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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="2024-07-25">25 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="2024-07-27">27 July 2024</time></p>
    <details open>
     <summary>More details about this document</summary>
     <div data-fill-with="spec-metadata">
@@ -3447,8 +3447,7 @@ <h4 class="heading settled" data-level="7.7.11" id="api-mlgraphbuilder-convtrans
    </details>
    <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 element-wise binary operations will be broadcasted according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</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>
+   <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>);
@@ -3501,7 +3500,7 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
      <li data-md>
       <p>If <var>a</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype③⓪">dataType</a> is not equal to <var>b</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype③①">dataType</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑦⑥">TypeError</a></code>.</p>
      <li data-md>
-      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting-the-shapes" id="ref-for-bidirectionally-broadcasting-the-shapes">bidirectionally broadcasting the shapes</a> <var>a</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②③">shape</a> and <var>b</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②④">shape</a>.</p>
+      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting" id="ref-for-bidirectionally-broadcasting">bidirectionally broadcasting</a> <var>a</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②③">shape</a> and <var>b</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②④">shape</a>.</p>
       <ol>
        <li data-md>
         <p>If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑧②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑦⑦">TypeError</a></code>.</p>
@@ -3622,7 +3621,7 @@ <h4 class="heading settled" data-level="7.7.12" id="api-mlgraphbuilder-binary"><
    </details>
    <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>The input tensor will be broadcasted according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</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.</p>
+   <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>);
@@ -3685,7 +3684,7 @@ <h4 class="heading settled" data-level="7.7.13" id="api-mlgraphbuilder-logical">
        <li data-md>
         <p>If <var>a</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype③④">dataType</a> is not equal to <var>b</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype③⑤">dataType</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑧①">TypeError</a></code>.</p>
        <li data-md>
-        <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting-the-shapes" id="ref-for-bidirectionally-broadcasting-the-shapes①">bidirectionally broadcasting the shapes</a> <var>a</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②⑥">shape</a> and <var>b</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②⑦">shape</a>. If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑧②">TypeError</a></code>.</p>
+        <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting" id="ref-for-bidirectionally-broadcasting①">bidirectionally broadcasting</a> <var>a</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②⑥">shape</a> and <var>b</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②⑦">shape</a>. If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⓪②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑧②">TypeError</a></code>.</p>
       </ol>
      <li data-md>
       <p>Let <var>descriptor</var> be the result of <a data-link-type="dfn" href="#create-an-mloperanddescriptor" id="ref-for-create-an-mloperanddescriptor⑥">creating an MLOperandDescriptor</a> given <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8⑥">"uint8"</a></code> and <var>outputShape</var>.</p>
@@ -4123,7 +4122,7 @@ <h4 class="heading settled" data-level="7.7.15" id="api-mlgraphbuilder-elu"><spa
     </details>
    </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 dimensions must have the size of 1 or match the sizes of the corresponding output dimensions according to the new shape. 
+    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>);
 };
@@ -4146,7 +4145,7 @@ <h4 class="heading settled" data-level="7.7.16" id="api-mlgraphbuilder-expand"><
      <li data-md>
       <p>If <a data-link-type="dfn" href="#mlgraphbuilder-validate-operand" id="ref-for-mlgraphbuilder-validate-operand①③">validating operand</a> with <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this⑥②">this</a> and <var>input</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①④⑧">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑧⑦">TypeError</a></code>.</p>
      <li data-md>
-      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#unidirectionally-broadcasting-the-shapes" id="ref-for-unidirectionally-broadcasting-the-shapes">unidirectionally broadcasting the shapes</a> <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②⑧">shape</a> and <var>newShape</var>.</p>
+      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#unidirectionally-broadcasting" id="ref-for-unidirectionally-broadcasting">unidirectionally broadcasting</a> <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape②⑧">shape</a> and <var>newShape</var>.</p>
       <ol>
        <li data-md>
         <p>If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①④⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑧⑧">TypeError</a></code>.</p>
@@ -4394,7 +4393,7 @@ <h4 class="heading settled" data-level="7.7.18" id="api-mlgraphbuilder-gelu-meth
     </details>
    </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-broadcastable">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. 
