ul>
    </div>
    <details class="algorithm" data-algorithm="element-wise-binary-op" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="element-wise-binary-op" data-noexport id="mlgraphbuilder-element-wise-binary-op">create element-wise binary operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string③">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②②">MLOperand</a></code> <var>a</var> and <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②③">MLOperand</a></code> <var>b</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="element-wise-binary-op" data-noexport id="mlgraphbuilder-element-wise-binary-op">create element-wise binary operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string③">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②③">MLOperand</a></code> <var>a</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①②④">MLOperand</a></code> <var>b</var>, and <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①⑧">MLOperatorOptions</a></code> <var>options</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#assert" id="ref-for-assert②">Assert</a>: <var>op</var> is one of "add", "sub", "mul", "div", "max", "min", "pow".</p>
@@ -3513,7 +3535,7 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand⑧">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑤②">this</a> and <var>descriptor</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑤">operator</a> for the <var>op</var> operation, given <var>a</var> and <var>b</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑨">operator</a> for the <var>op</var> operation, given <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot⑨">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -3527,11 +3549,11 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
    </details>
    <details open>
     <summary> The element-wise binary operation algorithms invoke the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op"> create element-wise binary operation</a> steps as follows. </summary>
-    <div class="algorithm" data-algorithm="add(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-add"><code>add(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="add(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="add(a, b, options)|add(a, b)" id="dom-mlgraphbuilder-add"><code>add(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op①"> create element-wise binary operation</a> given "add", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op①"> create element-wise binary operation</a> given "add", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧③">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧④">throw</a> the error.</p>
@@ -3540,11 +3562,11 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="sub(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-sub"><code>sub(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="sub(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="sub(a, b, options)|sub(a, b)" id="dom-mlgraphbuilder-sub"><code>sub(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op②"> create element-wise binary operation</a> given "sub", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op②"> create element-wise binary operation</a> given "sub", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧⑤">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧⑥">throw</a> the error.</p>
@@ -3553,11 +3575,11 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="mul(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-mul"><code>mul(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="mul(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="mul(a, b, options)|mul(a, b)" id="dom-mlgraphbuilder-mul"><code>mul(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op③"> create element-wise binary operation</a> given "mul", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op③"> create element-wise binary operation</a> given "mul", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧⑦">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧⑧">throw</a> the error.</p>
@@ -3566,11 +3588,11 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="div(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-div"><code>div(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="div(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="div(a, b, options)|div(a, b)" id="dom-mlgraphbuilder-div"><code>div(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op④"> create element-wise binary operation</a> given "div", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op④"> create element-wise binary operation</a> given "div", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧⑨">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑨⓪">throw</a> the error.</p>
@@ -3579,11 +3601,11 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="max(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-max"><code>max(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="max(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="max(a, b, options)|max(a, b)" id="dom-mlgraphbuilder-max"><code>max(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op⑤"> create element-wise binary operation</a> given "max", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op⑤"> create element-wise binary operation</a> given "max", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑨①">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑨②">throw</a> the error.</p>
@@ -3592,11 +3614,11 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="min(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-min"><code>min(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="min(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="min(a, b, options)|min(a, b)" id="dom-mlgraphbuilder-min"><code>min(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op⑥"> create element-wise binary operation</a> given "min", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op⑥"> create element-wise binary operation</a> given "min", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑨③">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑨④">throw</a> the error.</p>
@@ -3605,11 +3627,11 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="pow(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-pow"><code>pow(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="pow(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="pow(a, b, options)|pow(a, b)" id="dom-mlgraphbuilder-pow"><code>pow(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op⑦"> create element-wise binary operation</a> given "pow", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-binary-op" id="ref-for-mlgraphbuilder-element-wise-binary-op⑦"> create element-wise binary operation</a> given "pow", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑨⑤">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑨⑥">throw</a> the error.</p>
@@ -3622,24 +3644,36 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
    <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical"><span class="secno">7.7.13. </span><span class="content">Element-wise logical operations</span><a class="self-link" href="#api-mlgraphbuilder-logical"></a></h4>
     Compare input tensors element-wise and return a <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8④">"uint8"</a></code> tensor of values 0 (false) or 1 (true) for the comparisons. For single-operand operations, return the logical results of the operation. 
    <p>For multiple-operand operations, the operation will be broadcast according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The input tensors must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable①">bidirectionally broadcastable</a>. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①④">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①⑤">rank</a> of the input tensors. For each dimension of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder②⑨"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-equal" id="ref-for-dom-mlgraphbuilder-equal"><c- g>equal</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greater" id="ref-for-dom-mlgraphbuilder-greater"><c- g>greater</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-a①"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-b①"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greaterorequal" id="ref-for-dom-mlgraphbuilder-greaterorequal"><c- g>greaterOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-a②"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-b②"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesser" id="ref-for-dom-mlgraphbuilder-lesser"><c- g>lesser</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-a③"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-b③"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesserorequal" id="ref-for-dom-mlgraphbuilder-lesserorequal"><c- g>lesserOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-a④"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-b④"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-logicalnot" id="ref-for-dom-mlgraphbuilder-logicalnot"><c- g>logicalNot</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-a⑤"><c- g>a</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⓪"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-equal" id="ref-for-dom-mlgraphbuilder-equal"><c- g>equal</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-a"><c- g>a</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-b"><c- g>b</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions①⑨"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greater" id="ref-for-dom-mlgraphbuilder-greater"><c- g>greater</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①②⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-a①"><c- g>a</c-></a>,
+                    <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-b①"><c- g>b</c-></a>,
+                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②⓪"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-options①"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greaterorequal" id="ref-for-dom-mlgraphbuilder-greaterorequal"><c- g>greaterOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-a②"><c- g>a</c-></a>,
+                           <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-b②"><c- g>b</c-></a>,
+                           <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②①"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-options②"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesser" id="ref-for-dom-mlgraphbuilder-lesser"><c- g>lesser</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-a③"><c- g>a</c-></a>,
+                   <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-b③"><c- g>b</c-></a>,
+                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②②"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-options③"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesserorequal" id="ref-for-dom-mlgraphbuilder-lesserorequal"><c- g>lesserOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-a④"><c- g>a</c-></a>,
+                          <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①③⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-b④"><c- g>b</c-></a>,
+                          <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②③"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-options④"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-logicalnot" id="ref-for-dom-mlgraphbuilder-logicalnot"><c- g>logicalNot</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-a⑤"><c- g>a</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②④"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options" id="ref-for-dom-mlgraphbuilder-equal-a-b-options-options⑤"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/equal(a, b), MLGraphBuilder/greater(a, b), MLGraphBuilder/greaterOrEqual(a, b), MLGraphBuilder/lesser(a, b), MLGraphBuilder/lesserOrEqual(a, b), MLGraphBuilder/logicalNot(a)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-equal-a-b-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④①">MLOperand</a></code>. The first input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/equal(a, b, options), MLGraphBuilder/greater(a, b, options), MLGraphBuilder/greaterOrEqual(a, b, options), MLGraphBuilder/lesser(a, b, options), MLGraphBuilder/lesserOrEqual(a, b, options), MLGraphBuilder/logicalNot(a, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-equal-a-b-options-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④②">MLOperand</a></code>. The first input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/equal(a, b), MLGraphBuilder/greater(a, b), MLGraphBuilder/greaterOrEqual(a, b), MLGraphBuilder/lesser(a, b), MLGraphBuilder/lesserOrEqual(a, b), MLGraphBuilder/logicalNot(a)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-equal-a-b-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④②">MLOperand</a></code>. The second input tensor when specified.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/equal(a, b, options), MLGraphBuilder/greater(a, b, options), MLGraphBuilder/greaterOrEqual(a, b, options), MLGraphBuilder/lesser(a, b, options), MLGraphBuilder/lesserOrEqual(a, b, options), MLGraphBuilder/logicalNot(a, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-equal-a-b-options-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④③">MLOperand</a></code>. The second input tensor when specified.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/equal(a, b, options), MLGraphBuilder/greater(a, b, options), MLGraphBuilder/greaterOrEqual(a, b, options), MLGraphBuilder/lesser(a, b, options), MLGraphBuilder/lesserOrEqual(a, b, options), MLGraphBuilder/logicalNot(a, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-equal-a-b-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②⑤">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④③">MLOperand</a></code>. The output tensor that contains the result of element-wise comparison of the two input tensors.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④④">MLOperand</a></code>. The output tensor that contains the result of element-wise comparison of the two input tensors.</p>
    </div>
    <div>
      <strong>Operation types:</strong> 
@@ -3660,7 +3694,7 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
    </div>
    <div class="note" role="note"> Although operations <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-greaterorequal" id="ref-for-dom-mlgraphbuilder-greaterorequal①">greaterOrEqual()</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-lesserorequal" id="ref-for-dom-mlgraphbuilder-lesserorequal①">lesserOrEqual()</a></code> can each be implemented in terms of operations <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-logicalnot" id="ref-for-dom-mlgraphbuilder-logicalnot①">logicalNot()</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-lesser" id="ref-for-dom-mlgraphbuilder-lesser①">lesser()</a></code>, and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-greater" id="ref-for-dom-mlgraphbuilder-greater①">greater()</a></code> in other words <code>builder.greaterOrEqual(a, b)</code> is <code>builder.logicalNot(builder.lesser(a, b))</code>, they are specifically defined to handle NaN cases and for performance reason to avoid double comparisons. </div>
    <details class="algorithm" data-algorithm="element-wise-logical-op" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="element-wise-logical-op" data-noexport id="mlgraphbuilder-element-wise-logical-op">create element-wise logical operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string④">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④④">MLOperand</a></code> <var>a</var> and an optional <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④⑤">MLOperand</a></code> <var>b</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="element-wise-logical-op" data-noexport id="mlgraphbuilder-element-wise-logical-op">create element-wise logical operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string④">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④⑤">MLOperand</a></code> <var>a</var>, an optional <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①④⑥">MLOperand</a></code> <var>b</var>, and <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②⑥">MLOperatorOptions</a></code> <var>options</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#assert" id="ref-for-assert③">Assert</a>: <var>op</var> is one of "equal", "greater", "greaterOrEqual", "lesser", "lesserOrEqual", "logicalNot".</p>
@@ -3694,7 +3728,7 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand⑨">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑤⑥">this</a> and <var>descriptor</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑥">operator</a> for the <var>op</var> operation, given <var>a</var> and (if <var>op</var> is not "logicalNot") <var>b</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⓪">operator</a> for the <var>op</var> operation, given <var>a</var> and (if <var>op</var> is not "logicalNot") <var>b</var>, and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot①⓪">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -3708,11 +3742,11 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
    </details>
    <details open>
     <summary> The element-wise logical operation algorithms invoke the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op"> create element-wise logical operation</a> steps as follows. </summary>
-    <div class="algorithm" data-algorithm="equal(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-equal"><code>equal(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="equal(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="equal(a, b, options)|equal(a, b)" id="dom-mlgraphbuilder-equal"><code>equal(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op①"> create element-wise logical operation</a> given "equal", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op①"> create element-wise logical operation</a> given "equal", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪③">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪④">throw</a> the error.</p>
@@ -3721,11 +3755,11 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="greater(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-greater"><code>greater(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="greater(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="greater(a, b, options)|greater(a, b)" id="dom-mlgraphbuilder-greater"><code>greater(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op②"> create element-wise logical operation</a> given "greater", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op②"> create element-wise logical operation</a> given "greater", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪⑤">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪⑥">throw</a> the error.</p>
@@ -3734,11 +3768,11 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="greaterOrEqual(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-greaterorequal"><code>greaterOrEqual(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="greaterOrEqual(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="greaterOrEqual(a, b, options)|greaterOrEqual(a, b)" id="dom-mlgraphbuilder-greaterorequal"><code>greaterOrEqual(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op③"> create element-wise logical operation</a> given "greaterOrEqual", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op③"> create element-wise logical operation</a> given "greaterOrEqual", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪⑦">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪⑧">throw</a> the error.</p>
@@ -3747,11 +3781,11 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="lesser(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-lesser"><code>lesser(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="lesser(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="lesser(a, b, options)|lesser(a, b)" id="dom-mlgraphbuilder-lesser"><code>lesser(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op④"> create element-wise logical operation</a> given "lesser", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op④"> create element-wise logical operation</a> given "lesser", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪⑨">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①①⓪">throw</a> the error.</p>
@@ -3760,11 +3794,11 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="lesserOrEqual(a, b)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-lesserorequal"><code>lesserOrEqual(<var>a</var>, <var>b</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="lesserOrEqual(a, b, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="lesserOrEqual(a, b, options)|lesserOrEqual(a, b)" id="dom-mlgraphbuilder-lesserorequal"><code>lesserOrEqual(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op⑤"> create element-wise logical operation</a> given "lesserOrEqual", <var>a</var> and <var>b</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op⑤"> create element-wise logical operation</a> given "lesserOrEqual", <var>a</var>, <var>b</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①①①">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①①②">throw</a> the error.</p>
@@ -3773,11 +3807,11 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="logicalNot(a)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-logicalnot"><code>logicalNot(<var>a</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="logicalNot(a, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="logicalNot(a, options)|logicalNot(a)" id="dom-mlgraphbuilder-logicalnot"><code>logicalNot(<var>a</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op⑥"> create element-wise logical operation</a> given "logicalNot" and <var>a</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-logical-op" id="ref-for-mlgraphbuilder-element-wise-logical-op⑥"> create element-wise logical operation</a> given "logicalNot", <var>a</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①①③">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①①④">throw</a> the error.</p>
@@ -3789,29 +3823,31 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
    </details>
    <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><span class="secno">7.7.14. </span><span class="content">Element-wise unary operations</span><a class="self-link" href="#api-mlgraphbuilder-unary"></a></h4>
     Compute the element-wise unary operation for input tensor. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⓪"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-abs" id="ref-for-dom-mlgraphbuilder-abs"><c- g>abs</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-ceil" id="ref-for-dom-mlgraphbuilder-ceil"><c- g>ceil</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input①"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cos" id="ref-for-dom-mlgraphbuilder-cos"><c- g>cos</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input②"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-erf" id="ref-for-dom-mlgraphbuilder-erf"><c- g>erf</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input③"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-exp" id="ref-for-dom-mlgraphbuilder-exp"><c- g>exp</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input④"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-floor" id="ref-for-dom-mlgraphbuilder-floor"><c- g>floor</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input⑤"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-identity" id="ref-for-dom-mlgraphbuilder-identity①"><c- g>identity</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input⑥"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-log" id="ref-for-dom-mlgraphbuilder-log"><c- g>log</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input⑦"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-neg" id="ref-for-dom-mlgraphbuilder-neg"><c- g>neg</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input⑧"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reciprocal" id="ref-for-dom-mlgraphbuilder-reciprocal"><c- g>reciprocal</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input⑨"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sin" id="ref-for-dom-mlgraphbuilder-sin"><c- g>sin</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input①⓪"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sqrt" id="ref-for-dom-mlgraphbuilder-sqrt"><c- g>sqrt</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input①①"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tan" id="ref-for-dom-mlgraphbuilder-tan"><c- g>tan</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input" id="ref-for-dom-mlgraphbuilder-abs-input-input①②"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③①"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-abs" id="ref-for-dom-mlgraphbuilder-abs"><c- g>abs</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②⑦"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①④⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-ceil" id="ref-for-dom-mlgraphbuilder-ceil"><c- g>ceil</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input①"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②⑧"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options①"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cos" id="ref-for-dom-mlgraphbuilder-cos"><c- g>cos</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input②"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions②⑨"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options②"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-erf" id="ref-for-dom-mlgraphbuilder-erf"><c- g>erf</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input③"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③⓪"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options③"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-exp" id="ref-for-dom-mlgraphbuilder-exp"><c- g>exp</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input④"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③①"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options④"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-floor" id="ref-for-dom-mlgraphbuilder-floor"><c- g>floor</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input⑤"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③②"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options⑤"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑤⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-identity" id="ref-for-dom-mlgraphbuilder-identity①"><c- g>identity</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input⑥"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③③"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options⑥"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-log" id="ref-for-dom-mlgraphbuilder-log"><c- g>log</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input⑦"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③④"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options⑦"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-neg" id="ref-for-dom-mlgraphbuilder-neg"><c- g>neg</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input⑧"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③⑤"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options⑧"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reciprocal" id="ref-for-dom-mlgraphbuilder-reciprocal"><c- g>reciprocal</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input⑨"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③⑥"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options⑨"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sin" id="ref-for-dom-mlgraphbuilder-sin"><c- g>sin</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input①⓪"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③⑦"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options①⓪"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑥⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sqrt" id="ref-for-dom-mlgraphbuilder-sqrt"><c- g>sqrt</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input①①"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③⑧"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options①①"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tan" id="ref-for-dom-mlgraphbuilder-tan"><c- g>tan</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input" id="ref-for-dom-mlgraphbuilder-abs-input-options-input①②"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions③⑨"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options" id="ref-for-dom-mlgraphbuilder-abs-input-options-options①②"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/abs(input), MLGraphBuilder/ceil(input), MLGraphBuilder/cos(input), MLGraphBuilder/erf(input), MLGraphBuilder/exp(input), MLGraphBuilder/floor(input), MLGraphBuilder/identity(input), MLGraphBuilder/log(input), MLGraphBuilder/neg(input), MLGraphBuilder/reciprocal(input), MLGraphBuilder/sin(input), MLGraphBuilder/sqrt(input), MLGraphBuilder/tan(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-abs-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦②">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/abs(input, options), MLGraphBuilder/ceil(input, options), MLGraphBuilder/cos(input, options), MLGraphBuilder/erf(input, options), MLGraphBuilder/exp(input, options), MLGraphBuilder/floor(input, options), MLGraphBuilder/identity(input, options), MLGraphBuilder/log(input, options), MLGraphBuilder/neg(input, options), MLGraphBuilder/reciprocal(input, options), MLGraphBuilder/sin(input, options), MLGraphBuilder/sqrt(input, options), MLGraphBuilder/tan(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-abs-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦③">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/abs(input, options), MLGraphBuilder/ceil(input, options), MLGraphBuilder/cos(input, options), MLGraphBuilder/erf(input, options), MLGraphBuilder/exp(input, options), MLGraphBuilder/floor(input, options), MLGraphBuilder/identity(input, options), MLGraphBuilder/log(input, options), MLGraphBuilder/neg(input, options), MLGraphBuilder/reciprocal(input, options), MLGraphBuilder/sin(input, options), MLGraphBuilder/sqrt(input, options), MLGraphBuilder/tan(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-abs-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④⓪">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦③">MLOperand</a></code>. The output tensor that contains the result of
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦④">MLOperand</a></code>. The output tensor that contains the result of
     element-wise unary operation of the input tensor. The shape of the output
     tensor is the same as the shape of input tensor.</p>
    </div>
@@ -3847,7 +3883,7 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
     </ul>
    </div>
    <details class="algorithm" data-algorithm="element-wise-unary-op" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="element-wise-unary-op" data-noexport id="mlgraphbuilder-element-wise-unary-op">create element-wise unary operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string⑤">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦④">MLOperand</a></code> <var>input</var>, and optional <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list①⑦">list</a> <var>allowedDataTypes</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="element-wise-unary-op" data-noexport id="mlgraphbuilder-element-wise-unary-op">create element-wise unary operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string⑤">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦⑤">MLOperand</a></code> <var>input</var>, optional <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list①⑦">list</a> <var>allowedDataTypes</var>, and <var>options</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#assert" id="ref-for-assert④">Assert</a>: <var>op</var> is one of "abs", "ceil", "cos", "erf", "exp", "floor", "identity", "log", "neg", "reciprocal", "sin", "sqrt", "tan".</p>
@@ -3863,7 +3899,7 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand②">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑦">operator</a> for the <var>op</var> operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②①">operator</a> for the <var>op</var> operation given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot①①">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -3877,11 +3913,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
    </details>
    <details open>
     <summary> The element-wise unary operation algorithms invoke the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op"> create element-wise unary operation</a> steps as follows. </summary>
-    <div class="algorithm" data-algorithm="abs(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-abs"><code>abs(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="abs(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="abs(input, options)|abs(input)" id="dom-mlgraphbuilder-abs"><code>abs(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①"> create element-wise unary operation</a> given "abs", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32⑦">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑤">"float16"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32②">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8④">"int8"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①"> create element-wise unary operation</a> given "abs", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32⑦">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑤">"float16"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32②">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8④">"int8"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①①⑧">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①①⑨">throw</a> the error.</p>
@@ -3890,11 +3926,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="ceil(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-ceil"><code>ceil(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="ceil(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="ceil(input, options)|ceil(input)" id="dom-mlgraphbuilder-ceil"><code>ceil(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op②"> create element-wise unary operation</a> given "ceil", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32⑧">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑥">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op②"> create element-wise unary operation</a> given "ceil", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32⑧">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑥">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②⓪">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②①">throw</a> the error.</p>
@@ -3903,11 +3939,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="cos(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-cos"><code>cos(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="cos(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="cos(input, options)|cos(input)" id="dom-mlgraphbuilder-cos"><code>cos(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op③"> create element-wise unary operation</a> given "cos", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32⑨">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑦">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op③"> create element-wise unary operation</a> given "cos", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32⑨">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑦">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②②">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②③">throw</a> the error.</p>
@@ -3916,11 +3952,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="erf(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-erf"><code>erf(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="erf(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="erf(input, options)|erf(input)" id="dom-mlgraphbuilder-erf"><code>erf(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op④"> create element-wise unary operation</a> given "erf", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⓪">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑧">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op④"> create element-wise unary operation</a> given "erf", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⓪">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑧">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②④">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②⑤">throw</a> the error.</p>
@@ -3929,11 +3965,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="exp(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-exp"><code>exp(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="exp(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="exp(input, options)|exp(input)" id="dom-mlgraphbuilder-exp"><code>exp(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑤"> create element-wise unary operation</a> given "exp", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①①">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑨">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑤"> create element-wise unary operation</a> given "exp", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①①">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16⑨">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②⑥">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②⑦">throw</a> the error.</p>
@@ -3942,11 +3978,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="floor(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-floor"><code>floor(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="floor(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="floor(input, options)|floor(input)" id="dom-mlgraphbuilder-floor"><code>floor(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑥"> create element-wise unary operation</a> given "floor", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①②">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⓪">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑥"> create element-wise unary operation</a> given "floor", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①②">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⓪">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②⑧">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①②⑨">throw</a> the error.</p>
@@ -3955,11 +3991,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="identity(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-identity"><code>identity(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="identity(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="identity(input, options)|identity(input)" id="dom-mlgraphbuilder-identity"><code>identity(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑦"> create element-wise unary operation</a> given "identity" and <var>input</var>.</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑦"> create element-wise unary operation</a> given "identity" <var>input</var>, and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③⓪">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③①">throw</a> the error.</p>
@@ -3968,11 +4004,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="log(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-log"><code>log(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="log(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="log(input, options)|log(input)" id="dom-mlgraphbuilder-log"><code>log(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑧"> create element-wise unary operation</a> given "log", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①③">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①①">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑧"> create element-wise unary operation</a> given "log", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①③">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①①">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③②">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③③">throw</a> the error.</p>
@@ -3981,11 +4017,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="neg(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-neg"><code>neg(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="neg(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="neg(input, options)|neg(input)" id="dom-mlgraphbuilder-neg"><code>neg(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑨"> create element-wise unary operation</a> given "neg", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①④">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①②">"float16"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32③">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8⑤">"int8"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op⑨"> create element-wise unary operation</a> given "neg", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①④">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①②">"float16"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32③">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8⑤">"int8"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③④">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③⑤">throw</a> the error.</p>
@@ -3994,11 +4030,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="reciprocal(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-reciprocal"><code>reciprocal(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="reciprocal(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="reciprocal(input, options)|reciprocal(input)" id="dom-mlgraphbuilder-reciprocal"><code>reciprocal(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①⓪"> create element-wise unary operation</a> given "reciprocal", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑤">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①③">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①⓪"> create element-wise unary operation</a> given "reciprocal", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑤">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①③">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③⑥">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③⑦">throw</a> the error.</p>
@@ -4007,11 +4043,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="sin(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-sin"><code>sin(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="sin(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="sin(input, options)|sin(input)" id="dom-mlgraphbuilder-sin"><code>sin(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①①"> create element-wise unary operation</a> given "sin", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑥">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①④">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①①"> create element-wise unary operation</a> given "sin", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑥">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①④">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③⑧">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①③⑨">throw</a> the error.</p>
@@ -4020,11 +4056,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="sqrt(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-sqrt"><code>sqrt(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="sqrt(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="sqrt(input, options)|sqrt(input)" id="dom-mlgraphbuilder-sqrt"><code>sqrt(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①②"> create element-wise unary operation</a> given "sqrt", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑦">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⑤">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①②"> create element-wise unary operation</a> given "sqrt", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑦">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⑤">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①④⓪">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①④①">throw</a> the error.</p>
@@ -4033,11 +4069,11 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
        <p>Return <var>output</var>.</p>
      </ol>
     </div>
-    <div class="algorithm" data-algorithm="tan(input)" data-algorithm-for="MLGraphBuilder">
-      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-tan"><code>tan(<var>input</var>)</code></dfn> method steps are: 
+    <div class="algorithm" data-algorithm="tan(input, options)" data-algorithm-for="MLGraphBuilder">
+      The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="tan(input, options)|tan(input)" id="dom-mlgraphbuilder-tan"><code>tan(<var>input</var>, <var>options</var>)</code></dfn> method steps are: 
      <ol>
       <li data-md>
-       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①③"> create element-wise unary operation</a> given "tan", <var>input</var>, and « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑧">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⑥">"float16"</a></code> ».</p>
+       <p>Let <var>output</var> be the result of running the <a data-link-type="dfn" href="#mlgraphbuilder-element-wise-unary-op" id="ref-for-mlgraphbuilder-element-wise-unary-op①③"> create element-wise unary operation</a> given "tan", <var>input</var>, « <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑧">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⑥">"float16"</a></code> », and <var>options</var>.</p>
        <ol>
         <li data-md>
          <p>If that <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①④②">throws</a> an error, then re-<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①④③">throw</a> the error.</p>
@@ -4049,12 +4085,12 @@ <h4 class="heading settled" data-level="7.7.14" id="api-mlgraphbuilder-unary"><s
    </details>
    <h4 class="heading settled" data-level="7.7.15" id="api-mlgraphbuilder-elu"><span class="secno">7.7.15. </span><span class="content">elu</span><a class="self-link" href="#api-mlgraphbuilder-elu"></a></h4>
     Calculate the <a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#ELU"> exponential linear unit function</a> (ELU) on the input tensor element-wise. The calculation follows the expression <code>max(0, x) + alpha * (exp(min(0, x)) - 1)</code>. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mleluoptions"><code><c- g>MLEluOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mleluoptions"><code><c- g>MLEluOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④①"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double③"><c- b>double</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="double" href="#dom-mleluoptions-alpha" id="ref-for-dom-mleluoptions-alpha"><c- g>alpha</c-></a> = 1;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③①"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-elu" id="ref-for-dom-mlgraphbuilder-elu"><c- g>elu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mleluoptions" id="ref-for-dictdef-mleluoptions"><c- n>MLEluOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-elu-input-options-options" id="ref-for-dom-mlgraphbuilder-elu-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③②"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-elu" id="ref-for-dom-mlgraphbuilder-elu"><c- g>elu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mleluoptions" id="ref-for-dictdef-mleluoptions"><c- n>MLEluOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-elu-input-options-options" id="ref-for-dom-mlgraphbuilder-elu-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mleluoptions" id="ref-for-dictdef-mleluoptions①">MLEluOptions</a></code> has the following members:</p>
@@ -4067,14 +4103,14 @@ <h4 class="heading settled" data-level="7.7.15" id="api-mlgraphbuilder-elu"><spa
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/elu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-elu-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦⑦">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/elu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-elu-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦⑧">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/elu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-elu-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mleluoptions" id="ref-for-dictdef-mleluoptions②">MLEluOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦⑧">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑦⑨">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
    <details class="algorithm" data-algorithm="elu(input, options)" data-algorithm-for="MLGraphBuilder" open>
@@ -4094,7 +4130,7 @@ <h4 class="heading settled" data-level="7.7.15" id="api-mlgraphbuilder-elu"><spa
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand③">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑧">operator</a> for the "elu" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②②">operator</a> for the "elu" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot①②">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -4123,22 +4159,26 @@ <h4 class="heading settled" data-level="7.7.15" id="api-mlgraphbuilder-elu"><spa
    </div>
    <h4 class="heading settled" data-level="7.7.16" id="api-mlgraphbuilder-expand"><span class="secno">7.7.16. </span><span class="content">expand</span><a class="self-link" href="#api-mlgraphbuilder-expand"></a></h4>
     Expand any dimension of size 1 of the input tensor to a larger size according to the new shape. The expansion is consistent with <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The input tensor must be <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable">unidirectionally broadcastable</a> to the new shape; its dimensions must have the size of 1 or match the sizes of the corresponding output dimensions according to the new shape. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③②"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑦⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-expand" id="ref-for-dom-mlgraphbuilder-expand"><c- g>expand</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-input" id="ref-for-dom-mlgraphbuilder-expand-input-newshape-input"><c- g>input</c-></a>, <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①③"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①⑤"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②③"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-newshape" id="ref-for-dom-mlgraphbuilder-expand-input-newshape-newshape"><c- g>newShape</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③③"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-expand" id="ref-for-dom-mlgraphbuilder-expand"><c- g>expand</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-options-input" id="ref-for-dom-mlgraphbuilder-expand-input-newshape-options-input"><c- g>input</c-></a>,
+                   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①③"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①⑤"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②③"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-options-newshape" id="ref-for-dom-mlgraphbuilder-expand-input-newshape-options-newshape"><c- g>newShape</c-></a>,
+                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④②"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-options-options" id="ref-for-dom-mlgraphbuilder-expand-input-newshape-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/expand(input, newShape)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-expand-input-newshape-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧①">MLOperand</a></code>. An input tensor</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/expand(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-expand-input-newshape-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧②">MLOperand</a></code>. An input tensor</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/expand(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-expand-input-newshape-options-newshape"><code>newShape</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①④">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②④">unsigned long</a></code>>. The new shape the input tensor is expanded to.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/expand(input, newShape)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-expand-input-newshape-newshape"><code>newShape</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①④">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②④">unsigned long</a></code>>. The new shape the input tensor is expanded to.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/expand(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-expand-input-newshape-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④③">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧②">MLOperand</a></code>. The tensor with expanded size dimensions.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧③">MLOperand</a></code>. The tensor with expanded size dimensions.</p>
    </div>
-   <details class="algorithm" data-algorithm="expand(input, newShape)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-expand"><code>expand(<var>input</var>, <var>newShape</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="expand(input, newShape, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="expand(input, newShape, options)|expand(input, newShape)" id="dom-mlgraphbuilder-expand"><code>expand(<var>input</var>, <var>newShape</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑥①">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot①⑦">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①④⑦">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror①⑤">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException②⑤">DOMException</a></code>.</p>
@@ -4158,7 +4198,7 @@ <h4 class="heading settled" data-level="7.7.16" id="api-mlgraphbuilder-expand"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand①⓪">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑥③">this</a> and <var>outputDescriptor</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators①⑨">operator</a> for the "expand" operation, given <var>input</var> and <var>newShape</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②③">operator</a> for the "expand" operation, given <var>input</var>, <var>newShape</var>, and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot①③">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -4172,13 +4212,13 @@ <h4 class="heading settled" data-level="7.7.16" id="api-mlgraphbuilder-expand"><
    </details>
    <h4 class="heading settled" data-level="7.7.17" id="api-mlgraphbuilder-gather"><span class="secno">7.7.17. </span><span class="content">gather</span><a class="self-link" href="#api-mlgraphbuilder-gather"></a></h4>
     Gather values of the input tensor along an axis according to the indices. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgatheroptions"><code><c- g>MLGatherOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgatheroptions"><code><c- g>MLGatherOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④④"><c- n>MLOperatorOptions</c-></a> {
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①⑥"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②⑤"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlgatheroptions-axis" id="ref-for-dom-mlgatheroptions-axis"><c- g>axis</c-></a> = 0;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③③"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gather" id="ref-for-dom-mlgraphbuilder-gather"><c- g>gather</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input"><c- g>input</c-></a>,
-                   <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices"><c- g>indices</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③④"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gather" id="ref-for-dom-mlgraphbuilder-gather"><c- g>gather</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input"><c- g>input</c-></a>,
+                   <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices"><c- g>indices</c-></a>,
                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlgatheroptions" id="ref-for-dictdef-mlgatheroptions"><c- n>MLGatherOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gather-input-indices-options-options" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
@@ -4192,13 +4232,13 @@ <h4 class="heading settled" data-level="7.7.17" id="api-mlgraphbuilder-gather"><
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑥">MLOperand</a></code>. The input N-D tensor from which the values are gathered.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑦">MLOperand</a></code>. The input N-D tensor from which the values are gathered.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-indices"><code>indices</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑦">MLOperand</a></code>. The indices N-D tensor of the input values to gather. The values must be of type <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32④">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32③">"uint32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64③">"int64"</a></code>, and must be in the range -N (inclusive) to N (exclusive) where N is the size of the input dimension indexed by <em>options.axis</em>, and a negative index means indexing from the end of the dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-indices"><code>indices</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑧">MLOperand</a></code>. The indices N-D tensor of the input values to gather. The values must be of type <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32④">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32③">"uint32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64③">"int64"</a></code>, and must be in the range -N (inclusive) to N (exclusive) where N is the size of the input dimension indexed by <em>options.axis</em>, and a negative index means indexing from the end of the dimension.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlgatheroptions" id="ref-for-dictdef-mlgatheroptions②">MLGatherOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑧">MLOperand</a></code>. The output N-D tensor of <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①⑦">rank</a> equal to the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①⑧">rank</a> of <em>input</em> + the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①⑨">rank</a> of <em>indices</em> - 1.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑨">MLOperand</a></code>. The output N-D tensor of <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①⑦">rank</a> equal to the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①⑧">rank</a> of <em>input</em> + the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank①⑨">rank</a> of <em>indices</em> - 1.</p>
    </div>
    <div class="note" role="note"> The <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices①">indices</a></code> parameter to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather" id="ref-for-dom-mlgraphbuilder-gather①">gather()</a></code> can not be clamped to the allowed range when the graph is built because the inputs are not known until execution. Implementations can introduce <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp②">clamp()</a></code> in the compiled graph if the required clamping behavior is not provided by the underlying platform. Similarly, if the underlying platform does not support negative indices, the implementation can introduce operations in the compiled graph to transform a negative index from the end of the dimension into a positive index. </div>
    <details class="algorithm" data-algorithm="gather(input, indices, options)" data-algorithm-for="MLGraphBuilder" open>
@@ -4268,7 +4308,7 @@ <h4 class="heading settled" data-level="7.7.17" id="api-mlgraphbuilder-gather"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand①①">creating an MLOperand</a> given <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⓪">operator</a> for the "gather" operation, given <var>input</var>, <var>indices</var>, and <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②④">operator</a> for the "gather" operation, given <var>input</var>, <var>indices</var>, and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot①④">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -4335,24 +4375,26 @@ <h4 class="heading settled" data-level="7.7.17" id="api-mlgraphbuilder-gather"><
    </div>
    <h4 class="heading settled" data-level="7.7.18" id="api-mlgraphbuilder-gelu-method"><span class="secno">7.7.18. </span><span class="content">gelu</span><a class="self-link" href="#api-mlgraphbuilder-gelu-method"></a></h4>
     Compute the <a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Gaussian-error_linear_unit_(GELU)">gaussian error linear unit function</a> (GELU) of the input tensor. The calculation follows the expression <code>0.5 * x * (1 + erf(x / sqrt(2)))</code>. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③④"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑧⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gelu" id="ref-for-dom-mlgraphbuilder-gelu"><c- g>gelu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gelu-input-input" id="ref-for-dom-mlgraphbuilder-gelu-input-input"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑤"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gelu" id="ref-for-dom-mlgraphbuilder-gelu"><c- g>gelu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④⑤"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gelu-input-options-options" id="ref-for-dom-mlgraphbuilder-gelu-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gelu(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gelu-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨①">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gelu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gelu-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨②">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gelu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gelu-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④⑥">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨②">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨③">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="gelu(input)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-gelu"><code>gelu(<var>input</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="gelu(input, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="gelu(input, options)|gelu(input)" id="dom-mlgraphbuilder-gelu"><code>gelu(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑥⑥">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot①⑨">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑤④">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror①⑦">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException②⑦">DOMException</a></code>.</p>
@@ -4366,7 +4408,7 @@ <h4 class="heading settled" data-level="7.7.18" id="api-mlgraphbuilder-gelu-meth
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand④">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②①">operator</a> for the "gelu" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑤">operator</a> for the "gelu" operation given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot①⑤">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -4394,21 +4436,21 @@ <h4 class="heading settled" data-level="7.7.18" id="api-mlgraphbuilder-gelu-meth
    </div>
    <h4 class="heading settled" data-level="7.7.19" id="api-mlgraphbuilder-gemm"><span class="secno">7.7.19. </span><span class="content">gemm</span><a class="self-link" href="#api-mlgraphbuilder-gemm"></a></h4>
     Calculate the <a href="https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms#Level_3">general matrix multiplication of the Basic Linear Algebra Subprograms</a>. The calculation follows the expression <code>alpha * A * B + beta * C</code>, where <code>A</code> is a 2-D tensor with shape <em>[M, K]</em> or <em>[K, M]</em>, <code>B</code> is a 2-D tensor with shape <em>[K, N]</em> or <em>[N, K]</em>, and <code>C</code> is <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable①">unidirectionally broadcastable</a> to the shape <em>[M, N]</em>. <code>A</code> and <code>B</code> may optionally be transposed prior to the calculation. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgemmoptions"><code><c- g>MLGemmOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c"><c- g>c</c-></a>;
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgemmoptions"><code><c- g>MLGemmOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④⑦"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c"><c- g>c</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double⑤"><c- b>double</c-></a> <a class="idl-code" data-default="1.0" data-link-type="dict-member" data-type="double" href="#dom-mlgemmoptions-alpha" id="ref-for-dom-mlgemmoptions-alpha"><c- g>alpha</c-></a> = 1.0;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double⑥"><c- b>double</c-></a> <a class="idl-code" data-default="1.0" data-link-type="dict-member" data-type="double" href="#dom-mlgemmoptions-beta" id="ref-for-dom-mlgemmoptions-beta"><c- g>beta</c-></a> = 1.0;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean③"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlgemmoptions-atranspose" id="ref-for-dom-mlgemmoptions-atranspose"><c- g>aTranspose</c-></a> = <c- b>false</c->;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean④"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlgemmoptions-btranspose" id="ref-for-dom-mlgemmoptions-btranspose"><c- g>bTranspose</c-></a> = <c- b>false</c->;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑤"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gemm" id="ref-for-dom-mlgraphbuilder-gemm①"><c- g>gemm</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gemm-a-b-options-a" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gemm-a-b-options-b" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlgemmoptions" id="ref-for-dictdef-mlgemmoptions"><c- n>MLGemmOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gemm-a-b-options-options" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑥"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gemm" id="ref-for-dom-mlgraphbuilder-gemm①"><c- g>gemm</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gemm-a-b-options-a" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gemm-a-b-options-b" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlgemmoptions" id="ref-for-dictdef-mlgemmoptions"><c- n>MLGemmOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gemm-a-b-options-options" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlgemmoptions" id="ref-for-dictdef-mlgemmoptions①">MLGemmOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGemmOptions" data-dfn-type="dict-member" data-export id="dom-mlgemmoptions-c"><code>c</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑦">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGemmOptions" data-dfn-type="dict-member" data-export id="dom-mlgemmoptions-c"><code>c</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑧">MLOperand</a></span>
     <dd data-md>
      <p>The third input tensor. It is either a scalar, or of the shape that is <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable②">unidirectionally broadcastable</a> to the shape <em>[M, N]</em>. When it is not specified, the computation is done as if <em>c</em> is a scalar 0.0.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGemmOptions" data-dfn-type="dict-member" data-export id="dom-mlgemmoptions-alpha"><code>alpha</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double⑦">double</a>, defaulting to <code>1.0</code></span>
@@ -4428,13 +4470,13 @@ <h4 class="heading settled" data-level="7.7.19" id="api-mlgraphbuilder-gemm"><sp
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨⑧">MLOperand</a></code>. The first input 2-D tensor with shape <em>[M, K]</em> if <em>aTranspose</em> is false, or <em>[K, M]</em> if <em>aTranspose</em> is true.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨⑨">MLOperand</a></code>. The first input 2-D tensor with shape <em>[M, K]</em> if <em>aTranspose</em> is false, or <em>[K, M]</em> if <em>aTranspose</em> is true.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨⑨">MLOperand</a></code>. The second input 2-D tensor with shape <em>[K, N]</em> if <em>bTranspose</em> is false, or <em>[N, K]</em> if <em>bTranspose</em> is true.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⓪⓪">MLOperand</a></code>. The second input 2-D tensor with shape <em>[K, N]</em> if <em>bTranspose</em> is false, or <em>[N, K]</em> if <em>bTranspose</em> is true.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlgemmoptions" id="ref-for-dictdef-mlgemmoptions②">MLGemmOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⓪⓪">MLOperand</a></code>. The output 2-D tensor of shape <em>[M, N]</em> that contains the calculated product of all the inputs.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⓪①">MLOperand</a></code>. The output 2-D tensor of shape <em>[M, N]</em> that contains the calculated product of all the inputs.</p>
    </div>
    <details class="algorithm" data-algorithm="gemm(a, b, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="gemm(a, b, options)|gemm(a, b)" id="dom-mlgraphbuilder-gemm"><code>gemm(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -4479,7 +4521,7 @@ <h4 class="heading settled" data-level="7.7.19" id="api-mlgraphbuilder-gemm"><sp
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand①②">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑦⓪">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②②">operator</a> for the "gemm" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑥">operator</a> for the "gemm" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot①⑥">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -4534,10 +4576,10 @@ <h4 class="heading settled" data-level="7.7.20" id="api-mlgraphbuilder-gru"><spa
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLRecurrentNetworkDirection" data-dfn-type="enum-value" data-export id="dom-mlrecurrentnetworkdirection-both"><code><c- s>"both"</c-></code></dfn>
 };
 
-<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgruoptions"><code><c- g>MLGruOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-bias" id="ref-for-dom-mlgruoptions-bias"><c- g>bias</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-recurrentbias" id="ref-for-dom-mlgruoptions-recurrentbias"><c- g>recurrentBias</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-initialhiddenstate" id="ref-for-dom-mlgruoptions-initialhiddenstate"><c- g>initialHiddenState</c-></a>;
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgruoptions"><code><c- g>MLGruOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④⑧"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-bias" id="ref-for-dom-mlgruoptions-bias"><c- g>bias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-recurrentbias" id="ref-for-dom-mlgruoptions-recurrentbias"><c- g>recurrentBias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-initialhiddenstate" id="ref-for-dom-mlgruoptions-initialhiddenstate"><c- g>initialHiddenState</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean⑦"><c- b>boolean</c-></a> <a class="idl-code" data-default="true" data-link-type="dict-member" data-type="boolean" href="#dom-mlgruoptions-resetafter" id="ref-for-dom-mlgruoptions-resetafter"><c- g>resetAfter</c-></a> = <c- b>true</c->;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean⑧"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlgruoptions-returnsequence" id="ref-for-dom-mlgruoptions-returnsequence"><c- g>returnSequence</c-></a> = <c- b>false</c->;
   <a data-link-type="idl-name" href="#enumdef-mlrecurrentnetworkdirection" id="ref-for-enumdef-mlrecurrentnetworkdirection"><c- n>MLRecurrentNetworkDirection</c-></a> <a class="idl-code" data-default="&quot;forward&quot;" data-link-type="dict-member" data-type="MLRecurrentNetworkDirection" href="#dom-mlgruoptions-direction" id="ref-for-dom-mlgruoptions-direction"><c- g>direction</c-></a> = "forward";
@@ -4545,10 +4587,10 @@ <h4 class="heading settled" data-level="7.7.20" id="api-mlgraphbuilder-gru"><spa
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑤"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#enumdef-mlrecurrentnetworkactivation" id="ref-for-enumdef-mlrecurrentnetworkactivation"><c- n>MLRecurrentNetworkActivation</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<MLRecurrentNetworkActivation>" href="#dom-mlgruoptions-activations" id="ref-for-dom-mlgruoptions-activations"><c- g>activations</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑥"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑥"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪④"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gru" id="ref-for-dom-mlgraphbuilder-gru"><c- g>gru</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-input"><c- g>input</c-></a>,
-                          <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight"><c- g>weight</c-></a>,
-                          <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑦"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑥"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑤"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gru" id="ref-for-dom-mlgraphbuilder-gru"><c- g>gru</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-input"><c- g>input</c-></a>,
+                          <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight"><c- g>weight</c-></a>,
+                          <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
                           [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①⑦"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②⑦"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-steps" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-steps"><c- g>steps</c-></a>,
                           [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①⑧"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②⑧"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-hiddensize" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-hiddensize"><c- g>hiddenSize</c-></a>,
                           <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlgruoptions" id="ref-for-dictdef-mlgruoptions"><c- n>MLGruOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-options" id="ref-for-dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-options"><c- g>options</c-></a> = {});
@@ -4556,13 +4598,13 @@ <h4 class="heading settled" data-level="7.7.20" id="api-mlgraphbuilder-gru"><spa
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlgruoptions" id="ref-for-dictdef-mlgruoptions①">MLGruOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑧">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑨">MLOperand</a></span>
     <dd data-md>
      <p>The 2-D input bias tensor of shape <em>[numDirections, 3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout①">layout</a></code> argument.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⓪⑨">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⓪">MLOperand</a></span>
     <dd data-md>
      <p>The 2-D recurrent bias tensor of shape <em>[numDirections, 3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout②">layout</a></code> argument.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-initialhiddenstate"><code>initialHiddenState</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⓪">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-initialhiddenstate"><code>initialHiddenState</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①①">MLOperand</a></span>
     <dd data-md>
      <p>The 3-D initial hidden state tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>.
 When not specified, implementations SHOULD use a tensor filled with zero.</p>
@@ -4586,11 +4628,11 @@ <h4 class="heading settled" data-level="7.7.20" id="api-mlgraphbuilder-gru"><spa
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①①">MLOperand</a></code>. The input 3-D tensor of shape <em>[steps, batchSize, inputSize]</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①②">MLOperand</a></code>. The input 3-D tensor of shape <em>[steps, batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①②">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout③">layout</a></code> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①③">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout③">layout</a></code> argument.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①③">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout④">layout</a></code> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①④">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout④">layout</a></code> argument.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-steps"><code>steps</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②⑨">unsigned long</a></code> scalar. The number of time steps in the recurrent network. The value must be greater than 0.</p>
      <li data-md>
@@ -4598,7 +4640,7 @@ <h4 class="heading settled" data-level="7.7.20" id="api-mlgraphbuilder-gru"><spa
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlgruoptions" id="ref-for-dictdef-mlgruoptions②">MLGruOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑦">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①④">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the cell output from the last time step of the network. Additionally, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-returnsequence" id="ref-for-dom-mlgruoptions-returnsequence①">returnSequence</a></code> is set to true, the second element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every cell outputs from each time step in the temporal sequence.</p>
+    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑦">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①⑤">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the cell output from the last time step of the network. Additionally, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-returnsequence" id="ref-for-dom-mlgruoptions-returnsequence①">returnSequence</a></code> is set to true, the second element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every cell outputs from each time step in the temporal sequence.</p>
    </div>
    <details class="algorithm" data-algorithm="gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="gru(input, weight, recurrentWeight, steps, hiddenSize, options)|gru(input, weight, recurrentWeight, steps, hiddenSize)" id="dom-mlgraphbuilder-gru"><code>gru(<var>input</var>, <var>weight</var>, <var>recurrentWeight</var>, <var>steps</var>, <var>hiddenSize</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -4685,7 +4727,7 @@ <h4 class="heading settled" data-level="7.7.20" id="api-mlgraphbuilder-gru"><spa
       <p><em>Make graph connections:</em></p>
       <ol>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②③">operator</a> for the "gru" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>steps</var>, <var>hiddenSize</var> and <var>options</var> as parameters.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑦">operator</a> for the "gru" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>steps</var>, <var>hiddenSize</var> and <var>options</var>.</p>
        <li data-md>
         <p>Let <var>output0</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand①③">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑦③">this</a> and <var>desc0</var>.</p>
        <li data-md>
@@ -4826,29 +4868,29 @@ <h4 class="heading settled" data-level="7.7.20" id="api-mlgraphbuilder-gru"><spa
    </div>
    <h4 class="heading settled" data-level="7.7.21" id="api-mlgraphbuilder-grucell"><span class="secno">7.7.21. </span><span class="content">gruCell</span><a class="self-link" href="#api-mlgraphbuilder-grucell"></a></h4>
     A single time step of the Gated Recurrent Unit <a data-link-type="biblio" href="#biblio-gru" title="Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation">[GRU]</a> recurrent network using an update gate and a reset gate to compute the hidden state that rolls into the output across the temporal sequence of a recurrent network. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgrucelloptions"><code><c- g>MLGruCellOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgrucelloptions-bias" id="ref-for-dom-mlgrucelloptions-bias"><c- g>bias</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgrucelloptions-recurrentbias" id="ref-for-dom-mlgrucelloptions-recurrentbias"><c- g>recurrentBias</c-></a>;
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlgrucelloptions"><code><c- g>MLGruCellOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④⑨"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgrucelloptions-bias" id="ref-for-dom-mlgrucelloptions-bias"><c- g>bias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgrucelloptions-recurrentbias" id="ref-for-dom-mlgrucelloptions-recurrentbias"><c- g>recurrentBias</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①①"><c- b>boolean</c-></a> <a class="idl-code" data-default="true" data-link-type="dict-member" data-type="boolean" href="#dom-mlgrucelloptions-resetafter" id="ref-for-dom-mlgrucelloptions-resetafter"><c- g>resetAfter</c-></a> = <c- b>true</c->;
   <a data-link-type="idl-name" href="#enumdef-mlgruweightlayout" id="ref-for-enumdef-mlgruweightlayout②"><c- n>MLGruWeightLayout</c-></a> <a class="idl-code" data-default="&quot;zrn&quot;" data-link-type="dict-member" data-type="MLGruWeightLayout" href="#dom-mlgrucelloptions-layout" id="ref-for-dom-mlgrucelloptions-layout"><c- g>layout</c-></a> = "zrn";
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑧"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#enumdef-mlrecurrentnetworkactivation" id="ref-for-enumdef-mlrecurrentnetworkactivation②"><c- n>MLRecurrentNetworkActivation</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<MLRecurrentNetworkActivation>" href="#dom-mlgrucelloptions-activations" id="ref-for-dom-mlgrucelloptions-activations"><c- g>activations</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑦"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-grucell" id="ref-for-dom-mlgraphbuilder-grucell"><c- g>gruCell</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-input"><c- g>input</c-></a>,
-                    <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight"><c- g>weight</c-></a>,
-                    <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
-                    <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddenstate" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddenstate"><c- g>hiddenState</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑧"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-grucell" id="ref-for-dom-mlgraphbuilder-grucell"><c- g>gruCell</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-input"><c- g>input</c-></a>,
+                    <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight"><c- g>weight</c-></a>,
+                    <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
+                    <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddenstate" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddenstate"><c- g>hiddenState</c-></a>,
                     [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange①⑨"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③①"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddensize" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddensize"><c- g>hiddenSize</c-></a>,
                     <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlgrucelloptions" id="ref-for-dictdef-mlgrucelloptions"><c- n>MLGruCellOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-options" id="ref-for-dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlgrucelloptions" id="ref-for-dictdef-mlgrucelloptions①">MLGruCellOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②②">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②③">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D input bias tensor of shape <em>[3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout⑤">layout</a></code> argument.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②③">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②④">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D recurrent bias tensor of shape <em>[3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout⑥">layout</a></code> argument.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-resetafter"><code>resetAfter</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①②">boolean</a>, defaulting to <code>true</code></span>
@@ -4865,19 +4907,19 @@ <h4 class="heading settled" data-level="7.7.21" id="api-mlgraphbuilder-grucell">
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②④">MLOperand</a></code>. The input 2-D tensor of shape <em>[batchSize, inputSize]</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑤">MLOperand</a></code>. The input 2-D tensor of shape <em>[batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑤">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑥">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑥">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑦">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddenstate"><code>hiddenState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑦">MLOperand</a></code>. The 2-D input hidden state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddenstate"><code>hiddenState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑧">MLOperand</a></code>. The 2-D input hidden state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddensize"><code>hiddenSize</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③②">unsigned long</a></code> scalar. The value of the second dimension of the output tensor shape. It indicates the number of features in the hidden state.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlgrucelloptions" id="ref-for-dictdef-mlgrucelloptions②">MLGruCellOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑧">MLOperand</a></code>. The 2-D tensor of shape <em>[batchSize, hiddenSize]</em>, the cell output hidden state of a single time step of the recurrent network.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑨">MLOperand</a></code>. The 2-D tensor of shape <em>[batchSize, hiddenSize]</em>, the cell output hidden state of a single time step of the recurrent network.</p>
    </div>
    <details class="algorithm" data-algorithm="gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)|gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize)" id="dom-mlgraphbuilder-grucell"><code>gruCell(<var>input</var>, <var>weight</var>, <var>recurrentWeight</var>, <var>hiddenState</var>, <var>hiddenSize</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -4946,7 +4988,7 @@ <h4 class="heading settled" data-level="7.7.21" id="api-mlgraphbuilder-grucell">
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand①⑤">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑦⑦">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②④">operator</a> for the "gruCell" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>hiddenState</var>, <var>hiddenSize</var> and <var>options</var> as parameters.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑧">operator</a> for the "gruCell" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>hiddenState</var>, <var>hiddenSize</var> and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot②⓪">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -5066,13 +5108,13 @@ <h4 class="heading settled" data-level="7.7.21" id="api-mlgraphbuilder-grucell">
    </div>
    <h4 class="heading settled" data-level="7.7.22" id="api-mlgraphbuilder-hard-sigmoid"><span class="secno">7.7.22. </span><span class="content">hardSigmoid</span><a class="self-link" href="#api-mlgraphbuilder-hard-sigmoid"></a></h4>
     Calculate the non-smooth <a href="https://en.wikipedia.org/wiki/Hard_sigmoid">hard sigmoid function</a> on the input tensor, used instead of the sigmoid function for faster computation. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlhardsigmoidoptions"><code><c- g>MLHardSigmoidOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlhardsigmoidoptions"><code><c- g>MLHardSigmoidOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤⓪"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double⑨"><c- b>double</c-></a> <a class="idl-code" data-default="0.2" data-link-type="dict-member" data-type="double" href="#dom-mlhardsigmoidoptions-alpha" id="ref-for-dom-mlhardsigmoidoptions-alpha"><c- g>alpha</c-></a> = 0.2;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①⓪"><c- b>double</c-></a> <a class="idl-code" data-default="0.5" data-link-type="dict-member" data-type="double" href="#dom-mlhardsigmoidoptions-beta" id="ref-for-dom-mlhardsigmoidoptions-beta"><c- g>beta</c-></a> = 0.5;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑧"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-hardsigmoid" id="ref-for-dom-mlgraphbuilder-hardsigmoid"><c- g>hardSigmoid</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlhardsigmoidoptions" id="ref-for-dictdef-mlhardsigmoidoptions"><c- n>MLHardSigmoidOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardsigmoid-input-options-options" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑨"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-hardsigmoid" id="ref-for-dom-mlgraphbuilder-hardsigmoid"><c- g>hardSigmoid</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlhardsigmoidoptions" id="ref-for-dictdef-mlhardsigmoidoptions"><c- n>MLHardSigmoidOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardsigmoid-input-options-options" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlhardsigmoidoptions" id="ref-for-dictdef-mlhardsigmoidoptions①">MLHardSigmoidOptions</a></code> has the following members:</p>
@@ -5088,14 +5130,14 @@ <h4 class="heading settled" data-level="7.7.22" id="api-mlgraphbuilder-hard-sigm
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/hardSigmoid(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-hardsigmoid-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③①">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/hardSigmoid(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-hardsigmoid-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③②">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/hardSigmoid(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-hardsigmoid-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlhardsigmoidoptions" id="ref-for-dictdef-mlhardsigmoidoptions②">MLHardSigmoidOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③②">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③③">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
    <details class="algorithm" data-algorithm="hardSigmoid(input, options)" data-algorithm-for="MLGraphBuilder" open>
@@ -5117,7 +5159,7 @@ <h4 class="heading settled" data-level="7.7.22" id="api-mlgraphbuilder-hard-sigm
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand⑤">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑤">operator</a> for the "hardSigmoid" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑨">operator</a> for the "hardSigmoid" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot②①">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -5146,24 +5188,26 @@ <h4 class="heading settled" data-level="7.7.22" id="api-mlgraphbuilder-hard-sigm
    </div>
    <h4 class="heading settled" data-level="7.7.23" id="api-mlgraphbuilder-hard-swish"><span class="secno">7.7.23. </span><span class="content">hardSwish</span><a class="self-link" href="#api-mlgraphbuilder-hard-swish"></a></h4>
     Computes the nonlinear function <code>y = x * max(0, min(6, (x + 3))) / 6</code> that is introduced by <a data-link-type="biblio" href="#biblio-mobilenetv3" title="Searching for MobileNetV3">[MobileNetV3]</a> on the input tensor element-wise. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder③⑨"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-hardswish" id="ref-for-dom-mlgraphbuilder-hardswish"><c- g>hardSwish</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardswish-input-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-input"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⓪"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-hardswish" id="ref-for-dom-mlgraphbuilder-hardswish"><c- g>hardSwish</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤①"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardswish-input-options-options" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/hardSwish(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-hardswish-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③⑤">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/hardSwish(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-hardswish-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③⑥">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/hardSwish(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-hardswish-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤②">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③⑥">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③⑦">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="hardSwish(input)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-hardswish"><code>hardSwish(<var>input</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="hardSwish(input, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="hardSwish(input, options)|hardSwish(input)" id="dom-mlgraphbuilder-hardswish"><code>hardSwish(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑧⓪">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot②④">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑨⑧">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror②②">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException③②">DOMException</a></code>.</p>
@@ -5177,7 +5221,7 @@ <h4 class="heading settled" data-level="7.7.23" id="api-mlgraphbuilder-hard-swis
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand⑥">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑥">operator</a> for the "hardSwish" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⓪">operator</a> for the "hardSwish" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot②②">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -5208,24 +5252,24 @@ <h4 class="heading settled" data-level="7.7.23" id="api-mlgraphbuilder-hard-swis
    </div>
    <h4 class="heading settled" data-level="7.7.24" id="api-mlgraphbuilder-instancenorm"><span class="secno">7.7.24. </span><span class="content">instanceNormalization</span><a class="self-link" href="#api-mlgraphbuilder-instancenorm"></a></h4>
     Normalize the input using <a data-link-type="biblio" href="#biblio-instance-normalization" title="Instance Normalization: The Missing Ingredient for Fast Stylization">[Instance-Normalization]</a>. Unlike <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization" id="ref-for-dom-mlgraphbuilder-batchnormalization①">batchNormalization()</a></code> where the mean and variance values used in the normalization are computed across all the samples in the batch dimension while the model is trained, the mean and variance values used in the instance normalization are computed on the fly for each input feature of each individual sample in the batch. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlinstancenormalizationoptions"><code><c- g>MLInstanceNormalizationOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlinstancenormalizationoptions-scale" id="ref-for-dom-mlinstancenormalizationoptions-scale"><c- g>scale</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlinstancenormalizationoptions-bias" id="ref-for-dom-mlinstancenormalizationoptions-bias"><c- g>bias</c-></a>;
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlinstancenormalizationoptions"><code><c- g>MLInstanceNormalizationOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤③"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlinstancenormalizationoptions-scale" id="ref-for-dom-mlinstancenormalizationoptions-scale"><c- g>scale</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlinstancenormalizationoptions-bias" id="ref-for-dom-mlinstancenormalizationoptions-bias"><c- g>bias</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①③"><c- b>double</c-></a> <a class="idl-code" data-default="1e-5" data-link-type="dict-member" data-type="double" href="#dom-mlinstancenormalizationoptions-epsilon" id="ref-for-dom-mlinstancenormalizationoptions-epsilon"><c- g>epsilon</c-></a> = 1e-5;
   <a data-link-type="idl-name" href="#enumdef-mlinputoperandlayout" id="ref-for-enumdef-mlinputoperandlayout④"><c- n>MLInputOperandLayout</c-></a> <a class="idl-code" data-default="&quot;nchw&quot;" data-link-type="dict-member" data-type="MLInputOperandLayout" href="#dom-mlinstancenormalizationoptions-layout" id="ref-for-dom-mlinstancenormalizationoptions-layout"><c- g>layout</c-></a> = "nchw";
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⓪"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②③⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-instancenormalization" id="ref-for-dom-mlgraphbuilder-instancenormalization"><c- g>instanceNormalization</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input"><c- g>input</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④①"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-instancenormalization" id="ref-for-dom-mlgraphbuilder-instancenormalization"><c- g>instanceNormalization</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input"><c- g>input</c-></a>,
                                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlinstancenormalizationoptions" id="ref-for-dictdef-mlinstancenormalizationoptions"><c- n>MLInstanceNormalizationOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-instancenormalization-input-options-options" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlinstancenormalizationoptions" id="ref-for-dictdef-mlinstancenormalizationoptions①">MLInstanceNormalizationOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④①">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④②">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D tensor of the scaling values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size①⑧">size</a> is equal to the number of channels, i.e. the size of the feature dimension of the input. For example, for an <var>input</var> tensor with <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw⑨">"nchw"</a></code> layout, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size①⑨">size</a> is equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape④⑧">shape</a>[1].</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④②">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④③">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D tensor of the bias values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②⓪">size</a> is equal to the size of the feature dimension of the input. For example, for an <var>input</var> tensor with <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw①⓪">"nchw"</a></code> layout, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②①">size</a> is equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape④⑨">shape</a>[1].</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-epsilon"><code>epsilon</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①④">double</a>, defaulting to <code>1e-5</code></span>
@@ -5239,11 +5283,11 @@ <h4 class="heading settled" data-level="7.7.24" id="api-mlgraphbuilder-instancen
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/instanceNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-instancenormalization-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②④③">MLOperand</a></code>. The input 4-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/instanceNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-instancenormalization-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②④④">MLOperand</a></code>. The input 4-D tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/instanceNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-instancenormalization-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlinstancenormalizationoptions" id="ref-for-dictdef-mlinstancenormalizationoptions②">MLInstanceNormalizationOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②④④">MLOperand</a></code>. The instance-normalized 4-D tensor of the same shape as <em>input</em>.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②④⑤">MLOperand</a></code>. The instance-normalized 4-D tensor of the same shape as <em>input</em>.</p>
    </div>
    <details class="algorithm" data-algorithm="instanceNormalization(input, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="instanceNormalization(input, options)|instanceNormalization(input)" id="dom-mlgraphbuilder-instancenormalization"><code>instanceNormalization(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -5282,7 +5326,7 @@ <h4 class="heading settled" data-level="7.7.24" id="api-mlgraphbuilder-instancen
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand⑦">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑦">operator</a> for the "instanceNormalization" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③①">operator</a> for the "instanceNormalization" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot②③">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -5327,24 +5371,24 @@ <h4 class="heading settled" data-level="7.7.24" id="api-mlgraphbuilder-instancen
    </div>
    <h4 class="heading settled" data-level="7.7.25" id="api-mlgraphbuilder-layernorm"><span class="secno">7.7.25. </span><span class="content">layerNormalization</span><a class="self-link" href="#api-mlgraphbuilder-layernorm"></a></h4>
     Normalize the input using <a data-link-type="biblio" href="#biblio-layer-normalization" title="Layer Normalization">[Layer-Normalization]</a>. Unlike <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization" id="ref-for-dom-mlgraphbuilder-batchnormalization②">batchNormalization()</a></code> where the mean and variance values are computed across all the samples in the batch dimension while the model is trained, and in <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization" id="ref-for-dom-mlgraphbuilder-instancenormalization①">instanceNormalization()</a></code> where the mean and variance values are computed on the fly for each input feature of each individual sample in the batch, the means and variance values of the layer normalization are computed on the fly across all the input features of each individual sample in the batch. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllayernormalizationoptions"><code><c- g>MLLayerNormalizationOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllayernormalizationoptions-scale" id="ref-for-dom-mllayernormalizationoptions-scale"><c- g>scale</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllayernormalizationoptions-bias" id="ref-for-dom-mllayernormalizationoptions-bias"><c- g>bias</c-></a>;
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllayernormalizationoptions"><code><c- g>MLLayerNormalizationOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤④"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllayernormalizationoptions-scale" id="ref-for-dom-mllayernormalizationoptions-scale"><c- g>scale</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllayernormalizationoptions-bias" id="ref-for-dom-mllayernormalizationoptions-bias"><c- g>bias</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑨"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②⓪"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③③"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes"><c- g>axes</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①⑤"><c- b>double</c-></a> <a class="idl-code" data-default="1e-5" data-link-type="dict-member" data-type="double" href="#dom-mllayernormalizationoptions-epsilon" id="ref-for-dom-mllayernormalizationoptions-epsilon"><c- g>epsilon</c-></a> = 1e-5;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④①"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-layernormalization" id="ref-for-dom-mlgraphbuilder-layernormalization"><c- g>layerNormalization</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input"><c- g>input</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④②"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-layernormalization" id="ref-for-dom-mlgraphbuilder-layernormalization"><c- g>layerNormalization</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input"><c- g>input</c-></a>,
                                <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mllayernormalizationoptions" id="ref-for-dictdef-mllayernormalizationoptions"><c- n>MLLayerNormalizationOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-layernormalization-input-options-options" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mllayernormalizationoptions" id="ref-for-dictdef-mllayernormalizationoptions①">MLLayerNormalizationOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④⑨">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤⓪">MLOperand</a></span>
     <dd data-md>
      <p>The N-D tensor of the scaling values whose shape is determined by the <var>axes</var> member in that each value in <var>axes</var> indicates the dimension of the input tensor with scaling values. For example, for an <var>axes</var> values of [1,2,3], the shape of this tensor is the list of the corresponding sizes of the input dimension 1, 2 and 3. When this member is not present, the scaling value is assumed to be 1.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤⓪">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤①">MLOperand</a></span>
     <dd data-md>
      <p>The N-D tensor of the bias values whose shape is determined by the <var>axes</var> member in that each value in <var>axes</var> indicates the dimension of the input tensor with bias values. For example, for an <var>axes</var> values of [1,2,3], the shape of this tensor is the list of the corresponding sizes of the input dimension 1, 2 and 3. When this member is not present, the bias value is assumed to be 0.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-axes"><code>axes</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
@@ -5358,11 +5402,11 @@ <h4 class="heading settled" data-level="7.7.25" id="api-mlgraphbuilder-layernorm
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/layerNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-layernormalization-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤①">MLOperand</a></code>. The input N-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/layerNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-layernormalization-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤②">MLOperand</a></code>. The input N-D tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/layerNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-layernormalization-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mllayernormalizationoptions" id="ref-for-dictdef-mllayernormalizationoptions②">MLLayerNormalizationOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤②">MLOperand</a></code>. The layer-normalized N-D tensor of the same shape as <em>input</em>.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤③">MLOperand</a></code>. The layer-normalized N-D tensor of the same shape as <em>input</em>.</p>
    </div>
    <details class="algorithm" data-algorithm="layerNormalization(input, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="layerNormalization(input, options)|layerNormalization(input)" id="dom-mlgraphbuilder-layernormalization"><code>layerNormalization(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -5423,7 +5467,7 @@ <h4 class="heading settled" data-level="7.7.25" id="api-mlgraphbuilder-layernorm
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand⑧">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑧">operator</a> for the "layerNormalization" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③②">operator</a> for the "layerNormalization" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot②④">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -5468,12 +5512,12 @@ <h4 class="heading settled" data-level="7.7.25" id="api-mlgraphbuilder-layernorm
    </div>
    <h4 class="heading settled" data-level="7.7.26" id="api-mlgraphbuilder-leakyrelu"><span class="secno">7.7.26. </span><span class="content">leakyRelu</span><a class="self-link" href="#api-mlgraphbuilder-leakyrelu"></a></h4>
     Calculate the <a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Leaky_ReLU"> leaky version of rectified linear function</a> on the input tensor element-wise. The calculation follows the expression <code>max(0, x) + alpha * min(0, x)</code>. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlleakyreluoptions"><code><c- g>MLLeakyReluOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlleakyreluoptions"><code><c- g>MLLeakyReluOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤⑤"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①⑦"><c- b>double</c-></a> <a class="idl-code" data-default="0.01" data-link-type="dict-member" data-type="double" href="#dom-mlleakyreluoptions-alpha" id="ref-for-dom-mlleakyreluoptions-alpha"><c- g>alpha</c-></a> = 0.01;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④②"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-leakyrelu" id="ref-for-dom-mlgraphbuilder-leakyrelu"><c- g>leakyRelu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlleakyreluoptions" id="ref-for-dictdef-mlleakyreluoptions"><c- n>MLLeakyReluOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-leakyrelu-input-options-options" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④③"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-leakyrelu" id="ref-for-dom-mlgraphbuilder-leakyrelu"><c- g>leakyRelu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlleakyreluoptions" id="ref-for-dictdef-mlleakyreluoptions"><c- n>MLLeakyReluOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-leakyrelu-input-options-options" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlleakyreluoptions" id="ref-for-dictdef-mlleakyreluoptions①">MLLeakyReluOptions</a></code> has the following members:</p>
@@ -5486,14 +5530,14 @@ <h4 class="heading settled" data-level="7.7.26" id="api-mlgraphbuilder-leakyrelu
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/leakyRelu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-leakyrelu-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤⑤">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/leakyRelu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-leakyrelu-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤⑥">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/leakyRelu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-leakyrelu-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlleakyreluoptions" id="ref-for-dictdef-mlleakyreluoptions②">MLLeakyReluOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤⑥">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤⑦">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
    <details class="algorithm" data-algorithm="leakyRelu(input, options)" data-algorithm-for="MLGraphBuilder" open>
@@ -5513,7 +5557,7 @@ <h4 class="heading settled" data-level="7.7.26" id="api-mlgraphbuilder-leakyrelu
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand⑨">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators②⑨">operator</a> for the "leakyRelu" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③③">operator</a> for the "leakyRelu" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot②⑤">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -5540,13 +5584,13 @@ <h4 class="heading settled" data-level="7.7.26" id="api-mlgraphbuilder-leakyrelu
    </div>
    <h4 class="heading settled" data-level="7.7.27" id="api-mlgraphbuilder-linear"><span class="secno">7.7.27. </span><span class="content">linear</span><a class="self-link" href="#api-mlgraphbuilder-linear"></a></h4>
     Calculate a linear function <code>y = alpha * x + beta</code> on the input tensor. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllinearoptions"><code><c- g>MLLinearOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllinearoptions"><code><c- g>MLLinearOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤⑥"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①⑨"><c- b>double</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="double" href="#dom-mllinearoptions-alpha" id="ref-for-dom-mllinearoptions-alpha"><c- g>alpha</c-></a> = 1;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double②⓪"><c- b>double</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="double" href="#dom-mllinearoptions-beta" id="ref-for-dom-mllinearoptions-beta"><c- g>beta</c-></a> = 0;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④③"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-linear" id="ref-for-dom-mlgraphbuilder-linear"><c- g>linear</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mllinearoptions" id="ref-for-dictdef-mllinearoptions"><c- n>MLLinearOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-linear-input-options-options" id="ref-for-dom-mlgraphbuilder-linear-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④④"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-linear" id="ref-for-dom-mlgraphbuilder-linear"><c- g>linear</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mllinearoptions" id="ref-for-dictdef-mllinearoptions"><c- n>MLLinearOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-linear-input-options-options" id="ref-for-dom-mlgraphbuilder-linear-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mllinearoptions" id="ref-for-dictdef-mllinearoptions①">MLLinearOptions</a></code> has the following members:</p>
@@ -5562,14 +5606,14 @@ <h4 class="heading settled" data-level="7.7.27" id="api-mlgraphbuilder-linear"><
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/linear(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-linear-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤⑨">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/linear(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-linear-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑥⓪">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/linear(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-linear-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mllinearoptions" id="ref-for-dictdef-mllinearoptions②">MLLinearOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑥⓪">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑥①">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
    <details class="algorithm" data-algorithm="linear(input, options)" data-algorithm-for="MLGraphBuilder" open>
@@ -5591,7 +5635,7 @@ <h4 class="heading settled" data-level="7.7.27" id="api-mlgraphbuilder-linear"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①⓪">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⓪">operator</a> for the "linear" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③④">operator</a> for the "linear" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot②⑥">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -5621,22 +5665,22 @@ <h4 class="heading settled" data-level="7.7.28" id="api-mlgraphbuilder-lstm"><sp
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmWeightLayout" data-dfn-type="enum-value" data-export id="dom-mllstmweightlayout-ifgo"><code><c- s>"ifgo"</c-></code></dfn>  // input-forget-cell-output gate ordering
 };
 