+    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>;
   <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;
@@ -4411,7 +4410,7 @@ <h4 class="heading settled" data-level="7.7.19" id="api-mlgraphbuilder-gemm"><sp
    <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>
     <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-broadcastable①">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>
+     <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>
     <dd data-md>
      <p>A multiplier for the first input.</p>
@@ -4468,7 +4467,7 @@ <h4 class="heading settled" data-level="7.7.19" id="api-mlgraphbuilder-gemm"><sp
       <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c②">c</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists②⑥">exists</a>:</p>
       <ol>
        <li data-md>
-        <p>If it is not <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable②">unidirectionally broadcastable</a> to the shape « <var>shapeA</var>[0], <var>shapeB</var>[1] », then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑥③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑨⑨">TypeError</a></code>.</p>
+        <p>If it is not <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable③">unidirectionally broadcastable</a> to the shape « <var>shapeA</var>[0], <var>shapeB</var>[1] », then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑥③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑨⑨">TypeError</a></code>.</p>
        <li data-md>
         <p>If its <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype④⑧">dataType</a> is not equal to <var>a</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype④⑨">dataType</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑥④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⓪⓪">TypeError</a></code>.</p>
       </ol>
@@ -6275,7 +6274,7 @@ <h4 class="heading settled" data-level="7.7.30" id="api-mlgraphbuilder-matmul"><
       <p>If both <em>a</em> and <em>b</em> are 2-dimensional, they are multiplied like conventional
 matrices and produce a 2-dimensional tensor as the output.</p>
      <li data-md>
-      <p>If either <em>a</em> or <em>b</em> is <code>N</code>-dimensional where <code>N > 2</code>, it is treated as a stack of matrices with dimensions corresponding to the last two indices. The matrix multiplication will be broadcasted accordingly by following the <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The output is a <code>N</code>-dimensional tensor whose rank is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③④">rank</a> of the input tensors. For each dimension, except the last two, of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
+      <p>If either <em>a</em> or <em>b</em> is <code>N</code>-dimensional where <code>N > 2</code>, it is treated as a stack of matrices with dimensions corresponding to the last two indices. The matrix multiplication 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 shapes of <em>a</em> and <em>b</em>, except the last two dimensions, must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable②">bidirectionally broadcastable</a>. The output is a <code>N</code>-dimensional tensor whose rank is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③④">rank</a> of the input tensors. For each dimension, except the last two, of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
     </ul>
    </div>
    <details class="algorithm" data-algorithm="calculate matmul output sizes" data-algorithm-for="MLGraphBuilder" open>
@@ -6306,7 +6305,7 @@ <h4 class="heading settled" data-level="7.7.30" id="api-mlgraphbuilder-matmul"><
      <li data-md>
       <p>Let <var>batchShapeB</var> be a <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-clone" id="ref-for-list-clone①⑤">clone</a> of <var>shapeB</var> with the spatial dimensions (last 2 items) <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-remove" id="ref-for-list-remove①">removed</a>.</p>
      <li data-md>
-      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting-the-shapes" id="ref-for-bidirectionally-broadcasting-the-shapes②">bidirectionally broadcasting the shapes</a> <var>batchShapeA</var> and <var>batchShapeB</var>. If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②⑥⑤">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑨①">TypeError</a></code>.</p>
+      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting" id="ref-for-bidirectionally-broadcasting②">bidirectionally broadcasting</a> <var>batchShapeA</var> and <var>batchShapeB</var>. If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②⑥⑤">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑨①">TypeError</a></code>.</p>
      <li data-md>
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-append" id="ref-for-list-append">Append</a> « <var>rowsA</var>, <var>colsB</var> » to <var>outputShape</var>.</p>
      <li data-md>
@@ -6787,6 +6786,7 @@ <h5 class="heading settled" data-level="7.7.32.3" id="api-mlgraphbuilder-pool2d-
     Calculate the maximum value for patches of a feature map, and use it to create a pooled feature map. See <a href="#api-mlgraphbuilder-pool2d">§ 7.7.32 Pooling operations</a> for more detail. 
    <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>);
 };
@@ -6797,7 +6797,7 @@ <h4 class="heading settled" data-level="7.7.33" id="api-mlgraphbuilder-prelu"><s
      <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>
      <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 is either the same as, or <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable③">unidirectionally broadcastable</a> to the shape of input tensor <em>input</em>.</p>
+      <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>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
@@ -6817,7 +6817,7 @@ <h4 class="heading settled" data-level="7.7.33" id="api-mlgraphbuilder-prelu"><s
      <li data-md>
       <p>If <var>slope</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①②⑤">dataType</a> is not equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①②⑥">dataType</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②⑨⑧">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②①③">TypeError</a></code>.</p>
      <li data-md>
-      <p>Let <var>outputShape</var> be to the result of <a data-link-type="dfn" href="#unidirectionally-broadcasting-the-shapes" id="ref-for-unidirectionally-broadcasting-the-shapes①">unidirectionally broadcasting the shapes</a> <var>slope</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑧⓪">shape</a> and <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑧①">shape</a>.</p>
+      <p>Let <var>outputShape</var> be to the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting" id="ref-for-bidirectionally-broadcasting③">bidirectionally broadcasting</a> <var>slope</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑧⓪">shape</a> and <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑧①">shape</a>.</p>
       <ol>
        <li data-md>
         <p>If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②⑨⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②①④">TypeError</a></code>.</p>
@@ -6878,7 +6878,7 @@ <h4 class="heading settled" data-level="7.7.34" id="api-mlgraphbuilder-reduce"><
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLReduceOptions" data-dfn-type="dict-member" data-export id="dom-mlreduceoptions-axes"><code>axes</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
     <dd data-md>
-     <p>The dimensions to reduce. The values in the list must be in the range [0, N-1] where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④③">rank</a> of the input tensor. If not present, all dimensions are reduced. If empty, no dimensions are reduced, and the shape of the output tensor is the same as the shape of the input tensor.</p>
+     <p>The dimensions to reduce. The values in the list must be in the range [0, N-1] where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑤">rank</a> of the input tensor. If not present, all dimensions are reduced. If empty, no dimensions are reduced, and the shape of the output tensor is the same as the shape of the input tensor.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLReduceOptions" data-dfn-type="dict-member" data-export id="dom-mlreduceoptions-keepdimensions"><code>keepDimensions</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①⑥">boolean</a>, defaulting to <code>false</code></span>
     <dd data-md>
      <p>If true, the output has the same rank as the input, setting any reduced dimensions to size 1.</p>
@@ -7291,7 +7291,7 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
      <li data-md>
       <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①③①">dataType</a> is not <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑤">"float32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④③">"float16"</a></code>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③②⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②①">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④④">rank</a> is not 4, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②②">TypeError</a></code>.</p>
+      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑥">rank</a> is not 4, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②②">TypeError</a></code>.</p>
      <li data-md>
       <p>If <a data-link-type="dfn" href="#mlgraphbuilder-check-resample-options" id="ref-for-mlgraphbuilder-check-resample-options">checking resample options</a> given <var>options</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②③">TypeError</a></code>.</p>
      <li data-md>
@@ -7444,9 +7444,9 @@ <h4 class="heading settled" data-level="7.7.39" id="api-mlgraphbuilder-slice"><s
      <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>
      <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-rank④⑤">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)" 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>
      <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-rank④⑥">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)" 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>
     </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>
    </div>
@@ -7460,9 +7460,9 @@ <h4 class="heading settled" data-level="7.7.39" id="api-mlgraphbuilder-slice"><s
      <li data-md>
       <p>If any of <var>sizes</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-item" id="ref-for-list-item⑥">items</a> are 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③①">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>starts</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑧">size</a> and <var>sizes</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑨">size</a> are not both equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑦">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③②">TypeError</a></code>.</p>
+      <p>If <var>starts</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑧">size</a> and <var>sizes</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑨">size</a> are not both equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑨">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③②">TypeError</a></code>.</p>
      <li data-md>
-      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①③">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①①">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑧">rank</a>, exclusive:</p>
+      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①③">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①①">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⓪">rank</a>, exclusive:</p>
       <ol>
        <li data-md>
         <p>If <var>sizes</var>[<var>index</var>] is 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③③">TypeError</a></code>.</p>
@@ -7521,7 +7521,7 @@ <h4 class="heading settled" data-level="7.7.40" id="api-mlgraphbuilder-softmax-m
      <li data-md>
       <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①③③">dataType</a> is not <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑦">"float32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④⑤">"float16"</a></code>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③⑦">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>axis</var> is greater than or equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑨">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③⑧">TypeError</a></code>.</p>
+      <p>If <var>axis</var> is greater than or equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤①">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③⑧">TypeError</a></code>.</p>
      <li data-md>
       <p><em>Make graph connections:</em></p>
       <ol>
@@ -7697,7 +7697,7 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLSplitOptions" data-dfn-type="dict-member" data-export id="dom-mlsplitoptions-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-long⑦⓪">unsigned long</a>, defaulting to <code>0</code></span>
     <dd data-md>
-     <p>The dimension along which to split. 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-rank⑤⓪">rank</a> of the input tensor.</p>
+     <p>The dimension along which to split. 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-rank⑤②">rank</a> of the input tensor.</p>
    </dl>
    <details class="algorithm" data-algorithm="split(input, splits, 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="split(input, splits, options)|split(input, splits)" id="dom-mlgraphbuilder-split"><code>split(<var>input</var>, <var>splits</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -7709,7 +7709,7 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
      <li data-md>
       <p>Let <var>axis</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis①">axis</a></code>.</p>
      <li data-md>
-      <p>If <var>axis</var> is greater than or equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤①">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②④④">TypeError</a></code>.</p>
+      <p>If <var>axis</var> is greater than or equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤③">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②④④">TypeError</a></code>.</p>
      <li data-md>
       <p>If <var>splits</var> is an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑦①">unsigned long</a></code>:</p>
       <ol>
@@ -7858,8 +7858,8 @@ <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLTransposeOptions" data-dfn-type="dict-member" data-export id="dom-mltransposeoptions-permutation"><code>permutation</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
     <dd data-md>
      <p>The values used to permute the output shape.
-The default is [N-1, ..., 0], where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤②">rank</a> of the input tensor, e.g. [2,1,0] for a 3-D tensor.
-These default values cause the output to become a transposed tensor of the input. When specified, the number of values must be the same as the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤③">rank</a> of the input tensor, and the values must be within the range from 0 to N-1 with no duplicates.</p>
+The default is [N-1, ..., 0], where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤④">rank</a> of the input tensor, e.g. [2,1,0] for a 3-D tensor.