-<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllstmoptions"><code><c- g>MLLstmOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-bias" id="ref-for-dom-mllstmoptions-bias"><c- g>bias</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-recurrentbias" id="ref-for-dom-mllstmoptions-recurrentbias"><c- g>recurrentBias</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-peepholeweight" id="ref-for-dom-mllstmoptions-peepholeweight"><c- g>peepholeWeight</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-initialhiddenstate" id="ref-for-dom-mllstmoptions-initialhiddenstate"><c- g>initialHiddenState</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-initialcellstate" id="ref-for-dom-mllstmoptions-initialcellstate"><c- g>initialCellState</c-></a>;
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllstmoptions"><code><c- g>MLLstmOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤⑦"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-bias" id="ref-for-dom-mllstmoptions-bias"><c- g>bias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-recurrentbias" id="ref-for-dom-mllstmoptions-recurrentbias"><c- g>recurrentBias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-peepholeweight" id="ref-for-dom-mllstmoptions-peepholeweight"><c- g>peepholeWeight</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-initialhiddenstate" id="ref-for-dom-mllstmoptions-initialhiddenstate"><c- g>initialHiddenState</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-initialcellstate" id="ref-for-dom-mllstmoptions-initialcellstate"><c- g>initialCellState</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①③"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mllstmoptions-returnsequence" id="ref-for-dom-mllstmoptions-returnsequence"><c- g>returnSequence</c-></a> = <c- b>false</c->;
   <a data-link-type="idl-name" href="#enumdef-mlrecurrentnetworkdirection" id="ref-for-enumdef-mlrecurrentnetworkdirection②"><c- n>MLRecurrentNetworkDirection</c-></a> <a class="idl-code" data-default="&quot;forward&quot;" data-link-type="dict-member" data-type="MLRecurrentNetworkDirection" href="#dom-mllstmoptions-direction" id="ref-for-dom-mllstmoptions-direction"><c- g>direction</c-></a> = "forward";
   <a data-link-type="idl-name" href="#enumdef-mllstmweightlayout" id="ref-for-enumdef-mllstmweightlayout"><c- n>MLLstmWeightLayout</c-></a> <a class="idl-code" data-default="&quot;iofg&quot;" data-link-type="dict-member" data-type="MLLstmWeightLayout" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout"><c- g>layout</c-></a> = "iofg";
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⓪"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#enumdef-mlrecurrentnetworkactivation" id="ref-for-enumdef-mlrecurrentnetworkactivation④"><c- n>MLRecurrentNetworkActivation</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<MLRecurrentNetworkActivation>" href="#dom-mllstmoptions-activations" id="ref-for-dom-mllstmoptions-activations"><c- g>activations</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④④"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②①"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑥"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lstm" id="ref-for-dom-mlgraphbuilder-lstm"><c- g>lstm</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-input"><c- g>input</c-></a>,
-                           <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight"><c- g>weight</c-></a>,
-                           <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑤"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②①"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑦"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lstm" id="ref-for-dom-mlgraphbuilder-lstm"><c- g>lstm</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-input"><c- g>input</c-></a>,
+                           <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑥⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight"><c- g>weight</c-></a>,
+                           <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
                            [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③④"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-steps" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-steps"><c- g>steps</c-></a>,
                            [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②②"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③⑤"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-hiddensize" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-hiddensize"><c- g>hiddenSize</c-></a>,
                            <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mllstmoptions" id="ref-for-dictdef-mllstmoptions"><c- n>MLLstmOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-options" id="ref-for-dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-options"><c- g>options</c-></a> = {});
@@ -5644,19 +5688,19 @@ <h4 class="heading settled" data-level="7.7.28" id="api-mlgraphbuilder-lstm"><sp
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mllstmoptions" id="ref-for-dictdef-mllstmoptions①">MLLstmOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦⓪">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦①">MLOperand</a></span>
     <dd data-md>
      <p>The 2-D input bias tensor of shape <em>[numDirections, 4 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout①">layout</a></code>.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦①">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦②">MLOperand</a></span>
     <dd data-md>
      <p>The 2-D recurrent bias tensor of shape <em>[numDirections, 4 * hiddenSize]</em>. The ordering of the bias vectors in the first dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout②">layout</a></code>.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-peepholeweight"><code>peepholeWeight</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦②">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-peepholeweight"><code>peepholeWeight</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦③">MLOperand</a></span>
     <dd data-md>
      <p>The 2-D weight tensor for peepholes of shape <em>[numDirections, 3 * hiddenSize]</em>. The pack ordering of the weight vectors is for the <code>input (i)</code>, <code>output (o)</code>, and <code>forget (f)</code> gate, respectively.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-initialhiddenstate"><code>initialHiddenState</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦③">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-initialhiddenstate"><code>initialHiddenState</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦④">MLOperand</a></span>
     <dd data-md>
      <p>The 3-D initial hidden state tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>. When not specified, implementations SHOULD use a tensor filled with zero.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-initialcellstate"><code>initialCellState</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦④">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-initialcellstate"><code>initialCellState</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦⑤">MLOperand</a></span>
     <dd data-md>
      <p>The 3-D initial hidden state tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>. When not specified, implementations SHOULD use a tensor filled with zero.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmOptions" data-dfn-type="dict-member" data-export id="dom-mllstmoptions-returnsequence"><code>returnSequence</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①④">boolean</a>, defaulting to <code>false</code></span>
@@ -5676,11 +5720,11 @@ <h4 class="heading settled" data-level="7.7.28" id="api-mlgraphbuilder-lstm"><sp
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑤">MLOperand</a></code>. The input 3-D tensor of shape <em>[steps, batchSize, inputSize]</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑥">MLOperand</a></code>. The input 3-D tensor of shape <em>[steps, batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑥">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout③">layout</a></code>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑦">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout③">layout</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑦">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout④">layout</a></code> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑧">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout④">layout</a></code> argument.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-steps"><code>steps</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③⑥">unsigned long</a></code> scalar. The number of time steps in the recurrent network. The value must be greater than 0.</p>
      <li data-md>
@@ -5688,7 +5732,7 @@ <h4 class="heading settled" data-level="7.7.28" id="api-mlgraphbuilder-lstm"><sp
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mllstmoptions" id="ref-for-dictdef-mllstmoptions②">MLLstmOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②②">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑧">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output hidden state from the last time step of the network. The second element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output cell state from the last time step of the network. Additionally, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-returnsequence" id="ref-for-dom-mllstmoptions-returnsequence①">returnSequence</a></code> is set to true, the third element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every output from each time step in the temporal sequence.</p>
+    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②②">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑨">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output hidden state from the last time step of the network. The second element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output cell state from the last time step of the network. Additionally, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-returnsequence" id="ref-for-dom-mllstmoptions-returnsequence①">returnSequence</a></code> is set to true, the third element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every output from each time step in the temporal sequence.</p>
    </div>
    <details class="algorithm" data-algorithm="lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="lstm(input, weight, recurrentWeight, steps, hiddenSize, options)|lstm(input, weight, recurrentWeight, steps, hiddenSize)" id="dom-mlgraphbuilder-lstm"><code>lstm(<var>input</var>, <var>weight</var>, <var>recurrentWeight</var>, <var>steps</var>, <var>hiddenSize</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -5793,7 +5837,7 @@ <h4 class="heading settled" data-level="7.7.28" id="api-mlgraphbuilder-lstm"><sp
       <p><em>Make graph connections:</em></p>
       <ol>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③①">operator</a> for the "lstm" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>steps</var>, <var>hiddenSize</var> and <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑤">operator</a> for the "lstm" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>steps</var>, <var>hiddenSize</var> and <var>options</var>.</p>
        <li data-md>
         <p>Let <var>output0</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand①⑥">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑨②">this</a> and <var>desc</var>.</p>
        <li data-md>
@@ -5967,33 +6011,33 @@ <h4 class="heading settled" data-level="7.7.28" id="api-mlgraphbuilder-lstm"><sp
    </div>
    <h4 class="heading settled" data-level="7.7.29" id="api-mlgraphbuilder-lstmcell"><span class="secno">7.7.29. </span><span class="content">lstmCell</span><a class="self-link" href="#api-mlgraphbuilder-lstmcell"></a></h4>
     A single time step of the Long Short-Term Memory <a data-link-type="biblio" href="#biblio-lstm" title="Long Short-Term Memory">[LSTM]</a> recurrent network using a cell state, an input, output, and forget gate to compute the cell state and the hidden state of the next time step that rolls into the output across the temporal sequence of the network. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllstmcelloptions"><code><c- g>MLLstmCellOptions</c-></code></dfn> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑦⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-bias" id="ref-for-dom-mllstmcelloptions-bias"><c- g>bias</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-recurrentbias" id="ref-for-dom-mllstmcelloptions-recurrentbias"><c- g>recurrentBias</c-></a>;
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-peepholeweight" id="ref-for-dom-mllstmcelloptions-peepholeweight"><c- g>peepholeWeight</c-></a>;
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mllstmcelloptions"><code><c- g>MLLstmCellOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤⑧"><c- n>MLOperatorOptions</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-bias" id="ref-for-dom-mllstmcelloptions-bias"><c- g>bias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-recurrentbias" id="ref-for-dom-mllstmcelloptions-recurrentbias"><c- g>recurrentBias</c-></a>;
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-peepholeweight" id="ref-for-dom-mllstmcelloptions-peepholeweight"><c- g>peepholeWeight</c-></a>;
   <a data-link-type="idl-name" href="#enumdef-mllstmweightlayout" id="ref-for-enumdef-mllstmweightlayout②"><c- n>MLLstmWeightLayout</c-></a> <a class="idl-code" data-default="&quot;iofg&quot;" data-link-type="dict-member" data-type="MLLstmWeightLayout" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout"><c- g>layout</c-></a> = "iofg";
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②③"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#enumdef-mlrecurrentnetworkactivation" id="ref-for-enumdef-mlrecurrentnetworkactivation⑥"><c- n>MLRecurrentNetworkActivation</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<MLRecurrentNetworkActivation>" href="#dom-mllstmcelloptions-activations" id="ref-for-dom-mllstmcelloptions-activations"><c- g>activations</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑤"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②④"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧②"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lstmcell" id="ref-for-dom-mlgraphbuilder-lstmcell"><c- g>lstmCell</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-input"><c- g>input</c-></a>,
-                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight"><c- g>weight</c-></a>,
-                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
-                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddenstate" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddenstate"><c- g>hiddenState</c-></a>,
-                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-cellstate" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-cellstate"><c- g>cellState</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑥"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②④"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧③"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lstmcell" id="ref-for-dom-mlgraphbuilder-lstmcell"><c- g>lstmCell</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-input" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-input"><c- g>input</c-></a>,
+                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight"><c- g>weight</c-></a>,
+                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight"><c- g>recurrentWeight</c-></a>,
+                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddenstate" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddenstate"><c- g>hiddenState</c-></a>,
+                               <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-cellstate" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-cellstate"><c- g>cellState</c-></a>,
                                [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②③"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③⑧"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddensize" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddensize"><c- g>hiddenSize</c-></a>,
                                <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mllstmcelloptions" id="ref-for-dictdef-mllstmcelloptions"><c- n>MLLstmCellOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-options" id="ref-for-dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mllstmcelloptions" id="ref-for-dictdef-mllstmcelloptions①">MLLstmCellOptions</a></code> has the following members:</p>
    <dl>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑧">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑨">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D input bias tensor of shape <em>[4 * hiddenSize]</em>. The ordering of the bias vectors in the first dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout①">layout</a></code> argument.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑧⑨">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⓪">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D recurrent bias tensor of shape <em>[4 * hiddenSize]</em>. The ordering of the bias vectors in the first dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout②">layout</a></code> argument.</p>
-    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-peepholeweight"><code>peepholeWeight</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⓪">MLOperand</a></span>
+    <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-peepholeweight"><code>peepholeWeight</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨①">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D weight tensor for peepholes of shape <em>[3 * hiddenSize]</em>. The pack ordering of the weight vectors is for the <code>input (i)</code>, <code>output (o)</code>, and <code>forget (f)</code> gate, respectively.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-layout"><code>layout</code></dfn>, <span> of type <a data-link-type="idl-name" href="#enumdef-mllstmweightlayout" id="ref-for-enumdef-mllstmweightlayout③">MLLstmWeightLayout</a>, defaulting to <code>"iofg"</code></span>
@@ -6007,21 +6051,21 @@ <h4 class="heading settled" data-level="7.7.29" id="api-mlgraphbuilder-lstmcell"
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨①">MLOperand</a></code>. The input 2-D tensor of shape <em>[batchSize, inputSize]</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨②">MLOperand</a></code>. The input 2-D tensor of shape <em>[batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨②">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨③">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨③">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨④">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddenstate"><code>hiddenState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨④">MLOperand</a></code>. The 2-D input hidden state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddenstate"><code>hiddenState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑤">MLOperand</a></code>. The 2-D input hidden state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-cellstate"><code>cellState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑤">MLOperand</a></code>. The 2-D input cell state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-cellstate"><code>cellState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑥">MLOperand</a></code>. The 2-D input cell state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddensize"><code>hiddenSize</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③⑨">unsigned long</a></code> scalar. The value of the second dimension of the output tensor shape. It indicates the number of features in the hidden state.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mllstmcelloptions" id="ref-for-dictdef-mllstmcelloptions②">MLLstmCellOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑤">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑥">MLOperand</a></code>>. The first element is the output hidden state of the current time step of the recurrent network. The following element is the output cell state. Both elements are 2-D tensors of shape <em>[batchSize, hiddenSize]</em>.</p>
+    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑤">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑦">MLOperand</a></code>>. The first element is the output hidden state of the current time step of the recurrent network. The following element is the output cell state. Both elements are 2-D tensors of shape <em>[batchSize, hiddenSize]</em>.</p>
    </div>
    <details class="algorithm" data-algorithm="lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)|lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize)" id="dom-mlgraphbuilder-lstmcell"><code>lstmCell(<var>input</var>, <var>weight</var>, <var>recurrentWeight</var>, <var>hiddenState</var>, <var>cellState</var>, <var>hiddenSize</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -6108,7 +6152,7 @@ <h4 class="heading settled" data-level="7.7.29" id="api-mlgraphbuilder-lstmcell"
        <li data-md>
         <p>Let <var>output</var> be the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list②⑤">list</a> « <var>output0</var>, <var>output1</var> ».</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③②">operator</a> for the "lstmCell" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>hiddenState</var>, <var>cellState</var>, <var>hiddenSize</var> and <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑥">operator</a> for the "lstmCell" operation, given <var>weight</var>, <var>recurrentWeight</var>, <var>hiddenState</var>, <var>cellState</var>, <var>hiddenSize</var> and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output0</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③②">[[operator]]</a></code> and <var>output1</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③③">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -6252,19 +6296,21 @@ <h4 class="heading settled" data-level="7.7.29" id="api-mlgraphbuilder-lstmcell"
    </div>
    <h4 class="heading settled" data-level="7.7.30" id="api-mlgraphbuilder-matmul"><span class="secno">7.7.30. </span><span class="content">matmul</span><a class="self-link" href="#api-mlgraphbuilder-matmul"></a></h4>
     Compute the matrix product of two input tensors. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑥"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-matmul" id="ref-for-dom-mlgraphbuilder-matmul"><c- g>matmul</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-b"><c- g>b</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑦"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-matmul" id="ref-for-dom-mlgraphbuilder-matmul"><c- g>matmul</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⓪⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑤⑨"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-options-options" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/matmul(a, b)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-matmul-a-b-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪⓪">MLOperand</a></code>. The first input tensor which is at least 2-D.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/matmul(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-matmul-a-b-options-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪①">MLOperand</a></code>. The first input tensor which is at least 2-D.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/matmul(a, b)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-matmul-a-b-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪①">MLOperand</a></code>. The second input tensor which is at least 2-D.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/matmul(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-matmul-a-b-options-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪②">MLOperand</a></code>. The second input tensor which is at least 2-D.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/matmul(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-matmul-a-b-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥⓪">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪②">MLOperand</a></code>. The output tensor that contains the matrix
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪③">MLOperand</a></code>. The output tensor that contains the matrix
     product of two input tensors.</p>
    </div>
    <div>
@@ -6278,7 +6324,7 @@ <h4 class="heading settled" data-level="7.7.30" id="api-mlgraphbuilder-matmul"><
     </ul>
    </div>
    <details class="algorithm" data-algorithm="calculate matmul output sizes" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-calculate-matmul-output-sizes">calculate matmul output sizes</dfn>, given <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪③">MLOperand</a></code> <var>a</var> and <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪④">MLOperand</a></code> <var>b</var> run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-calculate-matmul-output-sizes">calculate matmul output sizes</dfn>, given <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪④">MLOperand</a></code> <var>a</var> and <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪⑤">MLOperand</a></code> <var>b</var> run the following steps: </summary>
     <ol>
      <li data-md>
       <p>Let <var>shapeA</var> be a <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-clone" id="ref-for-list-clone①②">clone</a> of <var>a</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑦⑥">shape</a>.</p>
@@ -6312,8 +6358,8 @@ <h4 class="heading settled" data-level="7.7.30" id="api-mlgraphbuilder-matmul"><
       <p>Return <var>outputShape</var>.</p>
     </ol>
    </details>
-   <details class="algorithm" data-algorithm="matmul(a, b)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-matmul"><code>matmul(<var>a</var>, <var>b</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="matmul(a, b, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="matmul(a, b, options)|matmul(a, b)" id="dom-mlgraphbuilder-matmul"><code>matmul(<var>a</var>, <var>b</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑨⑨">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot③①">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②⑥⑥">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror②⑨">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException③⑨">DOMException</a></code>.</p>
@@ -6337,7 +6383,7 @@ <h4 class="heading settled" data-level="7.7.30" id="api-mlgraphbuilder-matmul"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②①">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①⓪①">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③③">operator</a> for the "matmul" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑦">operator</a> for the "matmul" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③④">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -6358,13 +6404,13 @@ <h4 class="heading settled" data-level="7.7.31" id="api-mlgraphbuilder-pad"><spa
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLPaddingMode" data-dfn-type="enum-value" data-export id="dom-mlpaddingmode-symmetric"><code><c- s>"symmetric"</c-></code></dfn>
 };
 
-<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlpadoptions"><code><c- g>MLPadOptions</c-></code></dfn> {
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlpadoptions"><code><c- g>MLPadOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥①"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#enumdef-mlpaddingmode" id="ref-for-enumdef-mlpaddingmode"><c- n>MLPaddingMode</c-></a> <a class="idl-code" data-default="&quot;constant&quot;" data-link-type="dict-member" data-type="MLPaddingMode" href="#dom-mlpadoptions-mode" id="ref-for-dom-mlpadoptions-mode"><c- g>mode</c-></a> = "constant";
   <a data-link-type="idl-name" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber⑨"><c- n>MLNumber</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="MLNumber" href="#dom-mlpadoptions-value" id="ref-for-dom-mlpadoptions-value"><c- g>value</c-></a> = 0;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑦"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⓪⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-pad" id="ref-for-dom-mlgraphbuilder-pad"><c- g>pad</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⓪⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input"><c- g>input</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑧"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⓪⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-pad" id="ref-for-dom-mlgraphbuilder-pad"><c- g>pad</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⓪⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input"><c- g>input</c-></a>,
                 <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑥"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②④"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④⓪"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-beginningpadding" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-beginningpadding"><c- g>beginningPadding</c-></a>,
                 <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑦"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②⑤"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④①"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-endingpadding" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-endingpadding"><c- g>endingPadding</c-></a>,
                 <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlpadoptions" id="ref-for-dictdef-mlpadoptions"><c- n>MLPadOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-options" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-options"><c- g>options</c-></a> = {});
@@ -6383,7 +6429,7 @@ <h4 class="heading settled" data-level="7.7.31" id="api-mlgraphbuilder-pad"><spa
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪⑦">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪⑧">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-beginningpadding"><code>beginningPadding</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑧">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④②">unsigned long</a></code>>. The number of padding values to add at the beginning of each input dimension, of length <em>N</em> where <em>N</em> is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑦">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>beginningPadding[d]</em> indicates how many values to add before the content in that dimension.</p>
      <li data-md>
@@ -6391,7 +6437,7 @@ <h4 class="heading settled" data-level="7.7.31" id="api-mlgraphbuilder-pad"><spa
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlpadoptions" id="ref-for-dictdef-mlpadoptions②">MLPadOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪⑧">MLOperand</a></code>. The padded output tensor. Each dimension of the output tensor can be calculated as follows:</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪⑨">MLOperand</a></code>. The padded output tensor. Each dimension of the output tensor can be calculated as follows:</p>
     <p><code>output size = beginning padding + input size + ending padding</code></p>
    </div>
    <details class="algorithm" data-algorithm="calculate padding output sizes" data-algorithm-for="MLGraphBuilder" open>
@@ -6438,7 +6484,7 @@ <h4 class="heading settled" data-level="7.7.31" id="api-mlgraphbuilder-pad"><spa
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②②">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①⓪④">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③④">operator</a> for the "padding" operation, given <var>beginningPadding</var>, <var>endingPadding</var> and <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑧">operator</a> for the "padding" operation, given <var>beginningPadding</var>, <var>endingPadding</var> and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③⑤">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -6499,7 +6545,7 @@ <h4 class="heading settled" data-level="7.7.32" id="api-mlgraphbuilder-pool2d"><
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLRoundingType" data-dfn-type="enum-value" data-export id="dom-mlroundingtype-ceil"><code><c- s>"ceil"</c-></code></dfn>
 };
 
-<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlpool2doptions"><code><c- g>MLPool2dOptions</c-></code></dfn> {
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlpool2doptions"><code><c- g>MLPool2dOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥②"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⓪"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②⑥"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④④"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlpool2doptions-windowdimensions" id="ref-for-dom-mlpool2doptions-windowdimensions"><c- g>windowDimensions</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③①"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②⑦"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④⑤"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlpool2doptions-padding" id="ref-for-dom-mlpool2doptions-padding"><c- g>padding</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③②"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange②⑧"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④⑥"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlpool2doptions-strides" id="ref-for-dom-mlpool2doptions-strides"><c- g>strides</c-></a>;
@@ -6509,10 +6555,10 @@ <h4 class="heading settled" data-level="7.7.32" id="api-mlgraphbuilder-pool2d"><
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③④"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⓪"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④⑧"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlpool2doptions-outputsizes" id="ref-for-dom-mlpool2doptions-outputsizes"><c- g>outputSizes</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑧"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⓪⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-averagepool2d" id="ref-for-dom-mlgraphbuilder-averagepool2d"><c- g>averagePool2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-input" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions"><c- n>MLPool2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-options" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-options"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-l2pool2d" id="ref-for-dom-mlgraphbuilder-l2pool2d"><c- g>l2Pool2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-input" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-input①"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions①"><c- n>MLPool2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-options" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-options①"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-maxpool2d" id="ref-for-dom-mlgraphbuilder-maxpool2d"><c- g>maxPool2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-input" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-input②"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions②"><c- n>MLPool2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-options" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-options②"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑨"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-averagepool2d" id="ref-for-dom-mlgraphbuilder-averagepool2d"><c- g>averagePool2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-input" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions"><c- n>MLPool2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-options" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-l2pool2d" id="ref-for-dom-mlgraphbuilder-l2pool2d"><c- g>l2Pool2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-input" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-input①"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions①"><c- n>MLPool2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-options" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-options①"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-maxpool2d" id="ref-for-dom-mlgraphbuilder-maxpool2d"><c- g>maxPool2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-input" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-input②"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions②"><c- n>MLPool2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-averagepool2d-input-options-options" id="ref-for-dom-mlgraphbuilder-averagepool2d-input-options-options②"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions③">MLPool2dOptions</a></code> has the following members:</p>
@@ -6570,12 +6616,12 @@ <h4 class="heading settled" data-level="7.7.32" id="api-mlgraphbuilder-pool2d"><
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/averagePool2d(input, options), MLGraphBuilder/l2Pool2d(input, options), MLGraphBuilder/maxPool2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-averagepool2d-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑤">MLOperand</a></code>. The input 4-D tensor. The logical shape
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/averagePool2d(input, options), MLGraphBuilder/l2Pool2d(input, options), MLGraphBuilder/maxPool2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-averagepool2d-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑥">MLOperand</a></code>. The input 4-D tensor. The logical shape
 is interpreted according to the value of <em>options.layout</em>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/averagePool2d(input, options), MLGraphBuilder/l2Pool2d(input, options), MLGraphBuilder/maxPool2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-averagepool2d-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions④">MLPool2dOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑥">MLOperand</a></code>. The output 4-D tensor that contains the
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑦">MLOperand</a></code>. The output 4-D tensor that contains the
     result of the reduction. The logical shape is interpreted according to the
     value of <em>layout</em>. More specifically, if the <em>options.roundingType</em> is <code class="idl"><a data-link-type="idl" href="#dom-mlroundingtype-floor" id="ref-for-dom-mlroundingtype-floor">"floor"</a></code>, the spatial dimensions of the output tensor can be calculated as follows:</p>
     <p><code>output size = floor(1 + (input size - filter size + beginning padding + ending padding) / stride)</code></p>
@@ -6670,7 +6716,7 @@ <h4 class="heading settled" data-level="7.7.32" id="api-mlgraphbuilder-pool2d"><
     </ol>
    </details>
    <details class="algorithm" data-algorithm="pooling-op" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="pooling-op" data-noexport id="mlgraphbuilder-pooling-op">create pooling operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string⑥">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑦">MLOperand</a></code> <var>input</var>, <code class="idl"><a data-link-type="idl" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions⑤">MLPool2dOptions</a></code> <var>options</var>, and optional <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list③③">list</a> <var>allowedDataTypes</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="pooling-op" data-noexport id="mlgraphbuilder-pooling-op">create pooling operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string⑥">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑧">MLOperand</a></code> <var>input</var>, <code class="idl"><a data-link-type="idl" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions⑤">MLPool2dOptions</a></code> <var>options</var>, and optional <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list③③">list</a> <var>allowedDataTypes</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#assert" id="ref-for-assert⑤">Assert</a>: <var>op</var> is one of "averagePool2d", "l2Pool2d", "maxPool2d".</p>
@@ -6724,7 +6770,7 @@ <h4 class="heading settled" data-level="7.7.32" id="api-mlgraphbuilder-pool2d"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②③">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①⓪⑦">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑤">operator</a> for the <var>op</var> operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑨">operator</a> for the <var>op</var> operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③⑥">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -6787,26 +6833,30 @@ <h5 class="heading settled" data-level="7.7.32.3" id="api-mlgraphbuilder-pool2d-
    <h4 class="heading settled" data-level="7.7.33" id="api-mlgraphbuilder-prelu"><span class="secno">7.7.33. </span><span class="content">prelu</span><a class="self-link" href="#api-mlgraphbuilder-prelu"></a></h4>
     Calculate the <a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Parametric_ReLU">parametric version of rectified linear function (Parametric ReLU)</a> on the input tensor element-wise. Parametric ReLU is a type of leaky ReLU that, instead of having a scalar slope like 0.01, making the slope (coefficient of leakage) into a parameter that is learned during the model training phase of this operation. The calculation follows the expression <code>max(0, x) + slope * min(0, x)</code>. 
    <p>The operation will be broadcast according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The input tensors must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable③">bidirectionally broadcastable</a>. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④③">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④④">rank</a> of the input tensors. For each dimension of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder④⑨"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-prelu" id="ref-for-dom-mlgraphbuilder-prelu"><c- g>prelu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-slope" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-slope"><c- g>slope</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⓪"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③①⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-prelu" id="ref-for-dom-mlgraphbuilder-prelu"><c- g>prelu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input"><c- g>input</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-options-slope" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-slope"><c- g>slope</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥③"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-options-options" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②①">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②②">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-options-slope"><code>slope</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②③">MLOperand</a></code>. The slope tensor. Its shape must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable④">bidirectionally broadcastable</a> to the shape of <em>input</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-slope"><code>slope</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②②">MLOperand</a></code>. The slope tensor. Its shape must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable④">bidirectionally broadcastable</a> to the shape of <em>input</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥④">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②③">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②④">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="prelu(input, slope)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-prelu"><code>prelu(<var>input</var>, <var>slope</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="prelu(input, slope, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="prelu(input, slope, options)|prelu(input, slope)" id="dom-mlgraphbuilder-prelu"><code>prelu(<var>input</var>, <var>slope</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①⓪⑧">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot③④">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②⑨⑤">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror③②">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException④②">DOMException</a></code>.</p>
@@ -6830,7 +6880,7 @@ <h4 class="heading settled" data-level="7.7.33" id="api-mlgraphbuilder-prelu"><s
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②④">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①①⓪">this</a> and <var>descriptor</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑥">operator</a> for the "prelu" operation, given <var>slope</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⓪">operator</a> for the "prelu" operation, given <var>slope</var> and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③⑦">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -6856,22 +6906,22 @@ <h4 class="heading settled" data-level="7.7.33" id="api-mlgraphbuilder-prelu"><s
    </div>
    <h4 class="heading settled" data-level="7.7.34" id="api-mlgraphbuilder-reduce"><span class="secno">7.7.34. </span><span class="content">Reduction operations</span><a class="self-link" href="#api-mlgraphbuilder-reduce"></a></h4>
     Reduce the input tensor along all dimensions, or along the axes specified in the <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-axes" id="ref-for-dom-mlreduceoptions-axes">axes</a></code> array parameter. For each specified axis, the dimension with that index is reduced, i.e. the resulting tensor will not contain it, unless the <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions">keepDimensions</a></code> option is specified. The values of the resulting tensor are calculated using the specified reduction function that takes as parameters all the values across the reduced dimension. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlreduceoptions"><code><c- g>MLReduceOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlreduceoptions"><code><c- g>MLReduceOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥⑤"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⑤"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④⑨"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlreduceoptions-axes" id="ref-for-dom-mlreduceoptions-axes①"><c- g>axes</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①⑤"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions①"><c- g>keepDimensions</c-></a> = <c- b>false</c->;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⓪"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducel1" id="ref-for-dom-mlgraphbuilder-reducel1"><c- g>reduceL1</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducel2" id="ref-for-dom-mlgraphbuilder-reducel2"><c- g>reduceL2</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input①"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions①"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options①"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducelogsum" id="ref-for-dom-mlgraphbuilder-reducelogsum"><c- g>reduceLogSum</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input②"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions②"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options②"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducelogsumexp" id="ref-for-dom-mlgraphbuilder-reducelogsumexp"><c- g>reduceLogSumExp</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input③"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions③"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options③"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducemax" id="ref-for-dom-mlgraphbuilder-reducemax"><c- g>reduceMax</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input④"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions④"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options④"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducemean" id="ref-for-dom-mlgraphbuilder-reducemean"><c- g>reduceMean</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑤"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑤"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑤"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducemin" id="ref-for-dom-mlgraphbuilder-reducemin"><c- g>reduceMin</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑥"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑥"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑥"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reduceproduct" id="ref-for-dom-mlgraphbuilder-reduceproduct"><c- g>reduceProduct</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑦"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑦"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑦"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducesum" id="ref-for-dom-mlgraphbuilder-reducesum"><c- g>reduceSum</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑧"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑧"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑧"><c- g>options</c-></a> = {});
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducesumsquare" id="ref-for-dom-mlgraphbuilder-reducesumsquare"><c- g>reduceSumSquare</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑨"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑨"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑨"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤①"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducel1" id="ref-for-dom-mlgraphbuilder-reducel1"><c- g>reduceL1</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducel2" id="ref-for-dom-mlgraphbuilder-reducel2"><c- g>reduceL2</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input①"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions①"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options①"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③②⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducelogsum" id="ref-for-dom-mlgraphbuilder-reducelogsum"><c- g>reduceLogSum</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input②"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions②"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options②"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducelogsumexp" id="ref-for-dom-mlgraphbuilder-reducelogsumexp"><c- g>reduceLogSumExp</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input③"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions③"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options③"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducemax" id="ref-for-dom-mlgraphbuilder-reducemax"><c- g>reduceMax</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input④"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions④"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options④"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducemean" id="ref-for-dom-mlgraphbuilder-reducemean"><c- g>reduceMean</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑤"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑤"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑤"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducemin" id="ref-for-dom-mlgraphbuilder-reducemin"><c- g>reduceMin</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑥"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑥"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑥"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③③⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reduceproduct" id="ref-for-dom-mlgraphbuilder-reduceproduct"><c- g>reduceProduct</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑦"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑦"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑦"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducesum" id="ref-for-dom-mlgraphbuilder-reducesum"><c- g>reduceSum</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑧"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑧"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑧"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reducesumsquare" id="ref-for-dom-mlgraphbuilder-reducesumsquare"><c- g>reduceSumSquare</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-input" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-input⑨"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions⑨"><c- n>MLReduceOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reducel1-input-options-options" id="ref-for-dom-mlgraphbuilder-reducel1-input-options-options⑨"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions①⓪">MLReduceOptions</a></code> has the following members:</p>
@@ -6887,11 +6937,11 @@ <h4 class="heading settled" data-level="7.7.34" id="api-mlgraphbuilder-reduce"><
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reduceL1(input, options), MLGraphBuilder/reduceL2(input, options), MLGraphBuilder/reduceLogSum(input, options), MLGraphBuilder/reduceLogSumExp(input, options), MLGraphBuilder/reduceMax(input, options), MLGraphBuilder/reduceMean(input, options), MLGraphBuilder/reduceMin(input, options), MLGraphBuilder/reduceProduct(input, options), MLGraphBuilder/reduceSum(input, options), MLGraphBuilder/reduceSumSquare(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reducel1-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④④">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reduceL1(input, options), MLGraphBuilder/reduceL2(input, options), MLGraphBuilder/reduceLogSum(input, options), MLGraphBuilder/reduceLogSumExp(input, options), MLGraphBuilder/reduceMax(input, options), MLGraphBuilder/reduceMean(input, options), MLGraphBuilder/reduceMin(input, options), MLGraphBuilder/reduceProduct(input, options), MLGraphBuilder/reduceSum(input, options), MLGraphBuilder/reduceSumSquare(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reducel1-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④⑤">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reduceL1(input, options), MLGraphBuilder/reduceL2(input, options), MLGraphBuilder/reduceLogSum(input, options), MLGraphBuilder/reduceLogSumExp(input, options), MLGraphBuilder/reduceMax(input, options), MLGraphBuilder/reduceMean(input, options), MLGraphBuilder/reduceMin(input, options), MLGraphBuilder/reduceProduct(input, options), MLGraphBuilder/reduceSum(input, options), MLGraphBuilder/reduceSumSquare(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reducel1-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions①①">MLReduceOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④⑤">MLOperand</a></code>. The reduced output tensor.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④⑥">MLOperand</a></code>. The reduced output tensor.</p>
    </div>
    <div class="note" role="note">
      <strong>Reduction types:</strong> 
@@ -6956,7 +7006,7 @@ <h4 class="heading settled" data-level="7.7.34" id="api-mlgraphbuilder-reduce"><
     </ol>
    </details>
    <details class="algorithm" data-algorithm="reduce-op" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="reduce-op" data-noexport id="mlgraphbuilder-reduce-op">create reduce operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string⑦">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④⑥">MLOperand</a></code> <var>input</var>, <code class="idl"><a data-link-type="idl" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions①②">MLReduceOptions</a></code> <var>options</var>, and optional <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④①">list</a> <var>allowedDataTypes</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-lt="reduce-op" data-noexport id="mlgraphbuilder-reduce-op">create reduce operation</dfn> given <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#string" id="ref-for-string⑦">string</a> <var>op</var>, <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④⑦">MLOperand</a></code> <var>input</var>, <code class="idl"><a data-link-type="idl" href="#dictdef-mlreduceoptions" id="ref-for-dictdef-mlreduceoptions①②">MLReduceOptions</a></code> <var>options</var>, and optional <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④①">list</a> <var>allowedDataTypes</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#assert" id="ref-for-assert⑥">Assert</a>: <var>op</var> is one of "reduceL1", "reduceL2", "reduceLogSum", "reduceLogSumExp", "reduceMax", "reduceMean", "reduceMin", "reduceProduct", "reduceSum", "reduceSumSquare".</p>
@@ -6976,7 +7026,7 @@ <h4 class="heading settled" data-level="7.7.34" id="api-mlgraphbuilder-reduce"><
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②⑤">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①①③">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑦">operator</a> for the <var>op</var> operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④①">operator</a> for the <var>op</var> operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③⑧">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7141,24 +7191,26 @@ <h4 class="heading settled" data-level="7.7.34" id="api-mlgraphbuilder-reduce"><
    <div class="note" role="note"> Some underlying platforms do not support an option like <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions③">keepDimensions</a></code> directly. This does not affect the underlying tensor data, only the shape. For example, if the input shape is <em>[2, 3, 4]</em>, the axis is 1, and <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions④">keepDimensions</a></code> is true, the expected output shape is <em>[2, 1 ,4]</em>. If the underlying platform never keeps reduced dimensions it will produce an output shape of <em>[2, 4]</em>. The implementation can introduce a no-op reshape to <em>[2, 1, 4]</em>. A similar no-op reshape can be introduced if <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions⑤">keepDimensions</a></code> is false but the underlying platform always keeps reduced dimensions. </div>
    <h4 class="heading settled" data-level="7.7.35" id="api-mlgraphbuilder-relu-method"><span class="secno">7.7.35. </span><span class="content">relu</span><a class="self-link" href="#api-mlgraphbuilder-relu-method"></a></h4>
     Compute the <a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)">rectified linear function</a> of the input tensor. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤①"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-relu" id="ref-for-dom-mlgraphbuilder-relu①"><c- g>relu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-relu-input-input" id="ref-for-dom-mlgraphbuilder-relu-input-input"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤②"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-relu" id="ref-for-dom-mlgraphbuilder-relu①"><c- g>relu</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③④⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥⑥"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-relu-input-options-options" id="ref-for-dom-mlgraphbuilder-relu-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/relu(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-relu-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③④⑨">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/relu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-relu-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⓪">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/relu(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-relu-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥⑦">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⓪">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤①">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="relu(input)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-relu"><code>relu(<var>input</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="relu(input, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="relu(input, options)|relu(input)" id="dom-mlgraphbuilder-relu"><code>relu(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①①④">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot③⑥">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③②④">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror③④">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException④④">DOMException</a></code>.</p>
@@ -7172,7 +7224,7 @@ <h4 class="heading settled" data-level="7.7.35" id="api-mlgraphbuilder-relu-meth
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①①">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑧">operator</a> for the "relu" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④②">operator</a> for the "relu" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot③⑨">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7200,26 +7252,26 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLInterpolationMode" data-dfn-type="enum-value" data-export id="dom-mlinterpolationmode-linear"><code><c- s>"linear"</c-></code></dfn>
 };
 