+These default values cause the output to become a transposed tensor of the input. When specified, the number of values must be the same as the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑤">rank</a> of the input tensor, and the values must be within the range from 0 to N-1 with no duplicates.</p>
    </dl>
    <div>
      <strong>Arguments:</strong> 
@@ -7884,9 +7884,9 @@ <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose
       <p>Otherwise if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation③">permutation</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑨">exists</a>:</p>
       <ol>
        <li data-md>
-        <p>If its <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④④">size</a> is not equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤④">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑧">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤①">TypeError</a></code>.</p>
+        <p>If its <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④④">size</a> is not equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑥">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑧">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤①">TypeError</a></code>.</p>
        <li data-md>
-        <p>If its values are not in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①③">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑤">rank</a> exclusive, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤②">TypeError</a></code>.</p>
+        <p>If its values are not in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①③">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑦">rank</a> exclusive, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤②">TypeError</a></code>.</p>
        <li data-md>
         <p>If it contains duplicate values, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤③">TypeError</a></code>.</p>
       </ol>
@@ -7946,7 +7946,7 @@ <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangula
      <li data-md>
       <p>If <a data-link-type="dfn" href="#mlgraphbuilder-validate-operand" id="ref-for-mlgraphbuilder-validate-operand④③">validating operand</a> with <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①③⑨">this</a> and <var>input</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤④">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑥">rank</a> is less than 2, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤⑤">TypeError</a></code>.</p>
+      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑧">rank</a> is less than 2, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤⑤">TypeError</a></code>.</p>
      <li data-md>
       <p><em>Make graph connections:</em></p>
       <ol>
@@ -8025,8 +8025,7 @@ <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangula
    </div>
    <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 input tensors must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable">bidirectionally broadcastable</a> and will be broadcasted according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a> to the final output shape. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑦">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑧">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>
+   <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>);
 };
@@ -8055,13 +8054,13 @@ <h4 class="heading settled" data-level="7.7.47" id="api-mlgraphbuilder-where"><s
      <li data-md>
       <p>If <var>trueValue</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①③⑧">dataType</a> is not equal to <var>falseValue</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①③⑨">dataType</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦⑦">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤⑧">TypeError</a></code>.</p>
      <li data-md>
-      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting-the-shapes" id="ref-for-bidirectionally-broadcasting-the-shapes③">bidirectionally broadcasting the shapes</a> <var>trueValue</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨②">shape</a> and <var>falseValue</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨③">shape</a>.</p>
+      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting" id="ref-for-bidirectionally-broadcasting④">bidirectionally broadcasting</a> <var>trueValue</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨②">shape</a> and <var>falseValue</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨③">shape</a>.</p>
       <ol>
        <li data-md>
         <p>If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦⑧">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤⑨">TypeError</a></code>.</p>
       </ol>
      <li data-md>
-      <p>Set <var>outputShape</var> to the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting-the-shapes" id="ref-for-bidirectionally-broadcasting-the-shapes④">bidirectionally broadcasting the shapes</a> <var>condition</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨④">shape</a> and |outputShape].</p>