-<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlresample2doptions"><code><c- g>MLResample2dOptions</c-></code></dfn> {
+<c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlresample2doptions"><code><c- g>MLResample2dOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥⑧"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#enumdef-mlinterpolationmode" id="ref-for-enumdef-mlinterpolationmode"><c- n>MLInterpolationMode</c-></a> <a class="idl-code" data-default="&quot;nearest-neighbor&quot;" data-link-type="dict-member" data-type="MLInterpolationMode" href="#dom-mlresample2doptions-mode" id="ref-for-dom-mlresample2doptions-mode"><c- g>mode</c-></a> = "nearest-neighbor";
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⑥"><c- b>sequence</c-></a>&lt;<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-float" id="ref-for-idl-float"><c- b>float</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<float>" href="#dom-mlresample2doptions-scales" id="ref-for-dom-mlresample2doptions-scales"><c- g>scales</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⑦"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③②"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⓪"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes"><c- g>sizes</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⑧"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③③"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤①"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes"><c- g>axes</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤②"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-resample2d" id="ref-for-dom-mlgraphbuilder-resample2d"><c- g>resample2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-resample2d-input-options-input" id="ref-for-dom-mlgraphbuilder-resample2d-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlresample2doptions" id="ref-for-dictdef-mlresample2doptions"><c- n>MLResample2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-resample2d-input-options-options" id="ref-for-dom-mlgraphbuilder-resample2d-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤③"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-resample2d" id="ref-for-dom-mlgraphbuilder-resample2d"><c- g>resample2d</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-resample2d-input-options-input" id="ref-for-dom-mlgraphbuilder-resample2d-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlresample2doptions" id="ref-for-dictdef-mlresample2doptions"><c- n>MLResample2dOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-resample2d-input-options-options" id="ref-for-dom-mlgraphbuilder-resample2d-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/resample2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-resample2d-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤③">MLOperand</a></code>. The input 4-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/resample2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-resample2d-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤④">MLOperand</a></code>. The input 4-D tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/resample2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-resample2d-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlresample2doptions" id="ref-for-dictdef-mlresample2doptions①">MLResample2dOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤④">MLOperand</a></code>. The output 4-D tensor.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⑤">MLOperand</a></code>. The output 4-D tensor.</p>
    </div>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlresample2doptions" id="ref-for-dictdef-mlresample2doptions②">MLResample2dOptions</a></code> has the following members:</p>
    <dl>
@@ -7259,7 +7311,7 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
     </ol>
    </details>
    <details class="algorithm" data-algorithm="calculate resample output sizes" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-calculate-resample-output-sizes">calculate resample output sizes</dfn> given <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⑤">MLOperand</a></code> <var>input</var> and <code class="idl"><a data-link-type="idl" href="#dictdef-mlresample2doptions" id="ref-for-dictdef-mlresample2doptions③">MLResample2dOptions</a></code> <var>options</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-calculate-resample-output-sizes">calculate resample output sizes</dfn> given <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⑥">MLOperand</a></code> <var>input</var> and <code class="idl"><a data-link-type="idl" href="#dictdef-mlresample2doptions" id="ref-for-dictdef-mlresample2doptions③">MLResample2dOptions</a></code> <var>options</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p>Let <var>inputDescriptor</var> be <var>input</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-descriptor-slot" id="ref-for-dom-mloperand-descriptor-slot①⓪">[[descriptor]]</a></code>.</p>
@@ -7302,7 +7354,7 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②⑥">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①①⑧">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators③⑨">operator</a> for the "resample2d" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④③">operator</a> for the "resample2d" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④⓪">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7316,26 +7368,30 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
    </details>
    <h4 class="heading settled" data-level="7.7.37" id="api-mlgraphbuilder-reshape-method"><span class="secno">7.7.37. </span><span class="content">reshape</span><a class="self-link" href="#api-mlgraphbuilder-reshape-method"></a></h4>
     Alter the shape of a tensor to a new shape. Reshape does not copy or change the content of the tensor. It just changes the tensor’s logical dimensions for the subsequent operations. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤③"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reshape" id="ref-for-dom-mlgraphbuilder-reshape"><c- g>reshape</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-input" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-input"><c- g>input</c-></a>, <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⑨"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③④"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤②"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-newshape" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-newshape"><c- g>newShape</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤④"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reshape" id="ref-for-dom-mlgraphbuilder-reshape"><c- g>reshape</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑤⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-options-input" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-input"><c- g>input</c-></a>,
+                    <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⑨"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③④"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤②"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-options-newshape" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-newshape"><c- g>newShape</c-></a>,
+                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥⑨"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-options-options" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⑧">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⑨">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-newshape"><code>newShape</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⓪">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤③">unsigned long</a></code>>. The shape of the output tensor.
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-options-newshape"><code>newShape</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⓪">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤③">unsigned long</a></code>>. The shape of the output tensor.
 The number of elements implied by <em>newShape</em> must be the same as the
 number of elements in the input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦⓪">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤⑨">MLOperand</a></code>. The output tensor. The values of the output
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⓪">MLOperand</a></code>. The output tensor. The values of the output
     tensor are the same as values of the input tensor. The shape of the output
     tensor is specified by the <em>newShape</em> argument.</p>
    </div>
-   <details class="algorithm" data-algorithm="reshape(input, newShape)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-reshape"><code>reshape(<var>input</var>, <var>newShape</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="reshape(input, newShape, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="reshape(input, newShape, options)|reshape(input, newShape)" id="dom-mlgraphbuilder-reshape"><code>reshape(<var>input</var>, <var>newShape</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①①⑨">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot③⑧">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③③">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror③⑥">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException④⑥">DOMException</a></code>.</p>
@@ -7361,7 +7417,7 @@ <h4 class="heading settled" data-level="7.7.37" id="api-mlgraphbuilder-reshape-m
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②⑦">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①②①">this</a> and <var>desc</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⓪">operator</a> for the "reshape" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④④">operator</a> for the "reshape" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④①">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7375,24 +7431,26 @@ <h4 class="heading settled" data-level="7.7.37" id="api-mlgraphbuilder-reshape-m
    </details>
    <h4 class="heading settled" data-level="7.7.38" id="api-mlgraphbuilder-sigmoid-method"><span class="secno">7.7.38. </span><span class="content">sigmoid</span><a class="self-link" href="#api-mlgraphbuilder-sigmoid-method"></a></h4>
     Compute the <a href="https://en.wikipedia.org/wiki/Sigmoid_function">sigmoid function</a> of the input tensor. The calculation follows the expression <code>1 / (exp(-x) + 1)</code>. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤④"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sigmoid" id="ref-for-dom-mlgraphbuilder-sigmoid②"><c- g>sigmoid</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-sigmoid-input-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-input"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑤"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sigmoid" id="ref-for-dom-mlgraphbuilder-sigmoid②"><c- g>sigmoid</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦①"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-sigmoid-input-options-options" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/sigmoid(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-sigmoid-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥②">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/sigmoid(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-sigmoid-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥③">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/sigmoid(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-sigmoid-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦②">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥③">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥④">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="sigmoid(input)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-sigmoid"><code>sigmoid(<var>input</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="sigmoid(input, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="sigmoid(input, options)|sigmoid(input)" id="dom-mlgraphbuilder-sigmoid"><code>sigmoid(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①②②">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot③⑨">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③⑦">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror③⑦">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException④⑦">DOMException</a></code>.</p>
@@ -7406,7 +7464,7 @@ <h4 class="heading settled" data-level="7.7.38" id="api-mlgraphbuilder-sigmoid-m
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①②">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④①">operator</a> for the "sigmoid" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑤">operator</a> for the "sigmoid" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④②">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7432,26 +7490,29 @@ <h4 class="heading settled" data-level="7.7.38" id="api-mlgraphbuilder-sigmoid-m
    </div>
    <h4 class="heading settled" data-level="7.7.39" id="api-mlgraphbuilder-slice"><span class="secno">7.7.39. </span><span class="content">slice</span><a class="self-link" href="#api-mlgraphbuilder-slice"></a></h4>
     Produce a slice of the input tensor. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑤"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-slice" id="ref-for-dom-mlgraphbuilder-slice"><c- g>slice</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-input"><c- g>input</c-></a>,
-                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④①"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⑤"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑤"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-starts" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-starts"><c- g>starts</c-></a>,
-                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④②"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⑥"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑥"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-sizes" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-sizes"><c- g>sizes</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑥"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-slice" id="ref-for-dom-mlgraphbuilder-slice"><c- g>slice</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input"><c- g>input</c-></a>,
+                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④①"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⑤"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑤"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-starts" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-starts"><c- g>starts</c-></a>,
+                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④②"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⑥"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑥"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes"><c- g>sizes</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦③"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-options" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⑥">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⑦">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-starts"><code>starts</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④③">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑦">unsigned long</a></code>>. The starting index to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑦">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>starts[d]</em> indicates the starting index to slice in that dimension. The starting index must be in the range [0, input size - 1] in that dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-starts"><code>starts</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④③">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑦">unsigned long</a></code>>. The starting index to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑦">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>starts[d]</em> indicates the starting index to slice in that dimension. The starting index must be in the range [0, input size - 1] in that dimension.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-sizes"><code>sizes</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④④">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑧">unsigned long</a></code>>. The number of elements to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑧">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>sizes[d]</em> indicates the number of elements to slice in that dimension. The size must not be 0 and must satisfy the constraint <code>starting index + size &lt;= input size</code> in that dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes"><code>sizes</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④④">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑧">unsigned long</a></code>>. The number of elements to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑧">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>sizes[d]</em> indicates the number of elements to slice in that dimension. The size must not be 0 and must satisfy the constraint <code>starting index + size &lt;= input size</code> in that dimension.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦④">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⑦">MLOperand</a></code>. The output tensor of the same rank as the input tensor with tensor values stripped to the specified starting and ending indices in each dimension.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⑧">MLOperand</a></code>. The output tensor of the same rank as the input tensor with tensor values stripped to the specified starting and ending indices in each dimension.</p>
    </div>
-   <details class="algorithm" data-algorithm="slice(input, starts, sizes)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-slice"><code>slice(<var>input</var>, <var>starts</var>, <var>sizes</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="slice(input, starts, sizes, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="slice(input, starts, sizes, options)|slice(input, starts, sizes)" id="dom-mlgraphbuilder-slice"><code>slice(<var>input</var>, <var>starts</var>, <var>sizes</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①②④">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot④⓪">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④⓪">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror③⑧">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException④⑧">DOMException</a></code>.</p>
@@ -7478,7 +7539,7 @@ <h4 class="heading settled" data-level="7.7.39" id="api-mlgraphbuilder-slice"><s
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①③">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④②">operator</a> for the "slice" operation, given <var>starts</var> and <var>sizes</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑥">operator</a> for the "slice" operation, given <var>starts</var>, <var>sizes</var>, and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④③">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7493,26 +7554,30 @@ <h4 class="heading settled" data-level="7.7.39" id="api-mlgraphbuilder-slice"><s
    <h4 class="heading settled" data-level="7.7.40" id="api-mlgraphbuilder-softmax-method"><span class="secno">7.7.40. </span><span class="content">softmax</span><a class="self-link" href="#api-mlgraphbuilder-softmax-method"></a></h4>
     Compute the <a href="https://en.wikipedia.org/wiki/Softmax_function">softmax</a> values of
 the N-D input tensor along the given axis. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑥"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softmax" id="ref-for-dom-mlgraphbuilder-softmax"><c- g>softmax</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-input"><c- g>input</c-></a>, <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑨"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-axis" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-axis"><c- g>axis</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑦"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑥⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softmax" id="ref-for-dom-mlgraphbuilder-softmax"><c- g>softmax</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input"><c- g>input</c-></a>,
+                    <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑨"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-options-axis" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-axis"><c- g>axis</c-></a>,
+                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦⑤"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-options-options" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softmax(input, axis)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softmax-input-axis-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⓪">MLOperand</a></code>. The input N-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softmax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softmax-input-axis-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦①">MLOperand</a></code>. The input N-D tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softmax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softmax-input-axis-options-axis"><code>axis</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⓪">unsigned long</a></code> scalar. The dimension the reduction will be performed on.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softmax(input, axis)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softmax-input-axis-axis"><code>axis</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⓪">unsigned long</a></code> scalar. The dimension the reduction will be performed on.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softmax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softmax-input-axis-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦⑥">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦①">MLOperand</a></code>. The output N-D tensor that contains the softmax results, of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦②">MLOperand</a></code>. The output N-D tensor that contains the softmax results, of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="softmax(input, axis)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-softmax"><code>softmax(<var>input</var>, <var>axis</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="softmax(input, axis, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="softmax(input, axis, options)|softmax(input, axis)" id="dom-mlgraphbuilder-softmax"><code>softmax(<var>input</var>, <var>axis</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①②⑥">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot④①">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④⑦">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror③⑨">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException④⑨">DOMException</a></code>.</p>
@@ -7528,7 +7593,7 @@ <h4 class="heading settled" data-level="7.7.40" id="api-mlgraphbuilder-softmax-m
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①④">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④③">operator</a> for the "softmax" operation, given <var>axis</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑦">operator</a> for the "softmax" operation, given <var>axis</var> and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④④">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7559,24 +7624,26 @@ <h4 class="heading settled" data-level="7.7.40" id="api-mlgraphbuilder-softmax-m
    </div>
    <h4 class="heading settled" data-level="7.7.41" id="api-mlgraphbuilder-softplus-method"><span class="secno">7.7.41. </span><span class="content">softplus</span><a class="self-link" href="#api-mlgraphbuilder-softplus-method"></a></h4>
     Compute the <a href="https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Softplus">softplus function</a> of the input tensor. The calculation follows the expression <code>ln(1 + exp(x))</code>. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑦"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softplus" id="ref-for-dom-mlgraphbuilder-softplus"><c- g>softplus</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softplus-input-input" id="ref-for-dom-mlgraphbuilder-softplus-input-input"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑧"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softplus" id="ref-for-dom-mlgraphbuilder-softplus"><c- g>softplus</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦⑦"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softplus-input-options-options" id="ref-for-dom-mlgraphbuilder-softplus-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softplus(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softplus-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦④">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softplus(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softplus-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑤">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softplus(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softplus-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦⑧">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑤">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑥">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="softplus(input)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-softplus"><code>softplus(<var>input</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="softplus(input, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="softplus(input, options)|softplus(input)" id="dom-mlgraphbuilder-softplus"><code>softplus(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①②⑧">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot④②">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤①">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror④⓪">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException⑤⓪">DOMException</a></code>.</p>
@@ -7590,7 +7657,7 @@ <h4 class="heading settled" data-level="7.7.41" id="api-mlgraphbuilder-softplus-
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①⑤">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④④">operator</a> for the "softplus" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑧">operator</a> for the "softplus" operation and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④⑤">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7614,8 +7681,8 @@ <h4 class="heading settled" data-level="7.7.41" id="api-mlgraphbuilder-softplus-
    </div>
    <h4 class="heading settled" data-level="7.7.42" id="api-mlgraphbuilder-softsign-method"><span class="secno">7.7.42. </span><span class="content">softsign</span><a class="self-link" href="#api-mlgraphbuilder-softsign-method"></a></h4>
     Compute the <a href="https://pytorch.org/docs/stable/generated/torch.nn.Softsign.html">softsign function</a> of the input tensor. The calculation follows the expression <code>x / (1 + |x|)</code>. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑧"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softsign" id="ref-for-dom-mlgraphbuilder-softsign"><c- g>softsign</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softsign-input-input" id="ref-for-dom-mlgraphbuilder-softsign-input-input"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑨"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softsign" id="ref-for-dom-mlgraphbuilder-softsign"><c- g>softsign</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑦⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦⑨"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softsign-input-options-options" id="ref-for-dom-mlgraphbuilder-softsign-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div class="note" role="note">
@@ -7633,16 +7700,18 @@ <h4 class="heading settled" data-level="7.7.42" id="api-mlgraphbuilder-softsign-
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softsign(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softsign-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑧">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softsign(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softsign-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑨">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/softsign(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-softsign-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧⓪">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑨">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⓪">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="softsign(input)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-softsign"><code>softsign(<var>input</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="softsign(input, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="softsign(input, options)|softsign(input)" id="dom-mlgraphbuilder-softsign"><code>softsign(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①③⓪">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot④③">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤④">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror④①">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException⑤①">DOMException</a></code>.</p>
@@ -7656,7 +7725,7 @@ <h4 class="heading settled" data-level="7.7.42" id="api-mlgraphbuilder-softsign-
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①⑥">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑤">operator</a> for the "softsign" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑨">operator</a> for the "softsign" operation and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④⑥">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7670,13 +7739,13 @@ <h4 class="heading settled" data-level="7.7.42" id="api-mlgraphbuilder-softsign-
    </details>
    <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><span class="secno">7.7.43. </span><span class="content">split</span><a class="self-link" href="#api-mlgraphbuilder-split"></a></h4>
     Split the input tensor into a number of sub tensors along the given axis. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlsplitoptions"><code><c- g>MLSplitOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlsplitoptions"><code><c- g>MLSplitOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧①"><c- n>MLOperatorOptions</c-></a> {
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⑦"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥①"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis"><c- g>axis</c-></a> = 0;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑤⑨"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑤"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧⓪"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-split" id="ref-for-dom-mlgraphbuilder-split"><c- g>split</c-></a>(
-      <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input"><c- g>input</c-></a>,
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥⓪"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑤"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧①"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-split" id="ref-for-dom-mlgraphbuilder-split"><c- g>split</c-></a>(
+      <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input"><c- g>input</c-></a>,
       ([<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⑧"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥②"><c- b>unsigned</c-> <c- b>long</c-></a> <c- b>or</c-> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑥"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③⑨"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥③"><c- b>unsigned</c-> <c- b>long</c-></a>>) <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-split-input-splits-options-splits" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-splits"><c- g>splits</c-></a>,
       <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlsplitoptions" id="ref-for-dictdef-mlsplitoptions"><c- n>MLSplitOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-split-input-splits-options-options" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-options"><c- g>options</c-></a> = {});
 };
@@ -7685,13 +7754,13 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧②">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧③">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-splits"><code>splits</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥④">unsigned long</a></code> or <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑦">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑤">unsigned long</a></code>>. If an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑥">unsigned long</a></code>, it specifies the number of output tensors along the axis. The number must evenly divide the dimension size of <em>input</em> along <em>options.axis</em>. If a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑧">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑦">unsigned long</a></code>>, it specifies the sizes of each output tensor along the <em>options.axis</em>. The sum of sizes must equal to the dimension size of <em>input</em> along <em>options.axis</em>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlsplitoptions" id="ref-for-dictdef-mlsplitoptions①">MLSplitOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑨">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧③">MLOperand</a></code>>. The split output tensors. If <em>splits</em> is an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑧">unsigned long</a></code>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④⓪">size</a> of the output is equal to <em>splits</em>. The shape of each output tensor is the same as <em>input</em> except the dimension size of <em>axis</em> equals to the quotient of dividing the dimension size of <em>input</em> along <em>axis</em> by <em>splits</em>. If <em>splits</em> is a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑤⓪">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑨">unsigned long</a></code>>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④①">size</a> of the output equals the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④②">size</a> of <em>splits</em>. The shape of the i-th output tensor is the same as <em>input</em> except along <em>axis</em> where the dimension size is <em>splits[i]</em>.</p>
+    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑨">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧④">MLOperand</a></code>>. The split output tensors. If <em>splits</em> is an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑧">unsigned long</a></code>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④⓪">size</a> of the output is equal to <em>splits</em>. The shape of each output tensor is the same as <em>input</em> except the dimension size of <em>axis</em> equals to the quotient of dividing the dimension size of <em>input</em> along <em>axis</em> by <em>splits</em>. If <em>splits</em> is a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑤⓪">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑨">unsigned long</a></code>>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④①">size</a> of the output equals the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④②">size</a> of <em>splits</em>. The shape of the i-th output tensor is the same as <em>input</em> except along <em>axis</em> where the dimension size is <em>splits[i]</em>.</p>
    </div>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlsplitoptions" id="ref-for-dictdef-mlsplitoptions②">MLSplitOptions</a></code> has the following members:</p>
    <dl>
@@ -7733,7 +7802,7 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
       <p><em>Make graph connections:</em></p>
       <ol>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑥">operator</a> for the "split" operation, given <var>splits</var> and <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤⓪">operator</a> for the "split" operation, given <var>splits</var> and <var>options</var>.</p>
        <li data-md>
         <p>Let <var>outputs</var> be a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑤">list</a>.</p>
        <li data-md>
@@ -7785,24 +7854,26 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
    </div>
    <h4 class="heading settled" data-level="7.7.44" id="api-mlgraphbuilder-tanh-method"><span class="secno">7.7.44. </span><span class="content">tanh</span><a class="self-link" href="#api-mlgraphbuilder-tanh-method"></a></h4>
     Compute the <a href="https://en.wikipedia.org/wiki/Hyperbolic_functions">hyperbolic tangent function</a> of the input tensor. The calculation follows the expression <code>(exp(2 * x) - 1) / (exp(2 * x) + 1)</code>. 
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥⓪"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tanh" id="ref-for-dom-mlgraphbuilder-tanh②"><c- g>tanh</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-tanh-input-input" id="ref-for-dom-mlgraphbuilder-tanh-input-input"><c- g>input</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥①"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧⑤"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tanh" id="ref-for-dom-mlgraphbuilder-tanh②"><c- g>tanh</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧②"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-tanh-input-options-options" id="ref-for-dom-mlgraphbuilder-tanh-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/tanh(input)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-tanh-input-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑥">MLOperand</a></code>. The input tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/tanh(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-tanh-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑦">MLOperand</a></code>. The input tensor.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/tanh(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-tanh-input-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧③">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑦">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑧">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
     </ul>
    </div>
-   <details class="algorithm" data-algorithm="tanh(input)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-tanh"><code>tanh(<var>input</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="tanh(input, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="tanh(input, options)|tanh(input)" id="dom-mlgraphbuilder-tanh"><code>tanh(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①③④">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot④⑤">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥③">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror④③">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException⑤③">DOMException</a></code>.</p>
@@ -7816,7 +7887,7 @@ <h4 class="heading settled" data-level="7.7.44" id="api-mlgraphbuilder-tanh-meth
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①⑧">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑦">operator</a> for the "tanh" operation.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤①">operator</a> for the "tanh" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④⑧">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7845,12 +7916,12 @@ <h4 class="heading settled" data-level="7.7.44" id="api-mlgraphbuilder-tanh-meth
    </div>
    <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose"><span class="secno">7.7.45. </span><span class="content">transpose</span><a class="self-link" href="#api-mlgraphbuilder-transpose"></a></h4>
     Permute the dimensions of the input tensor according to the <em>permutation</em> argument. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mltransposeoptions"><code><c- g>MLTransposeOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mltransposeoptions"><code><c- g>MLTransposeOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧④"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑤②"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange④⓪"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑦④"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation"><c- g>permutation</c-></a>;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥①"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-transpose" id="ref-for-dom-mlgraphbuilder-transpose"><c- g>transpose</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-transpose-input-options-input" id="ref-for-dom-mlgraphbuilder-transpose-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mltransposeoptions" id="ref-for-dictdef-mltransposeoptions"><c- n>MLTransposeOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-transpose-input-options-options" id="ref-for-dom-mlgraphbuilder-transpose-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥②"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑧⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-transpose" id="ref-for-dom-mlgraphbuilder-transpose"><c- g>transpose</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-transpose-input-options-input" id="ref-for-dom-mlgraphbuilder-transpose-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mltransposeoptions" id="ref-for-dictdef-mltransposeoptions"><c- n>MLTransposeOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-transpose-input-options-options" id="ref-for-dom-mlgraphbuilder-transpose-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mltransposeoptions" id="ref-for-dictdef-mltransposeoptions①">MLTransposeOptions</a></code> has the following members:</p>
@@ -7865,11 +7936,11 @@ <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/transpose(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-transpose-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨⓪">MLOperand</a></code>. The input N-D tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/transpose(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-transpose-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨①">MLOperand</a></code>. The input N-D tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/transpose(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-transpose-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mltransposeoptions" id="ref-for-dictdef-mltransposeoptions②">MLTransposeOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨①">MLOperand</a></code>. The permuted or transposed N-D tensor.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨②">MLOperand</a></code>. The permuted or transposed N-D tensor.</p>
    </div>
    <details class="algorithm" data-algorithm="transpose(input, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="transpose(input, options)|transpose(input)" id="dom-mlgraphbuilder-transpose"><code>transpose(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -7896,7 +7967,7 @@ <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①⑨">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑧">operator</a> for the "transpose" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤②">operator</a> for the "transpose" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot④⑨">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -7910,13 +7981,13 @@ <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose
    </details>
    <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangular"><span class="secno">7.7.46. </span><span class="content">triangular</span><a class="self-link" href="#api-mlgraphbuilder-triangular"></a></h4>
     Given a 2-D tensor (matrix), return a 2-D tensor containing either the upper or lower triangular part of the input tensor. If the input tensor has greater than 2 dimensions it is treated as a batch of matrices and the result has the same shape. 
-<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mltriangularoptions"><code><c- g>MLTriangularOptions</c-></code></dfn> {
+<pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mltriangularoptions"><code><c- g>MLTriangularOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧⑤"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①⑦"><c- b>boolean</c-></a> <a class="idl-code" data-default="true" data-link-type="dict-member" data-type="boolean" href="#dom-mltriangularoptions-upper" id="ref-for-dom-mltriangularoptions-upper"><c- g>upper</c-></a> = <c- b>true</c->;
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange④①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-long" id="ref-for-idl-long①"><c- b>long</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="long" href="#dom-mltriangularoptions-diagonal" id="ref-for-dom-mltriangularoptions-diagonal"><c- g>diagonal</c-></a> = 0;
 };
 
-<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥②"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨②"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-triangular" id="ref-for-dom-mlgraphbuilder-triangular"><c- g>triangular</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-triangular-input-options-input" id="ref-for-dom-mlgraphbuilder-triangular-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mltriangularoptions" id="ref-for-dictdef-mltriangularoptions"><c- n>MLTriangularOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-triangular-input-options-options" id="ref-for-dom-mlgraphbuilder-triangular-input-options-options"><c- g>options</c-></a> = {});
+<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥③"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨③"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-triangular" id="ref-for-dom-mlgraphbuilder-triangular"><c- g>triangular</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨④"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-triangular-input-options-input" id="ref-for-dom-mlgraphbuilder-triangular-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mltriangularoptions" id="ref-for-dictdef-mltriangularoptions"><c- n>MLTriangularOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-triangular-input-options-options" id="ref-for-dom-mlgraphbuilder-triangular-input-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mltriangularoptions" id="ref-for-dictdef-mltriangularoptions①">MLTriangularOptions</a></code> has the following members:</p>
@@ -7932,11 +8003,11 @@ <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangula
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/triangular(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-triangular-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨④">MLOperand</a></code>. The input tensor which is at least 2-D.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/triangular(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-triangular-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨⑤">MLOperand</a></code>. The input tensor which is at least 2-D.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/triangular(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-triangular-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mltriangularoptions" id="ref-for-dictdef-mltriangularoptions②">MLTriangularOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨⑤">MLOperand</a></code>. The output tensor representing a triangular matrix, or batch of matrices which is the same shape as the input.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑨⑥">MLOperand</a></code>. The output tensor representing a triangular matrix, or batch of matrices which is the same shape as the input.</p>
    </div>
    <details class="algorithm" data-algorithm="triangular(input, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="triangular(input, options)|triangular(input)" id="dom-mlgraphbuilder-triangular"><code>triangular(<var>input</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -7953,7 +8024,7 @@ <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangula
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand②⓪">copying an MLOperand</a> given <var>input</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators④⑨">operator</a> for the "triangular" operation, given <var>options</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤③">operator</a> for the "triangular" operation, given <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot⑤⓪">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -8026,24 +8097,29 @@ <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangula
    <h4 class="heading settled" data-level="7.7.47" id="api-mlgraphbuilder-where"><span class="secno">7.7.47. </span><span class="content">where</span><a class="self-link" href="#api-mlgraphbuilder-where"></a></h4>
     Select the values from the trueValue or the falseValue tensor depending on the corresponding values of the condition tensor, where non-zero is true and zero is false. The condition tensor is often the output of one of the element-wise logical operations. 
    <p>The operation will be broadcast according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The input tensors must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable⑤">bidirectionally broadcastable</a>. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑨">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥⓪">rank</a> of the input tensors. For each dimension of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
-<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥③"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑥"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-where" id="ref-for-dom-mlgraphbuilder-where"><c- g>where</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-condition"><c- g>condition</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-truevalue"><c- g>trueValue</c-></a>, <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-falsevalue"><c- g>falseValue</c-></a>);
+<pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥④"><c- g>MLGraphBuilder</c-></a> {
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑦"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-where" id="ref-for-dom-mlgraphbuilder-where"><c- g>where</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition"><c- g>condition</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue"><c- g>trueValue</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④⓪⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue"><c- g>falseValue</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧⑥"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-options" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-options"><c- g>options</c-></a> = {});
 };
 </pre>
    <div>
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-condition"><code>condition</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪⓪">MLOperand</a></code>. The condition tensor.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition"><code>condition</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪①">MLOperand</a></code>. The condition tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-truevalue"><code>trueValue</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪①">MLOperand</a></code>. The tensor from which the value is selected when the condition of the corresponding element is set to true.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue"><code>trueValue</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪②">MLOperand</a></code>. The tensor from which the value is selected when the condition of the corresponding element is set to true.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-falsevalue"><code>falseValue</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪②">MLOperand</a></code>. The tensor from which the value is selected when the condition of the corresponding element is set to false.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue"><code>falseValue</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪③">MLOperand</a></code>. The tensor from which the value is selected when the condition of the corresponding element is set to false.</p>
+     <li data-md>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧⑦">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪③">MLOperand</a></code>. The output tensor that contains the values selected element-wise from either the trueValue or the falseValue tensor.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪④">MLOperand</a></code>. The output tensor that contains the values selected element-wise from either the trueValue or the falseValue tensor.</p>
    </div>
-   <details class="algorithm" data-algorithm="where(condition, trueValue, falseValue)" data-algorithm-for="MLGraphBuilder" open>
-    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export id="dom-mlgraphbuilder-where"><code>where(<var>condition</var>, <var>trueValue</var>, <var>falseValue</var>)</code></dfn> method steps are: </summary>
+   <details class="algorithm" data-algorithm="where(condition, trueValue, falseValue, options)" data-algorithm-for="MLGraphBuilder" open>
+    <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="where(condition, trueValue, falseValue, options)|where(condition, trueValue, falseValue)" id="dom-mlgraphbuilder-where"><code>where(<var>condition</var>, <var>trueValue</var>, <var>falseValue</var>, <var>options</var>)</code></dfn> method steps are: </summary>
     <ol>
      <li data-md>
       <p>If <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①④⓪">this</a>.<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hasbuilt-slot" id="ref-for-dom-mlgraphbuilder-hasbuilt-slot④⑧">[[hasBuilt]]</a></code> is true, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦④">throw</a> an "<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#invalidstateerror" id="ref-for-invalidstateerror④⑥">InvalidStateError</a></code>" <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-DOMException" id="ref-for-idl-DOMException⑤⑥">DOMException</a></code>.</p>
@@ -8073,7 +8149,7 @@ <h4 class="heading settled" data-level="7.7.47" id="api-mlgraphbuilder-where"><s
        <li data-md>
         <p>Let <var>output</var> be the result of <a data-link-type="dfn" href="#create-an-mloperand" id="ref-for-create-an-mloperand②⑧">creating an MLOperand</a> given <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①④②">this</a> and <var>descriptor</var>.</p>
        <li data-md>
-        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤⓪">operator</a> for the "where" operation, given <var>condition</var>, <var>trueValue</var> and <var>falseValue</var>.</p>
+        <p>Let <var>operator</var> be an <a data-link-type="dfn" href="#operators" id="ref-for-operators⑤④">operator</a> for the "where" operation, given <var>condition</var>, <var>trueValue</var>, <var>falseValue</var>, and <var>options</var>.</p>
        <li data-md>
         <p>Set <var>output</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-operator-slot" id="ref-for-dom-mloperand-operator-slot⑤①">[[operator]]</a></code> to <var>operator</var>.</p>
        <li data-md>
@@ -8170,7 +8246,7 @@ <h3 class="heading settled" data-level="8.1" id="algorithms-broadcasting"><span
    </details>
    <p class="algorithm" data-algorithm="bidirectionally broadcastable"> <var>shapeA</var> is <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="bidirectionally-broadcastable">bidirectionally broadcastable</dfn> to <var>shapeB</var> if <a data-link-type="dfn" href="#bidirectionally-broadcasting" id="ref-for-bidirectionally-broadcasting⑥">bidirectionally broadcasting</a> <var>shapeA</var> and <var>shapeB</var> does not result in failure. </p>
    <h3 class="heading settled" data-level="8.2" id="algorithms-casting"><span class="secno">8.2. </span><span class="content">Casting</span><a class="self-link" href="#algorithms-casting"></a></h3>
-   <p>Explicit numeric casting is used in algorithms where parameters passed as <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber①①">MLNumber</a></code> or <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double②③">double</a></code> need to be converted to match the <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①⑥">MLOperandDataType</a></code> of input or output <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪④">MLOperand</a></code>s.</p>
+   <p>Explicit numeric casting is used in algorithms where parameters passed as <code class="idl"><a data-link-type="idl" href="#typedefdef-mlnumber" id="ref-for-typedefdef-mlnumber①①">MLNumber</a></code> or <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double②③">double</a></code> need to be converted to match the <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①⑥">MLOperandDataType</a></code> of input or output <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪⑤">MLOperand</a></code>s.</p>
    <details class="algorithm" data-algorithm="cast" open>
     <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="cast">cast</dfn> a number <var>x</var> to a given <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype①⑦">MLOperandDataType</a></code> <var>dataType</var>, perform the following steps. They return a number. </summary>
     <ol>
@@ -8515,6 +8591,7 @@ <h2 class="no-num no-ref heading settled" id="index"><span class="content">Index
   <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="content">Terms defined by this specification</span><a class="self-link" href="#index-defined-here"></a></h3>
   <ul class="index">
    <li><a href="#dom-mlgraphbuilder-abs">abs(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-abs">abs(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#operator-activation">activation</a><span>, in § 6.1</span>
    <li><a href="#operator-activation">activation function</a><span>, in § 6.1</span>
    <li>
@@ -8526,6 +8603,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
      <li><a href="#dom-mllstmoptions-activations">dict-member for MLLstmOptions</a><span>, in § 7.7.28</span>
     </ul>
    <li><a href="#dom-mlgraphbuilder-add">add(a, b)</a><span>, in § 7.7.12</span>
+   <li><a href="#dom-mlgraphbuilder-add">add(a, b, options)</a><span>, in § 7.7.12</span>
    <li>
     alpha
     <ul>
@@ -8599,8 +8677,10 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#mlgraphbuilder-calculate-resample-output-sizes">calculate resample output sizes</a><span>, in § 7.7.36</span>
    <li><a href="#cast">cast</a><span>, in § 8.2</span>
    <li><a href="#dom-mlgraphbuilder-cast">cast(input, type)</a><span>, in § 7.7.7</span>
+   <li><a href="#dom-mlgraphbuilder-cast">cast(input, type, options)</a><span>, in § 7.7.7</span>
    <li><a href="#dom-mlroundingtype-ceil">"ceil"</a><span>, in § 7.7.32</span>
    <li><a href="#dom-mlgraphbuilder-ceil">ceil(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-ceil">ceil(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#mloperanddescriptor-check-dimensions">check dimensions</a><span>, in § 7.5</span>
    <li><a href="#mlgraphbuilder-check-resample-options">check resample options</a><span>, in § 7.7.36</span>
    <li><a href="#dom-mlgraphbuilder-clamp">clamp(input)</a><span>, in § 7.7.8</span>
@@ -8608,6 +8688,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#computational-graph">computational graph</a><span>, in § 6.1</span>
    <li><a href="#dom-mlcontext-compute">compute(graph, inputs, outputs)</a><span>, in § 7.3.2</span>
    <li><a href="#dom-mlgraphbuilder-concat">concat(inputs, axis)</a><span>, in § 7.7.9</span>
+   <li><a href="#dom-mlgraphbuilder-concat">concat(inputs, axis, options)</a><span>, in § 7.7.9</span>
    <li><a href="#dom-mlpaddingmode-constant">"constant"</a><span>, in § 7.7.31</span>
    <li><a href="#dom-mlgraphbuilder-constant">constant(descriptor, bufferView)</a><span>, in § 7.7.3.1</span>
    <li><a href="#computational-graph-constants">constants</a><span>, in § 6.1</span>
@@ -8629,6 +8710,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mlgraphbuilder-convtranspose2d">convTranspose2d(input, filter, options)</a><span>, in § 7.7.11</span>
    <li><a href="#copy-an-mloperand">copy an MLOperand</a><span>, in § 7.6.1</span>
    <li><a href="#dom-mlgraphbuilder-cos">cos(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-cos">cos(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#dom-mldevicetype-cpu">"cpu"</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mldevicetype-cpu">cpu</a><span>, in § 7.2.1</span>
    <li><a href="#create-a-context">create a context</a><span>, in § 7.2.2</span>
@@ -8670,6 +8752,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
      <li><a href="#dom-mllstmoptions-direction">dict-member for MLLstmOptions</a><span>, in § 7.7.28</span>
     </ul>
    <li><a href="#dom-mlgraphbuilder-div">div(a, b)</a><span>, in § 7.7.12</span>
+   <li><a href="#dom-mlgraphbuilder-div">div(a, b, options)</a><span>, in § 7.7.12</span>
    <li><a href="#dom-mlpaddingmode-edge">"edge"</a><span>, in § 7.7.31</span>
    <li><a href="#mlgraphbuilder-element-wise-binary-op">element-wise-binary-op</a><span>, in § 7.7.12</span>
    <li><a href="#mlgraphbuilder-element-wise-logical-op">element-wise-logical-op</a><span>, in § 7.7.13</span>
@@ -8684,10 +8767,14 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
      <li><a href="#dom-mllayernormalizationoptions-epsilon">dict-member for MLLayerNormalizationOptions</a><span>, in § 7.7.25</span>
     </ul>
    <li><a href="#dom-mlgraphbuilder-equal">equal(a, b)</a><span>, in § 7.7.13</span>
+   <li><a href="#dom-mlgraphbuilder-equal">equal(a, b, options)</a><span>, in § 7.7.13</span>
    <li><a href="#dom-mlgraphbuilder-erf">erf(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-erf">erf(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#execute-graph">execute graph</a><span>, in § 7.3</span>
    <li><a href="#dom-mlgraphbuilder-expand">expand(input, newShape)</a><span>, in § 7.7.16</span>
+   <li><a href="#dom-mlgraphbuilder-expand">expand(input, newShape, options)</a><span>, in § 7.7.16</span>
    <li><a href="#dom-mlgraphbuilder-exp">exp(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-exp">exp(input, options)</a><span>, in § 7.7.14</span>
    <li>
     filterLayout
     <ul>
@@ -8698,17 +8785,21 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mloperanddatatype-float32">"float32"</a><span>, in § 7.5</span>
    <li><a href="#dom-mlroundingtype-floor">"floor"</a><span>, in § 7.7.32</span>
    <li><a href="#dom-mlgraphbuilder-floor">floor(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-floor">floor(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#dom-mlrecurrentnetworkdirection-forward">"forward"</a><span>, in § 7.7.20</span>
    <li><a href="#dom-mlgraphbuilder-gather">gather(input, indices)</a><span>, in § 7.7.17</span>
    <li><a href="#dom-mlgraphbuilder-gather">gather(input, indices, options)</a><span>, in § 7.7.17</span>
    <li><a href="#dom-mlgraphbuilder-gelu">gelu(input)</a><span>, in § 7.7.18</span>
+   <li><a href="#dom-mlgraphbuilder-gelu">gelu(input, options)</a><span>, in § 7.7.18</span>
    <li><a href="#dom-mlgraphbuilder-gemm">gemm(a, b)</a><span>, in § 7.7.19</span>
    <li><a href="#dom-mlgraphbuilder-gemm">gemm(a, b, options)</a><span>, in § 7.7.19</span>
    <li><a href="#dom-mldevicetype-gpu">"gpu"</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mldevicetype-gpu">gpu</a><span>, in § 7.2.1</span>
    <li><a href="#mlgraphbuilder-graph">graph</a><span>, in § 6.1</span>
    <li><a href="#dom-mlgraphbuilder-greater">greater(a, b)</a><span>, in § 7.7.13</span>
+   <li><a href="#dom-mlgraphbuilder-greater">greater(a, b, options)</a><span>, in § 7.7.13</span>
    <li><a href="#dom-mlgraphbuilder-greaterorequal">greaterOrEqual(a, b)</a><span>, in § 7.7.13</span>
+   <li><a href="#dom-mlgraphbuilder-greaterorequal">greaterOrEqual(a, b, options)</a><span>, in § 7.7.13</span>
    <li>
     groups
     <ul>
@@ -8722,12 +8813,14 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mlgraphbuilder-hardsigmoid">hardSigmoid(input)</a><span>, in § 7.7.22</span>
    <li><a href="#dom-mlgraphbuilder-hardsigmoid">hardSigmoid(input, options)</a><span>, in § 7.7.22</span>
    <li><a href="#dom-mlgraphbuilder-hardswish">hardSwish(input)</a><span>, in § 7.7.23</span>
+   <li><a href="#dom-mlgraphbuilder-hardswish">hardSwish(input, options)</a><span>, in § 7.7.23</span>
    <li><a href="#dom-mlgraphbuilder-hasbuilt-slot">[[hasBuilt]]</a><span>, in § 7.7</span>
    <li><a href="#dom-mlpowerpreference-high-performance">"high-performance"</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mlpowerpreference-high-performance">high-performance</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mlconv2dfilteroperandlayout-hwio">"hwio"</a><span>, in § 7.7.10</span>
    <li><a href="#dom-mlconvtranspose2dfilteroperandlayout-hwoi">"hwoi"</a><span>, in § 7.7.11</span>
    <li><a href="#dom-mlgraphbuilder-identity">identity(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-identity">identity(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#dom-mllstmweightlayout-ifgo">"ifgo"</a><span>, in § 7.7.28</span>
    <li><a href="#dom-mlconv2dfilteroperandlayout-ihwo">"ihwo"</a><span>, in § 7.7.10</span>
    <li><a href="#dom-mlgraph-implementation-slot">[[implementation]]</a><span>, in § 7.4</span>
@@ -8768,6 +8861,12 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
     </ul>
    <li><a href="#dom-mlgraphbuilder-l2pool2d">l2Pool2d(input)</a><span>, in § 7.7.32</span>
    <li><a href="#dom-mlgraphbuilder-l2pool2d">l2Pool2d(input, options)</a><span>, in § 7.7.32</span>
+   <li>
+    label
+    <ul>
+     <li><a href="#operator-label">dfn for operator</a><span>, in § 6.1</span>
+     <li><a href="#dom-mloperatoroptions-label">dict-member for MLOperatorOptions</a><span>, in § 7.6</span>
+    </ul>
    <li><a href="#dom-mlgraphbuilder-layernormalization">layerNormalization(input)</a><span>, in § 7.7.25</span>
    <li><a href="#dom-mlgraphbuilder-layernormalization">layerNormalization(input, options)</a><span>, in § 7.7.25</span>
    <li>
@@ -8783,12 +8882,16 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mlgraphbuilder-leakyrelu">leakyRelu(input)</a><span>, in § 7.7.26</span>
    <li><a href="#dom-mlgraphbuilder-leakyrelu">leakyRelu(input, options)</a><span>, in § 7.7.26</span>
    <li><a href="#dom-mlgraphbuilder-lesser">lesser(a, b)</a><span>, in § 7.7.13</span>
+   <li><a href="#dom-mlgraphbuilder-lesser">lesser(a, b, options)</a><span>, in § 7.7.13</span>
    <li><a href="#dom-mlgraphbuilder-lesserorequal">lesserOrEqual(a, b)</a><span>, in § 7.7.13</span>
+   <li><a href="#dom-mlgraphbuilder-lesserorequal">lesserOrEqual(a, b, options)</a><span>, in § 7.7.13</span>
    <li><a href="#dom-mlinterpolationmode-linear">"linear"</a><span>, in § 7.7.36</span>
    <li><a href="#dom-mlgraphbuilder-linear">linear(input)</a><span>, in § 7.7.27</span>
    <li><a href="#dom-mlgraphbuilder-linear">linear(input, options)</a><span>, in § 7.7.27</span>
    <li><a href="#dom-mlgraphbuilder-logicalnot">logicalNot(a)</a><span>, in § 7.7.13</span>
+   <li><a href="#dom-mlgraphbuilder-logicalnot">logicalNot(a, options)</a><span>, in § 7.7.13</span>
    <li><a href="#dom-mlgraphbuilder-log">log(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-log">log(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#dom-mlpowerpreference-low-power">"low-power"</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mlpowerpreference-low-power">low-power</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mlgraphbuilder-lstmcell">lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize)</a><span>, in § 7.7.29</span>
@@ -8796,11 +8899,14 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mlgraphbuilder-lstm">lstm(input, weight, recurrentWeight, steps, hiddenSize)</a><span>, in § 7.7.28</span>
    <li><a href="#dom-mlgraphbuilder-lstm">lstm(input, weight, recurrentWeight, steps, hiddenSize, options)</a><span>, in § 7.7.28</span>
    <li><a href="#dom-mlgraphbuilder-matmul">matmul(a, b)</a><span>, in § 7.7.30</span>
+   <li><a href="#dom-mlgraphbuilder-matmul">matmul(a, b, options)</a><span>, in § 7.7.30</span>
    <li><a href="#dom-mlgraphbuilder-max">max(a, b)</a><span>, in § 7.7.12</span>
+   <li><a href="#dom-mlgraphbuilder-max">max(a, b, options)</a><span>, in § 7.7.12</span>
    <li><a href="#dom-mlgraphbuilder-maxpool2d">maxPool2d(input)</a><span>, in § 7.7.32</span>
    <li><a href="#dom-mlgraphbuilder-maxpool2d">maxPool2d(input, options)</a><span>, in § 7.7.32</span>
    <li><a href="#dom-mlclampoptions-maxvalue">maxValue</a><span>, in § 7.7.8</span>
    <li><a href="#dom-mlgraphbuilder-min">min(a, b)</a><span>, in § 7.7.12</span>
+   <li><a href="#dom-mlgraphbuilder-min">min(a, b, options)</a><span>, in § 7.7.12</span>
    <li><a href="#dom-mlclampoptions-minvalue">minValue</a><span>, in § 7.7.8</span>
    <li><a href="#ml">ML</a><span>, in § 7.2</span>
    <li><a href="#dom-navigatorml-ml">ml</a><span>, in § 7.1</span>
@@ -8840,6 +8946,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#mloperand">MLOperand</a><span>, in § 7.6</span>
    <li><a href="#enumdef-mloperanddatatype">MLOperandDataType</a><span>, in § 7.5</span>
    <li><a href="#dictdef-mloperanddescriptor">MLOperandDescriptor</a><span>, in § 7.5</span>
+   <li><a href="#dictdef-mloperatoroptions">MLOperatorOptions</a><span>, in § 7.6</span>
    <li><a href="#enumdef-mlpaddingmode">MLPaddingMode</a><span>, in § 7.7.31</span>
    <li><a href="#dictdef-mlpadoptions">MLPadOptions</a><span>, in § 7.7.31</span>
    <li><a href="#dictdef-mlpool2doptions">MLPool2dOptions</a><span>, in § 7.7.32</span>
@@ -8860,11 +8967,13 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
      <li><a href="#dom-mlresample2doptions-mode">dict-member for MLResample2dOptions</a><span>, in § 7.7.36</span>
     </ul>
    <li><a href="#dom-mlgraphbuilder-mul">mul(a, b)</a><span>, in § 7.7.12</span>
+   <li><a href="#dom-mlgraphbuilder-mul">mul(a, b, options)</a><span>, in § 7.7.12</span>
    <li><a href="#dom-mloperand-name-slot">[[name]]</a><span>, in § 7.6</span>
    <li><a href="#navigatorml">NavigatorML</a><span>, in § 7.1</span>
    <li><a href="#dom-mlinputoperandlayout-nchw">"nchw"</a><span>, in § 7.5</span>
    <li><a href="#dom-mlinterpolationmode-nearest-neighbor">"nearest-neighbor"</a><span>, in § 7.7.36</span>
    <li><a href="#dom-mlgraphbuilder-neg">neg(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-neg">neg(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#dom-mlinputoperandlayout-nhwc">"nhwc"</a><span>, in § 7.5</span>
    <li><a href="#dom-mldevicetype-npu">"npu"</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mldevicetype-npu">npu</a><span>, in § 7.2.1</span>
@@ -8906,12 +9015,15 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mltransposeoptions-permutation">permutation</a><span>, in § 7.7.45</span>
    <li><a href="#mlgraphbuilder-pooling-op">pooling-op</a><span>, in § 7.7.32</span>
    <li><a href="#dom-mlgraphbuilder-pow">pow(a, b)</a><span>, in § 7.7.12</span>
+   <li><a href="#dom-mlgraphbuilder-pow">pow(a, b, options)</a><span>, in § 7.7.12</span>
    <li><a href="#dom-mlcontext-powerpreference-slot">[[powerPreference]]</a><span>, in § 7.3</span>
    <li><a href="#dom-mlcontextoptions-powerpreference">powerPreference</a><span>, in § 7.2.1</span>
    <li><a href="#dom-mlgraphbuilder-prelu">prelu(input, slope)</a><span>, in § 7.7.33</span>
+   <li><a href="#dom-mlgraphbuilder-prelu">prelu(input, slope, options)</a><span>, in § 7.7.33</span>
    <li><a href="#queue-an-ml-task">queue an ML task</a><span>, in § 6.3</span>
    <li><a href="#mloperand-rank">rank</a><span>, in § 7.6</span>
    <li><a href="#dom-mlgraphbuilder-reciprocal">reciprocal(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-reciprocal">reciprocal(input, options)</a><span>, in § 7.7.14</span>
    <li>
     recurrentBias
     <ul>
@@ -8944,6 +9056,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mlpaddingmode-reflection">"reflection"</a><span>, in § 7.7.31</span>
    <li><a href="#dom-mlrecurrentnetworkactivation-relu">"relu"</a><span>, in § 7.7.20</span>
    <li><a href="#dom-mlgraphbuilder-relu">relu(input)</a><span>, in § 7.7.35</span>
+   <li><a href="#dom-mlgraphbuilder-relu">relu(input, options)</a><span>, in § 7.7.35</span>
    <li><a href="#dom-mlgraphbuilder-resample2d">resample2d(input)</a><span>, in § 7.7.36</span>
    <li><a href="#dom-mlgraphbuilder-resample2d">resample2d(input, options)</a><span>, in § 7.7.36</span>
    <li>
@@ -8953,6 +9066,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
      <li><a href="#dom-mlgruoptions-resetafter">dict-member for MLGruOptions</a><span>, in § 7.7.20</span>
     </ul>
    <li><a href="#dom-mlgraphbuilder-reshape">reshape(input, newShape)</a><span>, in § 7.7.37</span>
+   <li><a href="#dom-mlgraphbuilder-reshape">reshape(input, newShape, options)</a><span>, in § 7.7.37</span>
    <li>
     returnSequence
     <ul>
@@ -8973,15 +9087,22 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mloperand-shape">shape()</a><span>, in § 7.6.3</span>
    <li><a href="#dom-mlrecurrentnetworkactivation-sigmoid">"sigmoid"</a><span>, in § 7.7.20</span>
    <li><a href="#dom-mlgraphbuilder-sigmoid">sigmoid(input)</a><span>, in § 7.7.38</span>
+   <li><a href="#dom-mlgraphbuilder-sigmoid">sigmoid(input, options)</a><span>, in § 7.7.38</span>
    <li><a href="#dom-mlgraphbuilder-sin">sin(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-sin">sin(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#dom-mlresample2doptions-sizes">sizes</a><span>, in § 7.7.36</span>
    <li><a href="#dom-mlgraphbuilder-slice">slice(input, starts, sizes)</a><span>, in § 7.7.39</span>
+   <li><a href="#dom-mlgraphbuilder-slice">slice(input, starts, sizes, options)</a><span>, in § 7.7.39</span>
    <li><a href="#dom-mlgraphbuilder-softmax">softmax(input, axis)</a><span>, in § 7.7.40</span>
+   <li><a href="#dom-mlgraphbuilder-softmax">softmax(input, axis, options)</a><span>, in § 7.7.40</span>
    <li><a href="#dom-mlgraphbuilder-softplus">softplus(input)</a><span>, in § 7.7.41</span>
+   <li><a href="#dom-mlgraphbuilder-softplus">softplus(input, options)</a><span>, in § 7.7.41</span>
    <li><a href="#dom-mlgraphbuilder-softsign">softsign(input)</a><span>, in § 7.7.42</span>
+   <li><a href="#dom-mlgraphbuilder-softsign">softsign(input, options)</a><span>, in § 7.7.42</span>
    <li><a href="#dom-mlgraphbuilder-split">split(input, splits)</a><span>, in § 7.7.43</span>
    <li><a href="#dom-mlgraphbuilder-split">split(input, splits, options)</a><span>, in § 7.7.43</span>
    <li><a href="#dom-mlgraphbuilder-sqrt">sqrt(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-sqrt">sqrt(input, options)</a><span>, in § 7.7.14</span>
    <li>
     strides
     <ul>
@@ -8990,10 +9111,13 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
      <li><a href="#dom-mlpool2doptions-strides">dict-member for MLPool2dOptions</a><span>, in § 7.7.32</span>
     </ul>
    <li><a href="#dom-mlgraphbuilder-sub">sub(a, b)</a><span>, in § 7.7.12</span>
+   <li><a href="#dom-mlgraphbuilder-sub">sub(a, b, options)</a><span>, in § 7.7.12</span>
    <li><a href="#dom-mlpaddingmode-symmetric">"symmetric"</a><span>, in § 7.7.31</span>
    <li><a href="#dom-mlrecurrentnetworkactivation-tanh">"tanh"</a><span>, in § 7.7.20</span>
    <li><a href="#dom-mlgraphbuilder-tanh">tanh(input)</a><span>, in § 7.7.44</span>
+   <li><a href="#dom-mlgraphbuilder-tanh">tanh(input, options)</a><span>, in § 7.7.44</span>
    <li><a href="#dom-mlgraphbuilder-tan">tan(input)</a><span>, in § 7.7.14</span>
+   <li><a href="#dom-mlgraphbuilder-tan">tan(input, options)</a><span>, in § 7.7.14</span>
    <li><a href="#mlnamedarraybufferviews-transfer">transfer</a><span>, in § 7.3.1</span>
    <li><a href="#dom-mlgraphbuilder-transpose">transpose(input)</a><span>, in § 7.7.45</span>
    <li><a href="#dom-mlgraphbuilder-transpose">transpose(input, options)</a><span>, in § 7.7.45</span>
@@ -9012,6 +9136,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#context-type-webgpu">webgpu</a><span>, in § 7.3</span>
    <li><a href="#webnn-feature">webnn-feature</a><span>, in § 6.4</span>
    <li><a href="#dom-mlgraphbuilder-where">where(condition, trueValue, falseValue)</a><span>, in § 7.7.47</span>
+   <li><a href="#dom-mlgraphbuilder-where">where(condition, trueValue, falseValue, options)</a><span>, in § 7.7.47</span>
    <li><a href="#dom-mlpool2doptions-windowdimensions">windowDimensions</a><span>, in § 7.7.32</span>
    <li><a href="#dom-mlgruweightlayout-zrn">"zrn"</a><span>, in § 7.7.20</span>
   </ul>
@@ -9116,6 +9241,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-elsewhere"><span cla
      <li><span class="dfn-paneled" id="5372cca8">boolean</span>
      <li><span class="dfn-paneled" id="495737df">byte length</span>
      <li><span class="dfn-paneled" id="8c800cdf">double</span>
+     <li><span class="dfn-paneled" id="cd787c3f">exception</span>
      <li><span class="dfn-paneled" id="eec1be2d">float</span>
      <li><span class="dfn-paneled" id="7b05fe24">get a copy of the bytes held by the buffer source</span>
      <li><span class="dfn-paneled" id="f8de33a3">long</span>
@@ -9311,6 +9437,10 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mloperand-shape"><c- g>shape</c-></a>();
 };
 