+      <p>Set <var>outputShape</var> to the result of <a data-link-type="dfn" href="#bidirectionally-broadcasting" id="ref-for-bidirectionally-broadcasting⑤">bidirectionally broadcasting</a> <var>condition</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨④">shape</a> and |outputShape].</p>
       <ol>
        <li data-md>
         <p>If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑥⓪">TypeError</a></code>.</p>
@@ -8102,8 +8101,8 @@ <h4 class="heading settled" data-level="7.7.47" id="api-mlgraphbuilder-where"><s
    <h2 class="heading settled" data-level="8" id="algorithms"><span class="secno">8. </span><span class="content">Algorithms</span><a class="self-link" href="#algorithms"></a></h2>
    <h3 class="heading settled" data-level="8.1" id="algorithms-broadcasting"><span class="secno">8.1. </span><span class="content">Broadcasting</span><a class="self-link" href="#algorithms-broadcasting"></a></h3>
    <p>Broadcasting refers to how operations treat tensors with different shapes, and follow the precedent set by <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>.</p>
-   <details class="algorithm" data-algorithm="unidirectionally broadcasting the shapes" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-lt="unidirectionally broadcasting the shapes" data-noexport id="unidirectionally-broadcasting-the-shapes">unidirectionally broadcast the shapes</dfn> <var>shapeFrom</var> and <var>shapeTo</var>, perform the following steps. <var>shapeFrom</var> and <var>shapeTo</var> are <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑥">lists</a> of positive integers, representing the dimensions of tensors, and the steps return a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑦">list</a> of positive integers, or failure. </summary>
+   <details class="algorithm" data-algorithm="unidirectionally broadcasting" open>
+    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-lt="unidirectionally broadcasting" data-noexport id="unidirectionally-broadcasting">unidirectionally broadcast the shapes</dfn> <var>shapeFrom</var> and <var>shapeTo</var>, perform the following steps. <var>shapeFrom</var> and <var>shapeTo</var> are <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑥">lists</a> of positive integers, representing the dimensions of tensors, and the steps return a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑦">list</a> of positive integers, or failure. </summary>
     <ol>
      <li data-md>
       <p>Let <var>sizeFrom</var> be <var>shapeFrom</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④⑤">size</a>.</p>
@@ -8133,9 +8132,9 @@ <h3 class="heading settled" data-level="8.1" id="algorithms-broadcasting"><span
       <p>Return <var>outputShape</var>.</p>
     </ol>
    </details>
-   <p class="algorithm" data-algorithm="unidirectionally broadcastable"> <var>shapeFrom</var> is <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="unidirectionally-broadcastable">unidirectionally broadcastable</dfn> to <var>shapeTo</var> if <a data-link-type="dfn" href="#unidirectionally-broadcasting-the-shapes" id="ref-for-unidirectionally-broadcasting-the-shapes②">unidirectionally broadcasting the shapes</a> <var>shapeFrom</var> and <var>shapeTo</var> does not result in failure. </p>
-   <details class="algorithm" data-algorithm="bidirectionally broadcasting the shapes" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-lt="bidirectionally broadcasting the shapes" data-noexport id="bidirectionally-broadcasting-the-shapes">bidirectionally broadcast the shapes</dfn> <var>shapeA</var> and <var>shapeB</var>, perform the following steps. <var>shapeA</var> and <var>shapeB</var> are <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑨">lists</a> of positive integers, representing the dimensions of tensors, and the steps return a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list⑤⓪">list</a> of positive integers, or failure. </summary>
+   <p class="algorithm" data-algorithm="unidirectionally broadcastable"> <var>shapeFrom</var> is <dfn class="dfn-paneled" data-dfn-type="dfn" data-noexport id="unidirectionally-broadcastable">unidirectionally broadcastable</dfn> to <var>shapeTo</var> if <a data-link-type="dfn" href="#unidirectionally-broadcasting" id="ref-for-unidirectionally-broadcasting①">unidirectionally broadcasting</a> <var>shapeFrom</var> and <var>shapeTo</var> does not result in failure. </p>
+   <details class="algorithm" data-algorithm="bidirectionally broadcasting" open>