+<c- b>dictionary</c-> <a href="#dictdef-mloperatoroptions"><code><c- g>MLOperatorOptions</c-></code></a> {
+  <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-USVString"><c- b>USVString</c-></a> <a class="idl-code" data-default="&quot;&quot;" data-link-type="dict-member" data-type="USVString" href="#dom-mloperatoroptions-label"><c- g>label</c-></a> = "";
+};
+
 <c- b>typedef</c-> (<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-bigint"><c- b>bigint</c-></a> <c- b>or</c-> <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unrestricted-double"><c- b>unrestricted</c-> <c- b>double</c-></a>) <a class="idl-code" data-link-type="typedef" href="#typedefdef-mlnumber"><c- g>MLNumber</c-></a>;
 
 <c- b>typedef</c-> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-record"><c- b>record</c-></a>&lt;<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-USVString"><c- b>USVString</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a>> <a href="#typedefdef-mlnamedoperands"><code><c- g>MLNamedOperands</c-></code></a>;
@@ -9333,7 +9463,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-promise"><c- b>Promise</c-></a>&lt;<a data-link-type="idl-name" href="#mlgraph"><c- n>MLGraph</c-></a>> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-build"><c- g>build</c-></a>(<a data-link-type="idl-name" href="#typedefdef-mlnamedoperands"><c- n>MLNamedOperands</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-build-outputs-outputs"><c- g>outputs</c-></a>);
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlargminmaxoptions"><code><c- g>MLArgMinMaxOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlargminmaxoptions"><code><c- g>MLArgMinMaxOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlargminmaxoptions-keepdimensions"><c- g>keepDimensions</c-></a> = <c- b>false</c->;
   <a data-link-type="idl-name" href="#enumdef-mloperanddatatype"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-default="&quot;int32&quot;" data-link-type="dict-member" data-type="MLOperandDataType" href="#dom-mlargminmaxoptions-outputdatatype"><c- g>outputDataType</c-></a> = "int32";
 };
@@ -9345,7 +9475,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlargminmaxoptions"><c- n>MLArgMinMaxOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-argmin-input-axis-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlbatchnormalizationoptions"><code><c- g>MLBatchNormalizationOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlbatchnormalizationoptions"><code><c- g>MLBatchNormalizationOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlbatchnormalizationoptions-scale"><c- g>scale</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlbatchnormalizationoptions-bias"><c- g>bias</c-></a>;
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlbatchnormalizationoptions-axis"><c- g>axis</c-></a> = 1;
@@ -9358,10 +9488,12 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cast"><c- g>cast</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#enumdef-mloperanddatatype"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-type"><c- g>type</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cast"><c- g>cast</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-options-input"><c- g>input</c-></a>,
+                 <a data-link-type="idl-name" href="#enumdef-mloperanddatatype"><c- n>MLOperandDataType</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-options-type"><c- g>type</c-></a>,
+                 <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-cast-input-type-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlclampoptions"><code><c- g>MLClampOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlclampoptions"><code><c- g>MLClampOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#typedefdef-mlnumber"><c- n>MLNumber</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLNumber" href="#dom-mlclampoptions-minvalue"><c- g>minValue</c-></a>;
   <a data-link-type="idl-name" href="#typedefdef-mlnumber"><c- n>MLNumber</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLNumber" href="#dom-mlclampoptions-maxvalue"><c- g>maxValue</c-></a>;
 };
@@ -9371,7 +9503,9 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-concat"><c- g>concat</c-></a>(<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-inputs"><c- g>inputs</c-></a>, [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-axis"><c- g>axis</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-concat"><c- g>concat</c-></a>(<a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-options-inputs"><c- g>inputs</c-></a>,
+                   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-options-axis"><c- g>axis</c-></a>,
+                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-concat-inputs-axis-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>enum</c-> <a href="#enumdef-mlconv2dfilteroperandlayout"><code><c- g>MLConv2dFilterOperandLayout</c-></code></a> {
@@ -9381,7 +9515,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a href="#dom-mlconv2dfilteroperandlayout-ihwo"><code><c- s>"ihwo"</c-></code></a>
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlconv2doptions"><code><c- g>MLConv2dOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlconv2doptions"><code><c- g>MLConv2dOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconv2doptions-padding"><c- g>padding</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconv2doptions-strides"><c- g>strides</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconv2doptions-dilations"><c- g>dilations</c-></a>;
@@ -9403,7 +9537,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a href="#dom-mlconvtranspose2dfilteroperandlayout-ohwi"><code><c- s>"ohwi"</c-></code></a>
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlconvtranspose2doptions"><code><c- g>MLConvTranspose2dOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlconvtranspose2doptions"><code><c- g>MLConvTranspose2dOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconvtranspose2doptions-padding"><c- g>padding</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconvtranspose2doptions-strides"><c- g>strides</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlconvtranspose2doptions-dilations"><c- g>dilations</c-></a>;
@@ -9421,41 +9555,51 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-add"><c- g>add</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sub"><c- g>sub</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-mul"><c- g>mul</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-div"><c- g>div</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-max"><c- g>max</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-min"><c- g>min</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-pow"><c- g>pow</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-b"><c- g>b</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-add"><c- g>add</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sub"><c- g>sub</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-mul"><c- g>mul</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-div"><c- g>div</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-max"><c- g>max</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-min"><c- g>min</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-pow"><c- g>pow</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-add-a-b-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-equal"><c- g>equal</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greater"><c- g>greater</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greaterorequal"><c- g>greaterOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesser"><c- g>lesser</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesserorequal"><c- g>lesserOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-b"><c- g>b</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-logicalnot"><c- g>logicalNot</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-a"><c- g>a</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-equal"><c- g>equal</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a"><c- g>a</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b"><c- g>b</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greater"><c- g>greater</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a"><c- g>a</c-></a>,
+                    <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b"><c- g>b</c-></a>,
+                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-greaterorequal"><c- g>greaterOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a"><c- g>a</c-></a>,
+                           <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b"><c- g>b</c-></a>,
+                           <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesser"><c- g>lesser</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a"><c- g>a</c-></a>,
+                   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b"><c- g>b</c-></a>,
+                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-lesserorequal"><c- g>lesserOrEqual</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a"><c- g>a</c-></a>,
+                          <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-b"><c- g>b</c-></a>,
+                          <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-logicalnot"><c- g>logicalNot</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-a"><c- g>a</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-equal-a-b-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-abs"><c- g>abs</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-ceil"><c- g>ceil</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cos"><c- g>cos</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-erf"><c- g>erf</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-exp"><c- g>exp</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-floor"><c- g>floor</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-identity"><c- g>identity</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-log"><c- g>log</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-neg"><c- g>neg</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reciprocal"><c- g>reciprocal</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sin"><c- g>sin</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sqrt"><c- g>sqrt</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tan"><c- g>tan</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-input"><c- g>input</c-></a>);
-};
-
-<c- b>dictionary</c-> <a href="#dictdef-mleluoptions"><code><c- g>MLEluOptions</c-></code></a> {
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-abs"><c- g>abs</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-ceil"><c- g>ceil</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-cos"><c- g>cos</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-erf"><c- g>erf</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-exp"><c- g>exp</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-floor"><c- g>floor</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-identity"><c- g>identity</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-log"><c- g>log</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-neg"><c- g>neg</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reciprocal"><c- g>reciprocal</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sin"><c- g>sin</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sqrt"><c- g>sqrt</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tan"><c- g>tan</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-abs-input-options-options"><c- g>options</c-></a> = {});
+};
+
+<c- b>dictionary</c-> <a href="#dictdef-mleluoptions"><code><c- g>MLEluOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="double" href="#dom-mleluoptions-alpha"><c- g>alpha</c-></a> = 1;
 };
 
@@ -9464,10 +9608,12 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-expand"><c- g>expand</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-input"><c- g>input</c-></a>, <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-newshape"><c- g>newShape</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-expand"><c- g>expand</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-options-input"><c- g>input</c-></a>,
+                   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-options-newshape"><c- g>newShape</c-></a>,
+                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-expand-input-newshape-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlgatheroptions"><code><c- g>MLGatherOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlgatheroptions"><code><c- g>MLGatherOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlgatheroptions-axis"><c- g>axis</c-></a> = 0;
 };
 
@@ -9478,10 +9624,10 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gelu"><c- g>gelu</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gelu-input-input"><c- g>input</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-gelu"><c- g>gelu</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gelu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gelu-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlgemmoptions"><code><c- g>MLGemmOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlgemmoptions"><code><c- g>MLGemmOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgemmoptions-c"><c- g>c</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="1.0" data-link-type="dict-member" data-type="double" href="#dom-mlgemmoptions-alpha"><c- g>alpha</c-></a> = 1.0;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="1.0" data-link-type="dict-member" data-type="double" href="#dom-mlgemmoptions-beta"><c- g>beta</c-></a> = 1.0;
@@ -9510,7 +9656,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a href="#dom-mlrecurrentnetworkdirection-both"><code><c- s>"both"</c-></code></a>
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlgruoptions"><code><c- g>MLGruOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlgruoptions"><code><c- g>MLGruOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-bias"><c- g>bias</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-recurrentbias"><c- g>recurrentBias</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgruoptions-initialhiddenstate"><c- g>initialHiddenState</c-></a>;
@@ -9530,7 +9676,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
                           <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlgruoptions"><c- n>MLGruOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlgrucelloptions"><code><c- g>MLGruCellOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlgrucelloptions"><code><c- g>MLGruCellOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgrucelloptions-bias"><c- g>bias</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlgrucelloptions-recurrentbias"><c- g>recurrentBias</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean"><c- b>boolean</c-></a> <a class="idl-code" data-default="true" data-link-type="dict-member" data-type="boolean" href="#dom-mlgrucelloptions-resetafter"><c- g>resetAfter</c-></a> = <c- b>true</c->;
@@ -9547,7 +9693,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
                     <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlgrucelloptions"><c- n>MLGruCellOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlhardsigmoidoptions"><code><c- g>MLHardSigmoidOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlhardsigmoidoptions"><code><c- g>MLHardSigmoidOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="0.2" data-link-type="dict-member" data-type="double" href="#dom-mlhardsigmoidoptions-alpha"><c- g>alpha</c-></a> = 0.2;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="0.5" data-link-type="dict-member" data-type="double" href="#dom-mlhardsigmoidoptions-beta"><c- g>beta</c-></a> = 0.5;
 };
@@ -9557,10 +9703,10 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-hardswish"><c- g>hardSwish</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardswish-input-input"><c- g>input</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-hardswish"><c- g>hardSwish</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardswish-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-hardswish-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlinstancenormalizationoptions"><code><c- g>MLInstanceNormalizationOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlinstancenormalizationoptions"><code><c- g>MLInstanceNormalizationOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlinstancenormalizationoptions-scale"><c- g>scale</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mlinstancenormalizationoptions-bias"><c- g>bias</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="1e-5" data-link-type="dict-member" data-type="double" href="#dom-mlinstancenormalizationoptions-epsilon"><c- g>epsilon</c-></a> = 1e-5;
@@ -9572,7 +9718,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
                                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlinstancenormalizationoptions"><c- n>MLInstanceNormalizationOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-instancenormalization-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mllayernormalizationoptions"><code><c- g>MLLayerNormalizationOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mllayernormalizationoptions"><code><c- g>MLLayerNormalizationOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllayernormalizationoptions-scale"><c- g>scale</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllayernormalizationoptions-bias"><c- g>bias</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mllayernormalizationoptions-axes"><c- g>axes</c-></a>;
@@ -9584,7 +9730,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
                                <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mllayernormalizationoptions"><c- n>MLLayerNormalizationOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-layernormalization-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlleakyreluoptions"><code><c- g>MLLeakyReluOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlleakyreluoptions"><code><c- g>MLLeakyReluOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="0.01" data-link-type="dict-member" data-type="double" href="#dom-mlleakyreluoptions-alpha"><c- g>alpha</c-></a> = 0.01;
 };
 
@@ -9592,7 +9738,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-leakyrelu"><c- g>leakyRelu</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-leakyrelu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mlleakyreluoptions"><c- n>MLLeakyReluOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-leakyrelu-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mllinearoptions"><code><c- g>MLLinearOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mllinearoptions"><code><c- g>MLLinearOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="1" data-link-type="dict-member" data-type="double" href="#dom-mllinearoptions-alpha"><c- g>alpha</c-></a> = 1;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-double"><c- b>double</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="double" href="#dom-mllinearoptions-beta"><c- g>beta</c-></a> = 0;
 };
@@ -9606,7 +9752,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a href="#dom-mllstmweightlayout-ifgo"><code><c- s>"ifgo"</c-></code></a>  // input-forget-cell-output gate ordering
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mllstmoptions"><code><c- g>MLLstmOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mllstmoptions"><code><c- g>MLLstmOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-bias"><c- g>bias</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-recurrentbias"><c- g>recurrentBias</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmoptions-peepholeweight"><c- g>peepholeWeight</c-></a>;
@@ -9627,7 +9773,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
                            <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mllstmoptions"><c- n>MLLstmOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mllstmcelloptions"><code><c- g>MLLstmCellOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mllstmcelloptions"><code><c- g>MLLstmCellOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-bias"><c- g>bias</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-recurrentbias"><c- g>recurrentBias</c-></a>;
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="dict-member" data-type="MLOperand" href="#dom-mllstmcelloptions-peepholeweight"><c- g>peepholeWeight</c-></a>;
@@ -9646,7 +9792,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-matmul"><c- g>matmul</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-b"><c- g>b</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-matmul"><c- g>matmul</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-options-a"><c- g>a</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-options-b"><c- g>b</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-matmul-a-b-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>enum</c-> <a href="#enumdef-mlpaddingmode"><code><c- g>MLPaddingMode</c-></code></a> {
@@ -9656,7 +9802,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a href="#dom-mlpaddingmode-symmetric"><code><c- s>"symmetric"</c-></code></a>
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlpadoptions"><code><c- g>MLPadOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlpadoptions"><code><c- g>MLPadOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#enumdef-mlpaddingmode"><c- n>MLPaddingMode</c-></a> <a class="idl-code" data-default="&quot;constant&quot;" data-link-type="dict-member" data-type="MLPaddingMode" href="#dom-mlpadoptions-mode"><c- g>mode</c-></a> = "constant";
   <a data-link-type="idl-name" href="#typedefdef-mlnumber"><c- n>MLNumber</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="MLNumber" href="#dom-mlpadoptions-value"><c- g>value</c-></a> = 0;
 };
@@ -9673,7 +9819,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a href="#dom-mlroundingtype-ceil"><code><c- s>"ceil"</c-></code></a>
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlpool2doptions"><code><c- g>MLPool2dOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlpool2doptions"><code><c- g>MLPool2dOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlpool2doptions-windowdimensions"><c- g>windowDimensions</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlpool2doptions-padding"><c- g>padding</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlpool2doptions-strides"><c- g>strides</c-></a>;
@@ -9690,10 +9836,12 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-prelu"><c- g>prelu</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-input"><c- g>input</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-slope"><c- g>slope</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-prelu"><c- g>prelu</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-options-input"><c- g>input</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-options-slope"><c- g>slope</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-prelu-input-slope-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlreduceoptions"><code><c- g>MLReduceOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlreduceoptions"><code><c- g>MLReduceOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlreduceoptions-axes"><c- g>axes</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlreduceoptions-keepdimensions"><c- g>keepDimensions</c-></a> = <c- b>false</c->;
 };
@@ -9712,7 +9860,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-relu"><c- g>relu</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-relu-input-input"><c- g>input</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-relu"><c- g>relu</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-relu-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-relu-input-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>enum</c-> <a href="#enumdef-mlinterpolationmode"><code><c- g>MLInterpolationMode</c-></code></a> {
@@ -9720,7 +9868,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a href="#dom-mlinterpolationmode-linear"><code><c- s>"linear"</c-></code></a>
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlresample2doptions"><code><c- g>MLResample2dOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlresample2doptions"><code><c- g>MLResample2dOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="idl-name" href="#enumdef-mlinterpolationmode"><c- n>MLInterpolationMode</c-></a> <a class="idl-code" data-default="&quot;nearest-neighbor&quot;" data-link-type="dict-member" data-type="MLInterpolationMode" href="#dom-mlresample2doptions-mode"><c- g>mode</c-></a> = "nearest-neighbor";
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;<a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-float"><c- b>float</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<float>" href="#dom-mlresample2doptions-scales"><c- g>scales</c-></a>;
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlresample2doptions-sizes"><c- g>sizes</c-></a>;
@@ -9732,32 +9880,37 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reshape"><c- g>reshape</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-input"><c- g>input</c-></a>, <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-newshape"><c- g>newShape</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-reshape"><c- g>reshape</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-options-input"><c- g>input</c-></a>,
+                    <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-options-newshape"><c- g>newShape</c-></a>,
+                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-reshape-input-newshape-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sigmoid"><c- g>sigmoid</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-sigmoid-input-input"><c- g>input</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-sigmoid"><c- g>sigmoid</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-sigmoid-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-sigmoid-input-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-slice"><c- g>slice</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-input"><c- g>input</c-></a>,
-                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-starts"><c- g>starts</c-></a>,
-                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-sizes"><c- g>sizes</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-slice"><c- g>slice</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input"><c- g>input</c-></a>,
+                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-starts"><c- g>starts</c-></a>,
+                  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes"><c- g>sizes</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softmax"><c- g>softmax</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-input"><c- g>input</c-></a>, <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-axis"><c- g>axis</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softmax"><c- g>softmax</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-options-input"><c- g>input</c-></a>,
+                    <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-options-axis"><c- g>axis</c-></a>,
+                    <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softmax-input-axis-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softplus"><c- g>softplus</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softplus-input-input"><c- g>input</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softplus"><c- g>softplus</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softplus-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softplus-input-options-options"><c- g>options</c-></a> = {});
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softsign"><c- g>softsign</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softsign-input-input"><c- g>input</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-softsign"><c- g>softsign</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softsign-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-softsign-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mlsplitoptions"><code><c- g>MLSplitOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mlsplitoptions"><code><c- g>MLSplitOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="unsigned long" href="#dom-mlsplitoptions-axis"><c- g>axis</c-></a> = 0;
 };
 
@@ -9769,10 +9922,10 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tanh"><c- g>tanh</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-tanh-input-input"><c- g>input</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-tanh"><c- g>tanh</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-tanh-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-tanh-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mltransposeoptions"><code><c- g>MLTransposeOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mltransposeoptions"><code><c- g>MLTransposeOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mltransposeoptions-permutation"><c- g>permutation</c-></a>;
 };
 
@@ -9780,7 +9933,7 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
   <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-transpose"><c- g>transpose</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-transpose-input-options-input"><c- g>input</c-></a>, <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mltransposeoptions"><c- n>MLTransposeOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-transpose-input-options-options"><c- g>options</c-></a> = {});
 };
 
-<c- b>dictionary</c-> <a href="#dictdef-mltriangularoptions"><code><c- g>MLTriangularOptions</c-></code></a> {
+<c- b>dictionary</c-> <a href="#dictdef-mltriangularoptions"><code><c- g>MLTriangularOptions</c-></code></a> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> {
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean"><c- b>boolean</c-></a> <a class="idl-code" data-default="true" data-link-type="dict-member" data-type="boolean" href="#dom-mltriangularoptions-upper"><c- g>upper</c-></a> = <c- b>true</c->;
   [<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-long"><c- b>long</c-></a> <a class="idl-code" data-default="0" data-link-type="dict-member" data-type="long" href="#dom-mltriangularoptions-diagonal"><c- g>diagonal</c-></a> = 0;
 };
@@ -9790,7 +9943,10 @@ <h2 class="no-num no-ref heading settled" id="idl-index"><span class="content">I
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-where"><c- g>where</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-condition"><c- g>condition</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-truevalue"><c- g>trueValue</c-></a>, <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-falsevalue"><c- g>falseValue</c-></a>);
+  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-where"><c- g>where</c-></a>(<a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition"><c- g>condition</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue"><c- g>trueValue</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue"><c- g>falseValue</c-></a>,
+                  <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-options"><c- g>options</c-></a> = {});
 };
 