+    <summary> To <dfn class="dfn-paneled" data-dfn-type="dfn" data-lt="bidirectionally broadcasting" data-noexport id="bidirectionally-broadcasting">bidirectionally broadcast the shapes</dfn> <var>shapeA</var> and <var>shapeB</var>, perform the following steps. <var>shapeA</var> and <var>shapeB</var> are <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑨">lists</a> of positive integers, representing the dimensions of tensors, and the steps return a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list⑤⓪">list</a> of positive integers, or failure. </summary>
     <ol>
      <li data-md>
       <p>Let <var>sizeA</var> be <var>shapeA</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④⑧">size</a>.</p>
@@ -8169,7 +8168,7 @@ <h3 class="heading settled" data-level="8.1" id="algorithms-broadcasting"><span
       <p>Return <var>outputShape</var>.</p>
     </ol>
    </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-the-shapes" id="ref-for-bidirectionally-broadcasting-the-shapes⑤">bidirectionally broadcasting the shapes</a> <var>shapeA</var> and <var>shapeB</var> does not result in failure. </p>
+   <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>
    <details class="algorithm" data-algorithm="cast" open>
@@ -8582,7 +8581,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
      <li><a href="#dom-mllstmoptions-bias">dict-member for MLLstmOptions</a><span>, in § 7.7.28</span>
     </ul>
    <li><a href="#bidirectionally-broadcastable">bidirectionally broadcastable</a><span>, in § 8.1</span>
-   <li><a href="#bidirectionally-broadcasting-the-shapes">bidirectionally broadcasting the shapes</a><span>, in § 8.1</span>
+   <li><a href="#bidirectionally-broadcasting">bidirectionally broadcasting</a><span>, in § 8.1</span>
    <li><a href="#dom-mlrecurrentnetworkdirection-both">"both"</a><span>, in § 7.7.20</span>
    <li><a href="#dom-mlgemmoptions-btranspose">bTranspose</a><span>, in § 7.7.19</span>
    <li><a href="#dom-mloperand-builder-slot">[[builder]]</a><span>, in § 7.6</span>
@@ -9004,7 +9003,7 @@ <h3 class="no-num no-ref heading settled" id="index-defined-here"><span class="c
    <li><a href="#dom-mloperanddatatype-uint64">"uint64"</a><span>, in § 7.5</span>
    <li><a href="#dom-mloperanddatatype-uint8">"uint8"</a><span>, in § 7.5</span>
    <li><a href="#unidirectionally-broadcastable">unidirectionally broadcastable</a><span>, in § 8.1</span>
-   <li><a href="#unidirectionally-broadcasting-the-shapes">unidirectionally broadcasting the shapes</a><span>, in § 8.1</span>
+   <li><a href="#unidirectionally-broadcasting">unidirectionally broadcasting</a><span>, in § 8.1</span>
    <li><a href="#dom-mltriangularoptions-upper">upper</a><span>, in § 7.7.46</span>
    <li><a href="#validate-buffer-with-descriptor">validate buffer with descriptor</a><span>, in § 7.3</span>
    <li><a href="#mlgraphbuilder-validate-operand">validate operand</a><span>, in § 7.6.1</span>
@@ -10085,8 +10084,8 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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MLOperandDescriptor dictionary"},{"refs":[{"id":"ref-for-mloperand\u2460\u2465"},{"id":"ref-for-mloperand\u2460\u2466"},{"id":"ref-for-mloperand\u2460\u2467"},{"id":"ref-for-mloperand\u2460\u2468"},{"id":"ref-for-mloperand\u2461\u24ea"},{"id":"ref-for-mloperand\u2461\u2460"},{"id":"ref-for-mloperand\u2461\u2461"},{"id":"ref-for-mloperand\u2461\u2462"},{"id":"ref-for-mloperand\u2461\u2463"},{"id":"ref-for-mloperand\u2461\u2464"},{"id":"ref-for-mloperand\u2461\u2465"},{"id":"ref-for-mloperand\u2461\u2466"}],"title":"7.6. MLOperand interface"},{"refs":[{"id":"ref-for-mloperand\u2461\u2467"},{"id":"ref-for-mloperand\u2461\u2468"},{"id":"ref-for-mloperand\u2462\u24ea"},{"id":"ref-for-mloperand\u2462\u2460"},{"id":"ref-for-mloperand\u2462\u2461"},{"id":"ref-for-mloperand\u2462\u2462"}],"title":"7.6.1. Creating an MLOperand"},{"refs":[{"id":"ref-for-mloperand\u2462\u2463"},{"id":"ref-for-mloperand\u2462\u2464"}],"title":"7.6.1.1. MLNumber"},{"refs":[{"id":"ref-for-mloperand\u2462\u2465"}],"title":"7.6.2. dataType()"},{"refs":[{"id":"ref-for-mloperand\u2462\u2466"}],"title":"7.6.3. shape()"},{"refs":[{"id":"ref-for-mloperand\u2462\u2467"},{"id":"ref-for-mloperand\u2462\u2468"},{"id":"ref-for-mloperand\u2463\u24ea"},{"id":"ref-for-mloperand\u2463\u2460"}],"title":"7.7. MLGraphBuilder interface"},{"refs":[{"id":"ref-for-mloperand\u2463\u2461"},{"id":"ref-for-mloperand\u2463\u2462"},{"id":"ref-for-mloperand\u2463\u2463"}],"title":"7.7.2. input operands"},{"refs":[{"id":"ref-for-mloperand\u2463\u2464"}],"title":"7.7.3. constant operands"},{"refs":[{"id":"ref-for-mloperand\u2463\u2465"},{"id":"ref-for-mloperand\u2463\u2466"}],"title":"7.7.3.1. constant(descriptor, bufferView)"},{"refs":[{"id":"ref-for-mloperand\u2463\u2467"},{"id":"ref-for-mloperand\u2463\u2468"}],"title":"7.7.3.2. constant(type, value)"},{"refs":[{"id":"ref-for-mloperand\u2464\u24ea"}],"title":"7.7.4. build method"},{"refs":[{"id":"ref-for-mloperand\u2464\u2460"},{"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"}],"title":"7.7.5. argMin/argMax operations"},{"refs":[{"id":"ref-for-mloperand\u2464\u2467"},{"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"}],"title":"7.7.6. batchNormalization"},{"refs":[{"id":"ref-for-mloperand\u2466\u24ea"},{"id":"ref-for-mloperand\u2466\u2460"},{"id":"ref-for-mloperand\u2466\u2461"},{"id":"ref-for-mloperand\u2466\u2462"}],"title":"7.7.7. cast"},{"refs":[{"id":"ref-for-mloperand\u2466\u2463"},{"id":"ref-for-mloperand\u2466\u2464"},{"id":"ref-for-mloperand\u2466\u2465"},{"id":"ref-for-mloperand\u2466\u2466"}],"title":"7.7.8. clamp"},{"refs":[{"id":"ref-for-mloperand\u2466\u2467"},{"id":"ref-for-mloperand\u2466\u2468"},{"id":"ref-for-mloperand\u2467\u24ea"},{"id":"ref-for-mloperand\u2467\u2460"}],"title":"7.7.9. concat"},{"refs":[{"id":"ref-for-mloperand\u2467\u2461"},{"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"}],"title":"7.7.10. conv2d"},{"refs":[{"id":"ref-for-mloperand\u2468\u24ea"},{"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"}],"title":"7.7.11. convTranspose2d"},{"refs":[{"id":"ref-for-mloperand\u2468\u2467"},{"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"}],"title":"7.7.12. Element-wise binary operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2461\u2463"},{"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"}],"title":"7.7.13. Element-wise logical operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2463\u2465"},{"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"}],"title":"7.7.14. Element-wise unary operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2466\u2464"},{"id":"ref-for-mloperand\u2460\u2466\u2465"},{"id":"ref-for-mloperand\u2460\u2466\u2466"},{"id":"ref-for-mloperand\u2460\u2466\u2467"}],"title":"7.7.15. elu"},{"refs":[{"id":"ref-for-mloperand\u2460\u2466\u2468"},{"id":"ref-for-mloperand\u2460\u2467\u24ea"},{"id":"ref-for-mloperand\u2460\u2467\u2460"},{"id":"ref-for-mloperand\u2460\u2467\u2461"}],"title":"7.7.16. expand"},{"refs":[{"id":"ref-for-mloperand\u2460\u2467\u2462"},{"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"}],"title":"7.7.17. gather"},{"refs":[{"id":"ref-for-mloperand\u2460\u2467\u2468"},{"id":"ref-for-mloperand\u2460\u2468\u24ea"},{"id":"ref-for-mloperand\u2460\u2468\u2460"},{"id":"ref-for-mloperand\u2460\u2468\u2461"}],"title":"7.7.18. gelu"},{"refs":[{"id":"ref-for-mloperand\u2460\u2468\u2462"},{"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"}],"title":"7.7.19. gemm"},{"refs":[{"id":"ref-for-mloperand\u2461\u24ea\u2460"},{"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"}],"title":"7.7.20. gru"},{"refs":[{"id":"ref-for-mloperand\u2461\u2460\u2464"},{"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"}],"title":"7.7.21. gruCell"},{"refs":[{"id":"ref-for-mloperand\u2461\u2461\u2468"},{"id":"ref-for-mloperand\u2461\u2462\u24ea"},{"id":"ref-for-mloperand\u2461\u2462\u2460"},{"id":"ref-for-mloperand\u2461\u2462\u2461"}],"title":"7.7.22. 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. instanceNormalization"},{"refs":[{"id":"ref-for-mloperand\u2461\u2463\u2464"},{"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"}],"title":"7.7.25. layerNormalization"},{"refs":[{"id":"ref-for-mloperand\u2461\u2464\u2462"},{"id":"ref-for-mloperand\u2461\u2464\u2463"},{"id":"ref-for-mloperand\u2461\u2464\u2464"},{"id":"ref-for-mloperand\u2461\u2464\u2465"}],"title":"7.7.26. leakyRelu"},{"refs":[{"id":"ref-for-mloperand\u2461\u2464\u2466"},{"id":"ref-for-mloperand\u2461\u2464\u2467"},{"id":"ref-for-mloperand\u2461\u2464\u2468"},{"id":"ref-for-mloperand\u2461\u2465\u24ea"}],"title":"7.7.27. 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. lstmCell"},{"refs":[{"id":"ref-for-mloperand\u2461\u2468\u2466"},{"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"}],"title":"7.7.30. matmul"},{"refs":[{"id":"ref-for-mloperand\u2462\u24ea\u2464"},{"id":"ref-for-mloperand\u2462\u24ea\u2465"},{"id":"ref-for-mloperand\u2462\u24ea\u2466"},{"id":"ref-for-mloperand\u2462\u24ea\u2467"}],"title":"7.7.31. pad"},{"refs":[{"id":"ref-for-mloperand\u2462\u24ea\u2468"},{"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"}],"title":"7.7.32. Pooling operations"},{"refs":[{"id":"ref-for-mloperand\u2462\u2460\u2467"},{"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"}],"title":"7.7.33. prelu"},{"refs":[{"id":"ref-for-mloperand\u2462\u2461\u2463"},{"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"}],"title":"7.7.34. 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+"unidirectionally-broadcastable": {"dfnID":"unidirectionally-broadcastable","dfnText":"unidirectionally broadcastable","external":false,"refSections":[{"refs":[{"id":"ref-for-unidirectionally-broadcastable"}],"title":"7.7.16. expand"},{"refs":[{"id":"ref-for-unidirectionally-broadcastable\u2460"},{"id":"ref-for-unidirectionally-broadcastable\u2461"},{"id":"ref-for-unidirectionally-broadcastable\u2462"}],"title":"7.7.19. gemm"}],"url":"#unidirectionally-broadcastable"},