 </pre>
@@ -10057,7 +10213,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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hardSigmoid"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u2462"},{"id":"ref-for-mloperand\u2461\u2462\u2463"},{"id":"ref-for-mloperand\u2461\u2462\u2464"},{"id":"ref-for-mloperand\u2461\u2462\u2465"}],"title":"7.7.23. hardSwish"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u2466"},{"id":"ref-for-mloperand\u2461\u2462\u2467"},{"id":"ref-for-mloperand\u2461\u2462\u2468"},{"id":"ref-for-mloperand\u2461\u2463\u24ea"},{"id":"ref-for-mloperand\u2461\u2463\u2460"},{"id":"ref-for-mloperand\u2461\u2463\u2461"},{"id":"ref-for-mloperand\u2461\u2463\u2462"},{"id":"ref-for-mloperand\u2461\u2463\u2463"}],"title":"7.7.24. 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linear"},{"refs":[{"id":"ref-for-mloperand\u2461\u2465\u2460"},{"id":"ref-for-mloperand\u2461\u2465\u2461"},{"id":"ref-for-mloperand\u2461\u2465\u2462"},{"id":"ref-for-mloperand\u2461\u2465\u2463"},{"id":"ref-for-mloperand\u2461\u2465\u2464"},{"id":"ref-for-mloperand\u2461\u2465\u2465"},{"id":"ref-for-mloperand\u2461\u2465\u2466"},{"id":"ref-for-mloperand\u2461\u2465\u2467"},{"id":"ref-for-mloperand\u2461\u2465\u2468"},{"id":"ref-for-mloperand\u2461\u2466\u24ea"},{"id":"ref-for-mloperand\u2461\u2466\u2460"},{"id":"ref-for-mloperand\u2461\u2466\u2461"},{"id":"ref-for-mloperand\u2461\u2466\u2462"},{"id":"ref-for-mloperand\u2461\u2466\u2463"},{"id":"ref-for-mloperand\u2461\u2466\u2464"},{"id":"ref-for-mloperand\u2461\u2466\u2465"},{"id":"ref-for-mloperand\u2461\u2466\u2466"},{"id":"ref-for-mloperand\u2461\u2466\u2467"}],"title":"7.7.28. lstm"},{"refs":[{"id":"ref-for-mloperand\u2461\u2466\u2468"},{"id":"ref-for-mloperand\u2461\u2467\u24ea"},{"id":"ref-for-mloperand\u2461\u2467\u2460"},{"id":"ref-for-mloperand\u2461\u2467\u2461"},{"id":"ref-for-mloperand\u2461\u2467\u2462"},{"id":"ref-for-mloperand\u2461\u2467\u2463"},{"id":"ref-for-mloperand\u2461\u2467\u2464"},{"id":"ref-for-mloperand\u2461\u2467\u2465"},{"id":"ref-for-mloperand\u2461\u2467\u2466"},{"id":"ref-for-mloperand\u2461\u2467\u2467"},{"id":"ref-for-mloperand\u2461\u2467\u2468"},{"id":"ref-for-mloperand\u2461\u2468\u24ea"},{"id":"ref-for-mloperand\u2461\u2468\u2460"},{"id":"ref-for-mloperand\u2461\u2468\u2461"},{"id":"ref-for-mloperand\u2461\u2468\u2462"},{"id":"ref-for-mloperand\u2461\u2468\u2463"},{"id":"ref-for-mloperand\u2461\u2468\u2464"},{"id":"ref-for-mloperand\u2461\u2468\u2465"}],"title":"7.7.29. 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Casting"}],"url":"#mloperand"},
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MLNumber"},{"refs":[{"id":"ref-for-mloperand\u2462\u2466"}],"title":"7.6.2. dataType()"},{"refs":[{"id":"ref-for-mloperand\u2462\u2467"}],"title":"7.6.3. shape()"},{"refs":[{"id":"ref-for-mloperand\u2462\u2468"},{"id":"ref-for-mloperand\u2463\u24ea"},{"id":"ref-for-mloperand\u2463\u2460"},{"id":"ref-for-mloperand\u2463\u2461"}],"title":"7.7. MLGraphBuilder interface"},{"refs":[{"id":"ref-for-mloperand\u2463\u2462"},{"id":"ref-for-mloperand\u2463\u2463"},{"id":"ref-for-mloperand\u2463\u2464"}],"title":"7.7.2. input operands"},{"refs":[{"id":"ref-for-mloperand\u2463\u2465"}],"title":"7.7.3. constant operands"},{"refs":[{"id":"ref-for-mloperand\u2463\u2466"},{"id":"ref-for-mloperand\u2463\u2467"}],"title":"7.7.3.1. constant(descriptor, bufferView)"},{"refs":[{"id":"ref-for-mloperand\u2463\u2468"},{"id":"ref-for-mloperand\u2464\u24ea"}],"title":"7.7.3.2. constant(type, value)"},{"refs":[{"id":"ref-for-mloperand\u2464\u2460"}],"title":"7.7.4. build method"},{"refs":[{"id":"ref-for-mloperand\u2464\u2461"},{"id":"ref-for-mloperand\u2464\u2462"},{"id":"ref-for-mloperand\u2464\u2463"},{"id":"ref-for-mloperand\u2464\u2464"},{"id":"ref-for-mloperand\u2464\u2465"},{"id":"ref-for-mloperand\u2464\u2466"},{"id":"ref-for-mloperand\u2464\u2467"}],"title":"7.7.5. argMin/argMax operations"},{"refs":[{"id":"ref-for-mloperand\u2464\u2468"},{"id":"ref-for-mloperand\u2465\u24ea"},{"id":"ref-for-mloperand\u2465\u2460"},{"id":"ref-for-mloperand\u2465\u2461"},{"id":"ref-for-mloperand\u2465\u2462"},{"id":"ref-for-mloperand\u2465\u2463"},{"id":"ref-for-mloperand\u2465\u2464"},{"id":"ref-for-mloperand\u2465\u2465"},{"id":"ref-for-mloperand\u2465\u2466"},{"id":"ref-for-mloperand\u2465\u2467"},{"id":"ref-for-mloperand\u2465\u2468"},{"id":"ref-for-mloperand\u2466\u24ea"}],"title":"7.7.6. batchNormalization"},{"refs":[{"id":"ref-for-mloperand\u2466\u2460"},{"id":"ref-for-mloperand\u2466\u2461"},{"id":"ref-for-mloperand\u2466\u2462"},{"id":"ref-for-mloperand\u2466\u2463"}],"title":"7.7.7. cast"},{"refs":[{"id":"ref-for-mloperand\u2466\u2464"},{"id":"ref-for-mloperand\u2466\u2465"},{"id":"ref-for-mloperand\u2466\u2466"},{"id":"ref-for-mloperand\u2466\u2467"}],"title":"7.7.8. clamp"},{"refs":[{"id":"ref-for-mloperand\u2466\u2468"},{"id":"ref-for-mloperand\u2467\u24ea"},{"id":"ref-for-mloperand\u2467\u2460"},{"id":"ref-for-mloperand\u2467\u2461"}],"title":"7.7.9. concat"},{"refs":[{"id":"ref-for-mloperand\u2467\u2462"},{"id":"ref-for-mloperand\u2467\u2463"},{"id":"ref-for-mloperand\u2467\u2464"},{"id":"ref-for-mloperand\u2467\u2465"},{"id":"ref-for-mloperand\u2467\u2466"},{"id":"ref-for-mloperand\u2467\u2467"},{"id":"ref-for-mloperand\u2467\u2468"},{"id":"ref-for-mloperand\u2468\u24ea"}],"title":"7.7.10. conv2d"},{"refs":[{"id":"ref-for-mloperand\u2468\u2460"},{"id":"ref-for-mloperand\u2468\u2461"},{"id":"ref-for-mloperand\u2468\u2462"},{"id":"ref-for-mloperand\u2468\u2463"},{"id":"ref-for-mloperand\u2468\u2464"},{"id":"ref-for-mloperand\u2468\u2465"},{"id":"ref-for-mloperand\u2468\u2466"},{"id":"ref-for-mloperand\u2468\u2467"}],"title":"7.7.11. convTranspose2d"},{"refs":[{"id":"ref-for-mloperand\u2468\u2468"},{"id":"ref-for-mloperand\u2460\u24ea\u24ea"},{"id":"ref-for-mloperand\u2460\u24ea\u2460"},{"id":"ref-for-mloperand\u2460\u24ea\u2461"},{"id":"ref-for-mloperand\u2460\u24ea\u2462"},{"id":"ref-for-mloperand\u2460\u24ea\u2463"},{"id":"ref-for-mloperand\u2460\u24ea\u2464"},{"id":"ref-for-mloperand\u2460\u24ea\u2465"},{"id":"ref-for-mloperand\u2460\u24ea\u2466"},{"id":"ref-for-mloperand\u2460\u24ea\u2467"},{"id":"ref-for-mloperand\u2460\u24ea\u2468"},{"id":"ref-for-mloperand\u2460\u2460\u24ea"},{"id":"ref-for-mloperand\u2460\u2460\u2460"},{"id":"ref-for-mloperand\u2460\u2460\u2461"},{"id":"ref-for-mloperand\u2460\u2460\u2462"},{"id":"ref-for-mloperand\u2460\u2460\u2463"},{"id":"ref-for-mloperand\u2460\u2460\u2464"},{"id":"ref-for-mloperand\u2460\u2460\u2465"},{"id":"ref-for-mloperand\u2460\u2460\u2466"},{"id":"ref-for-mloperand\u2460\u2460\u2467"},{"id":"ref-for-mloperand\u2460\u2460\u2468"},{"id":"ref-for-mloperand\u2460\u2461\u24ea"},{"id":"ref-for-mloperand\u2460\u2461\u2460"},{"id":"ref-for-mloperand\u2460\u2461\u2461"},{"id":"ref-for-mloperand\u2460\u2461\u2462"},{"id":"ref-for-mloperand\u2460\u2461\u2463"}],"title":"7.7.12. Element-wise binary operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2461\u2464"},{"id":"ref-for-mloperand\u2460\u2461\u2465"},{"id":"ref-for-mloperand\u2460\u2461\u2466"},{"id":"ref-for-mloperand\u2460\u2461\u2467"},{"id":"ref-for-mloperand\u2460\u2461\u2468"},{"id":"ref-for-mloperand\u2460\u2462\u24ea"},{"id":"ref-for-mloperand\u2460\u2462\u2460"},{"id":"ref-for-mloperand\u2460\u2462\u2461"},{"id":"ref-for-mloperand\u2460\u2462\u2462"},{"id":"ref-for-mloperand\u2460\u2462\u2463"},{"id":"ref-for-mloperand\u2460\u2462\u2464"},{"id":"ref-for-mloperand\u2460\u2462\u2465"},{"id":"ref-for-mloperand\u2460\u2462\u2466"},{"id":"ref-for-mloperand\u2460\u2462\u2467"},{"id":"ref-for-mloperand\u2460\u2462\u2468"},{"id":"ref-for-mloperand\u2460\u2463\u24ea"},{"id":"ref-for-mloperand\u2460\u2463\u2460"},{"id":"ref-for-mloperand\u2460\u2463\u2461"},{"id":"ref-for-mloperand\u2460\u2463\u2462"},{"id":"ref-for-mloperand\u2460\u2463\u2463"},{"id":"ref-for-mloperand\u2460\u2463\u2464"},{"id":"ref-for-mloperand\u2460\u2463\u2465"}],"title":"7.7.13. Element-wise logical operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2463\u2466"},{"id":"ref-for-mloperand\u2460\u2463\u2467"},{"id":"ref-for-mloperand\u2460\u2463\u2468"},{"id":"ref-for-mloperand\u2460\u2464\u24ea"},{"id":"ref-for-mloperand\u2460\u2464\u2460"},{"id":"ref-for-mloperand\u2460\u2464\u2461"},{"id":"ref-for-mloperand\u2460\u2464\u2462"},{"id":"ref-for-mloperand\u2460\u2464\u2463"},{"id":"ref-for-mloperand\u2460\u2464\u2464"},{"id":"ref-for-mloperand\u2460\u2464\u2465"},{"id":"ref-for-mloperand\u2460\u2464\u2466"},{"id":"ref-for-mloperand\u2460\u2464\u2467"},{"id":"ref-for-mloperand\u2460\u2464\u2468"},{"id":"ref-for-mloperand\u2460\u2465\u24ea"},{"id":"ref-for-mloperand\u2460\u2465\u2460"},{"id":"ref-for-mloperand\u2460\u2465\u2461"},{"id":"ref-for-mloperand\u2460\u2465\u2462"},{"id":"ref-for-mloperand\u2460\u2465\u2463"},{"id":"ref-for-mloperand\u2460\u2465\u2464"},{"id":"ref-for-mloperand\u2460\u2465\u2465"},{"id":"ref-for-mloperand\u2460\u2465\u2466"},{"id":"ref-for-mloperand\u2460\u2465\u2467"},{"id":"ref-for-mloperand\u2460\u2465\u2468"},{"id":"ref-for-mloperand\u2460\u2466\u24ea"},{"id":"ref-for-mloperand\u2460\u2466\u2460"},{"id":"ref-for-mloperand\u2460\u2466\u2461"},{"id":"ref-for-mloperand\u2460\u2466\u2462"},{"id":"ref-for-mloperand\u2460\u2466\u2463"},{"id":"ref-for-mloperand\u2460\u2466\u2464"}],"title":"7.7.14. Element-wise unary operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2466\u2465"},{"id":"ref-for-mloperand\u2460\u2466\u2466"},{"id":"ref-for-mloperand\u2460\u2466\u2467"},{"id":"ref-for-mloperand\u2460\u2466\u2468"}],"title":"7.7.15. elu"},{"refs":[{"id":"ref-for-mloperand\u2460\u2467\u24ea"},{"id":"ref-for-mloperand\u2460\u2467\u2460"},{"id":"ref-for-mloperand\u2460\u2467\u2461"},{"id":"ref-for-mloperand\u2460\u2467\u2462"}],"title":"7.7.16. expand"},{"refs":[{"id":"ref-for-mloperand\u2460\u2467\u2463"},{"id":"ref-for-mloperand\u2460\u2467\u2464"},{"id":"ref-for-mloperand\u2460\u2467\u2465"},{"id":"ref-for-mloperand\u2460\u2467\u2466"},{"id":"ref-for-mloperand\u2460\u2467\u2467"},{"id":"ref-for-mloperand\u2460\u2467\u2468"}],"title":"7.7.17. gather"},{"refs":[{"id":"ref-for-mloperand\u2460\u2468\u24ea"},{"id":"ref-for-mloperand\u2460\u2468\u2460"},{"id":"ref-for-mloperand\u2460\u2468\u2461"},{"id":"ref-for-mloperand\u2460\u2468\u2462"}],"title":"7.7.18. gelu"},{"refs":[{"id":"ref-for-mloperand\u2460\u2468\u2463"},{"id":"ref-for-mloperand\u2460\u2468\u2464"},{"id":"ref-for-mloperand\u2460\u2468\u2465"},{"id":"ref-for-mloperand\u2460\u2468\u2466"},{"id":"ref-for-mloperand\u2460\u2468\u2467"},{"id":"ref-for-mloperand\u2460\u2468\u2468"},{"id":"ref-for-mloperand\u2461\u24ea\u24ea"},{"id":"ref-for-mloperand\u2461\u24ea\u2460"}],"title":"7.7.19. gemm"},{"refs":[{"id":"ref-for-mloperand\u2461\u24ea\u2461"},{"id":"ref-for-mloperand\u2461\u24ea\u2462"},{"id":"ref-for-mloperand\u2461\u24ea\u2463"},{"id":"ref-for-mloperand\u2461\u24ea\u2464"},{"id":"ref-for-mloperand\u2461\u24ea\u2465"},{"id":"ref-for-mloperand\u2461\u24ea\u2466"},{"id":"ref-for-mloperand\u2461\u24ea\u2467"},{"id":"ref-for-mloperand\u2461\u24ea\u2468"},{"id":"ref-for-mloperand\u2461\u2460\u24ea"},{"id":"ref-for-mloperand\u2461\u2460\u2460"},{"id":"ref-for-mloperand\u2461\u2460\u2461"},{"id":"ref-for-mloperand\u2461\u2460\u2462"},{"id":"ref-for-mloperand\u2461\u2460\u2463"},{"id":"ref-for-mloperand\u2461\u2460\u2464"}],"title":"7.7.20. gru"},{"refs":[{"id":"ref-for-mloperand\u2461\u2460\u2465"},{"id":"ref-for-mloperand\u2461\u2460\u2466"},{"id":"ref-for-mloperand\u2461\u2460\u2467"},{"id":"ref-for-mloperand\u2461\u2460\u2468"},{"id":"ref-for-mloperand\u2461\u2461\u24ea"},{"id":"ref-for-mloperand\u2461\u2461\u2460"},{"id":"ref-for-mloperand\u2461\u2461\u2461"},{"id":"ref-for-mloperand\u2461\u2461\u2462"},{"id":"ref-for-mloperand\u2461\u2461\u2463"},{"id":"ref-for-mloperand\u2461\u2461\u2464"},{"id":"ref-for-mloperand\u2461\u2461\u2465"},{"id":"ref-for-mloperand\u2461\u2461\u2466"},{"id":"ref-for-mloperand\u2461\u2461\u2467"},{"id":"ref-for-mloperand\u2461\u2461\u2468"}],"title":"7.7.21. gruCell"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u24ea"},{"id":"ref-for-mloperand\u2461\u2462\u2460"},{"id":"ref-for-mloperand\u2461\u2462\u2461"},{"id":"ref-for-mloperand\u2461\u2462\u2462"}],"title":"7.7.22. hardSigmoid"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u2463"},{"id":"ref-for-mloperand\u2461\u2462\u2464"},{"id":"ref-for-mloperand\u2461\u2462\u2465"},{"id":"ref-for-mloperand\u2461\u2462\u2466"}],"title":"7.7.23. hardSwish"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u2467"},{"id":"ref-for-mloperand\u2461\u2462\u2468"},{"id":"ref-for-mloperand\u2461\u2463\u24ea"},{"id":"ref-for-mloperand\u2461\u2463\u2460"},{"id":"ref-for-mloperand\u2461\u2463\u2461"},{"id":"ref-for-mloperand\u2461\u2463\u2462"},{"id":"ref-for-mloperand\u2461\u2463\u2463"},{"id":"ref-for-mloperand\u2461\u2463\u2464"}],"title":"7.7.24. instanceNormalization"},{"refs":[{"id":"ref-for-mloperand\u2461\u2463\u2465"},{"id":"ref-for-mloperand\u2461\u2463\u2466"},{"id":"ref-for-mloperand\u2461\u2463\u2467"},{"id":"ref-for-mloperand\u2461\u2463\u2468"},{"id":"ref-for-mloperand\u2461\u2464\u24ea"},{"id":"ref-for-mloperand\u2461\u2464\u2460"},{"id":"ref-for-mloperand\u2461\u2464\u2461"},{"id":"ref-for-mloperand\u2461\u2464\u2462"}],"title":"7.7.25. layerNormalization"},{"refs":[{"id":"ref-for-mloperand\u2461\u2464\u2463"},{"id":"ref-for-mloperand\u2461\u2464\u2464"},{"id":"ref-for-mloperand\u2461\u2464\u2465"},{"id":"ref-for-mloperand\u2461\u2464\u2466"}],"title":"7.7.26. leakyRelu"},{"refs":[{"id":"ref-for-mloperand\u2461\u2464\u2467"},{"id":"ref-for-mloperand\u2461\u2464\u2468"},{"id":"ref-for-mloperand\u2461\u2465\u24ea"},{"id":"ref-for-mloperand\u2461\u2465\u2460"}],"title":"7.7.27. linear"},{"refs":[{"id":"ref-for-mloperand\u2461\u2465\u2461"},{"id":"ref-for-mloperand\u2461\u2465\u2462"},{"id":"ref-for-mloperand\u2461\u2465\u2463"},{"id":"ref-for-mloperand\u2461\u2465\u2464"},{"id":"ref-for-mloperand\u2461\u2465\u2465"},{"id":"ref-for-mloperand\u2461\u2465\u2466"},{"id":"ref-for-mloperand\u2461\u2465\u2467"},{"id":"ref-for-mloperand\u2461\u2465\u2468"},{"id":"ref-for-mloperand\u2461\u2466\u24ea"},{"id":"ref-for-mloperand\u2461\u2466\u2460"},{"id":"ref-for-mloperand\u2461\u2466\u2461"},{"id":"ref-for-mloperand\u2461\u2466\u2462"},{"id":"ref-for-mloperand\u2461\u2466\u2463"},{"id":"ref-for-mloperand\u2461\u2466\u2464"},{"id":"ref-for-mloperand\u2461\u2466\u2465"},{"id":"ref-for-mloperand\u2461\u2466\u2466"},{"id":"ref-for-mloperand\u2461\u2466\u2467"},{"id":"ref-for-mloperand\u2461\u2466\u2468"}],"title":"7.7.28. lstm"},{"refs":[{"id":"ref-for-mloperand\u2461\u2467\u24ea"},{"id":"ref-for-mloperand\u2461\u2467\u2460"},{"id":"ref-for-mloperand\u2461\u2467\u2461"},{"id":"ref-for-mloperand\u2461\u2467\u2462"},{"id":"ref-for-mloperand\u2461\u2467\u2463"},{"id":"ref-for-mloperand\u2461\u2467\u2464"},{"id":"ref-for-mloperand\u2461\u2467\u2465"},{"id":"ref-for-mloperand\u2461\u2467\u2466"},{"id":"ref-for-mloperand\u2461\u2467\u2467"},{"id":"ref-for-mloperand\u2461\u2467\u2468"},{"id":"ref-for-mloperand\u2461\u2468\u24ea"},{"id":"ref-for-mloperand\u2461\u2468\u2460"},{"id":"ref-for-mloperand\u2461\u2468\u2461"},{"id":"ref-for-mloperand\u2461\u2468\u2462"},{"id":"ref-for-mloperand\u2461\u2468\u2463"},{"id":"ref-for-mloperand\u2461\u2468\u2464"},{"id":"ref-for-mloperand\u2461\u2468\u2465"},{"id":"ref-for-mloperand\u2461\u2468\u2466"}],"title":"7.7.29. lstmCell"},{"refs":[{"id":"ref-for-mloperand\u2461\u2468\u2467"},{"id":"ref-for-mloperand\u2461\u2468\u2468"},{"id":"ref-for-mloperand\u2462\u24ea\u24ea"},{"id":"ref-for-mloperand\u2462\u24ea\u2460"},{"id":"ref-for-mloperand\u2462\u24ea\u2461"},{"id":"ref-for-mloperand\u2462\u24ea\u2462"},{"id":"ref-for-mloperand\u2462\u24ea\u2463"},{"id":"ref-for-mloperand\u2462\u24ea\u2464"}],"title":"7.7.30. matmul"},{"refs":[{"id":"ref-for-mloperand\u2462\u24ea\u2465"},{"id":"ref-for-mloperand\u2462\u24ea\u2466"},{"id":"ref-for-mloperand\u2462\u24ea\u2467"},{"id":"ref-for-mloperand\u2462\u24ea\u2468"}],"title":"7.7.31. pad"},{"refs":[{"id":"ref-for-mloperand\u2462\u2460\u24ea"},{"id":"ref-for-mloperand\u2462\u2460\u2460"},{"id":"ref-for-mloperand\u2462\u2460\u2461"},{"id":"ref-for-mloperand\u2462\u2460\u2462"},{"id":"ref-for-mloperand\u2462\u2460\u2463"},{"id":"ref-for-mloperand\u2462\u2460\u2464"},{"id":"ref-for-mloperand\u2462\u2460\u2465"},{"id":"ref-for-mloperand\u2462\u2460\u2466"},{"id":"ref-for-mloperand\u2462\u2460\u2467"}],"title":"7.7.32. Pooling operations"},{"refs":[{"id":"ref-for-mloperand\u2462\u2460\u2468"},{"id":"ref-for-mloperand\u2462\u2461\u24ea"},{"id":"ref-for-mloperand\u2462\u2461\u2460"},{"id":"ref-for-mloperand\u2462\u2461\u2461"},{"id":"ref-for-mloperand\u2462\u2461\u2462"},{"id":"ref-for-mloperand\u2462\u2461\u2463"}],"title":"7.7.33. prelu"},{"refs":[{"id":"ref-for-mloperand\u2462\u2461\u2464"},{"id":"ref-for-mloperand\u2462\u2461\u2465"},{"id":"ref-for-mloperand\u2462\u2461\u2466"},{"id":"ref-for-mloperand\u2462\u2461\u2467"},{"id":"ref-for-mloperand\u2462\u2461\u2468"},{"id":"ref-for-mloperand\u2462\u2462\u24ea"},{"id":"ref-for-mloperand\u2462\u2462\u2460"},{"id":"ref-for-mloperand\u2462\u2462\u2461"},{"id":"ref-for-mloperand\u2462\u2462\u2462"},{"id":"ref-for-mloperand\u2462\u2462\u2463"},{"id":"ref-for-mloperand\u2462\u2462\u2464"},{"id":"ref-for-mloperand\u2462\u2462\u2465"},{"id":"ref-for-mloperand\u2462\u2462\u2466"},{"id":"ref-for-mloperand\u2462\u2462\u2467"},{"id":"ref-for-mloperand\u2462\u2462\u2468"},{"id":"ref-for-mloperand\u2462\u2463\u24ea"},{"id":"ref-for-mloperand\u2462\u2463\u2460"},{"id":"ref-for-mloperand\u2462\u2463\u2461"},{"id":"ref-for-mloperand\u2462\u2463\u2462"},{"id":"ref-for-mloperand\u2462\u2463\u2463"},{"id":"ref-for-mloperand\u2462\u2463\u2464"},{"id":"ref-for-mloperand\u2462\u2463\u2465"},{"id":"ref-for-mloperand\u2462\u2463\u2466"}],"title":"7.7.34. 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Casting"}],"url":"#mloperand"},
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@@ -11052,11 +11232,13 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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@@ -11072,16 +11254,18 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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@@ -11098,32 +11282,35 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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-"#dom-mlgraphbuilder-gelu-input-input": {"export":true,"for_":["MLGraphBuilder/gelu(input)"],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"input","type":"argument","url":"#dom-mlgraphbuilder-gelu-input-input"},
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@@ -11141,8 +11328,9 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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 "#dom-mlgraphbuilder-hasbuilt-slot": {"export":true,"for_":["MLGraphBuilder"],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"[[hasBuilt]]","type":"attribute","url":"#dom-mlgraphbuilder-hasbuilt-slot"},
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@@ -11158,13 +11346,13 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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@@ -11180,25 +11368,27 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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@@ -11212,46 +11402,55 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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 "https://webidl.spec.whatwg.org/#dfn-numeric-type": {"export":true,"for_":[],"level":"1","normative":true,"shortname":"webidl","spec":"webidl","status":"current","text":"numeric types","type":"dfn","url":"https://webidl.spec.whatwg.org/#dfn-numeric-type"},
 "https://webidl.spec.whatwg.org/#dfn-throw": {"export":true,"for_":["exception"],"level":"1","normative":true,"shortname":"webidl","spec":"webidl","status":"current","text":"throw","type":"dfn","url":"https://webidl.spec.whatwg.org/#dfn-throw"},