+"unidirectionally-broadcasting": {"dfnID":"unidirectionally-broadcasting","dfnText":"unidirectionally broadcast the shapes","external":false,"refSections":[{"refs":[{"id":"ref-for-unidirectionally-broadcasting"}],"title":"7.7.16. expand"},{"refs":[{"id":"ref-for-unidirectionally-broadcasting\u2460"}],"title":"8.1. Broadcasting"}],"url":"#unidirectionally-broadcasting"},
 "valid-dimension": {"dfnID":"valid-dimension","dfnText":"valid dimension","external":false,"refSections":[{"refs":[{"id":"ref-for-valid-dimension"}],"title":"7.5. MLOperandDescriptor dictionary"},{"refs":[{"id":"ref-for-valid-dimension\u2460"}],"title":"7.7.9. concat"},{"refs":[{"id":"ref-for-valid-dimension\u2461"}],"title":"7.7.10. conv2d"},{"refs":[{"id":"ref-for-valid-dimension\u2462"}],"title":"7.7.11. convTranspose2d"},{"refs":[{"id":"ref-for-valid-dimension\u2463"},{"id":"ref-for-valid-dimension\u2464"}],"title":"7.7.20. gru"},{"refs":[{"id":"ref-for-valid-dimension\u2465"},{"id":"ref-for-valid-dimension\u2466"}],"title":"7.7.21. gruCell"},{"refs":[{"id":"ref-for-valid-dimension\u2467"},{"id":"ref-for-valid-dimension\u2468"}],"title":"7.7.28. lstm"},{"refs":[{"id":"ref-for-valid-dimension\u2460\u24ea"},{"id":"ref-for-valid-dimension\u2460\u2460"}],"title":"7.7.29. lstmCell"},{"refs":[{"id":"ref-for-valid-dimension\u2460\u2461"}],"title":"7.7.31. pad"},{"refs":[{"id":"ref-for-valid-dimension\u2460\u2462"}],"title":"7.7.32. Pooling operations"},{"refs":[{"id":"ref-for-valid-dimension\u2460\u2463"}],"title":"7.7.36. resample2d"},{"refs":[{"id":"ref-for-valid-dimension\u2460\u2464"}],"title":"7.7.37. reshape"}],"url":"#valid-dimension"},
 "validate-buffer-with-descriptor": {"dfnID":"validate-buffer-with-descriptor","dfnText":"validate buffer with descriptor","external":false,"refSections":[{"refs":[{"id":"ref-for-validate-buffer-with-descriptor"},{"id":"ref-for-validate-buffer-with-descriptor\u2460"}],"title":"7.3.2. compute()"},{"refs":[{"id":"ref-for-validate-buffer-with-descriptor\u2461"}],"title":"7.7.3.1. constant(descriptor, bufferView)"}],"url":"#validate-buffer-with-descriptor"},
 "webnn-feature": {"dfnID":"webnn-feature","dfnText":"webnn","external":false,"refSections":[{"refs":[{"id":"ref-for-webnn-feature"},{"id":"ref-for-webnn-feature\u2460"}],"title":"7.2.2. createContext()"},{"refs":[{"id":"ref-for-webnn-feature\u2461"}],"title":"7.7.1. MLGraphBuilder constructor"}],"url":"#webnn-feature"},
@@ -10952,7 +10951,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
 {
 let refsData = {
 "#bidirectionally-broadcastable": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"bidirectionally broadcastable","type":"dfn","url":"#bidirectionally-broadcastable"},
-"#bidirectionally-broadcasting-the-shapes": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"bidirectionally broadcasting the shapes","type":"dfn","url":"#bidirectionally-broadcasting-the-shapes"},
+"#bidirectionally-broadcasting": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"bidirectionally broadcasting","type":"dfn","url":"#bidirectionally-broadcasting"},
 "#cast": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"cast","type":"dfn","url":"#cast"},
 "#computational-graph": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"computational graph","type":"dfn","url":"#computational-graph"},
 "#computational-graph-constants": {"export":true,"for_":["computational graph"],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"constants","type":"dfn","url":"#computational-graph-constants"},
@@ -11395,7 +11394,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
 "#typedefdef-mlnamedoperands": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"MLNamedOperands","type":"typedef","url":"#typedefdef-mlnamedoperands"},
 "#typedefdef-mlnumber": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"MLNumber","type":"typedef","url":"#typedefdef-mlnumber"},
 "#unidirectionally-broadcastable": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"unidirectionally broadcastable","type":"dfn","url":"#unidirectionally-broadcastable"},
-"#unidirectionally-broadcasting-the-shapes": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"unidirectionally broadcasting the shapes","type":"dfn","url":"#unidirectionally-broadcasting-the-shapes"},
+"#unidirectionally-broadcasting": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"unidirectionally broadcasting","type":"dfn","url":"#unidirectionally-broadcasting"},
 "#valid-dimension": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"valid dimension","type":"dfn","url":"#valid-dimension"},
 "#validate-buffer-with-descriptor": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"validate buffer with descriptor","type":"dfn","url":"#validate-buffer-with-descriptor"},
 "#webnn-feature": {"export":true,"for_":[],"level":"","normative":true,"shortname":"webnn","spec":"webnn","status":"local","text":"webnn-feature","type":"dfn","url":"#webnn-feature"},