Bug 1924561 [wpt PR 48602] - WebNN: Implement scatterElements opera…

…tor in DirectML backend, a=testonly Automatic update from web-platform-tests WebNN: Implement `scatterElements` operator in DirectML backend The `scatterElements` operator is proposed by WebML WG [1] for supporting popular transformer-based models. This CL adds the IDL and mojo definitions of scatterElements, and implements it in the DirectML backend by mapping to `DML_OPERATOR_SCATTER` [2]. This CL also adds the `scatterElements` validation and conformance tests into WPT. [1]: webmachinelearning/webnn#375 (comment) [2]: https://learn.microsoft.com/en-us/windows/win32/api/directml/ns-directml-dml_scatter_operator_desc Bug: 370536101,370538328 Change-Id: Ifb73bed5eb05cb919b106b4aaea5127ec099edb2 Cq-Include-Trybots: luci.chromium.try:win11-blink-rel, mac14.arm64-blink-rel, mac14-blink-rel, mac15.arm64-blink-rel, mac15-blink-rel, linux-blink-rel Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/5921136 Reviewed-by: Alex Gough <[email protected]> Reviewed-by: Weizhong Xia <[email protected]> Auto-Submit: ningxin hu <[email protected]> Commit-Queue: ningxin hu <[email protected]> Commit-Queue: Weizhong Xia <[email protected]> Reviewed-by: Rafael Cintron <[email protected]> Reviewed-by: Austin Sullivan <[email protected]> Cr-Commit-Position: refs/heads/main@{#1368312} -- wpt-commits: 59751055ef506c581da667594a2da8dac0c599b3 wpt-pr: 48602
i3roly · Oct 18, 2024 · 4298173 · 4298173
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diff --git a/testing/web-platform/tests/webnn/conformance_tests/scatterElements.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/scatterElements.https.any.js
@@ -0,0 +1,91 @@
+// META: title=test WebNN API scatterElements operation
+// META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
+// META: variant=?npu
+// META: script=../resources/utils.js
+// META: timeout=long
+
+'use strict';
+
+const getScatterElementsPrecisionTolerance = () => {
+  return {metricType: 'ULP', value: 0};
+};
+
+const scatterElementsTests = [
+  {
+    'name': 'Scatter elements along axis 0',
+    'graph': {
+      'inputs': {
+        'input': {
+          'data': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+          'descriptor': {shape: [3, 3], dataType: 'float32'}
+        },
+        'indices': {
+          'data': [1, 0, 2, 0, 2, 1],
+          'descriptor': {shape: [2, 3], dataType: 'int32'},
+        },
+        'updates': {
+          'data': [1.0, 1.1, 1.2, 2.0, 2.1, 2.2],
+          'descriptor': {shape: [2, 3], dataType: 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'scatterElements',
+        'arguments': [
+          {'input': 'input'}, {'indices': 'indices'}, {'updates': 'updates'},
+          {'options': {'axis': 0}}
+        ],
+        'outputs': 'output'
+      }],
+      'expectedOutputs': {
+        'output': {
+          'data': [2.0, 1.1, 0.0, 1.0, 0.0, 2.2, 0.0, 2.1, 1.2],
+          'descriptor': {shape: [3, 3], dataType: 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'Scatter elements along axis 1',
+    'graph': {
+      'inputs': {
+        'input': {
+          'data': [1.0, 2.0, 3.0, 4.0, 5.0],
+          'descriptor': {shape: [1, 5], dataType: 'float32'}
+        },
+        'indices': {
+          'data': [1, 3],
+          'descriptor': {shape: [1, 2], dataType: 'int32'},
+        },
+        'updates': {
+          'data': [1.1, 2.1],
+          'descriptor': {shape: [1, 2], dataType: 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'scatterElements',
+        'arguments': [
+          {'input': 'input'}, {'indices': 'indices'}, {'updates': 'updates'},
+          {'options': {'axis': 1}}
+        ],
+        'outputs': 'output'
+      }],
+      'expectedOutputs': {
+        'output': {
+          'data': [1.0, 1.1, 3.0, 2.1, 5.0],
+          'descriptor': {shape: [1, 5], dataType: 'float32'}
+        }
+      }
+    }
+  }
+];
+
+if (navigator.ml) {
+  scatterElementsTests.forEach((test) => {
+    webnn_conformance_test(
+        buildGraphAndCompute, getScatterElementsPrecisionTolerance, test);
+  });
+} else {
+  test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
+}
diff --git a/testing/web-platform/tests/webnn/validation_tests/scatterElements.https.any.js b/testing/web-platform/tests/webnn/validation_tests/scatterElements.https.any.js
@@ -0,0 +1,150 @@
+// META: title=validation tests for WebNN API scatterElements operation
+// META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
+// META: variant=?npu
+// META: script=../resources/utils_validation.js
+
+'use strict';
+
+const tests = [
+  {
+    name: '[scatterElements] Test scatterElements with default options',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 3]},
+    updates: {dataType: 'float32', shape: [2, 3]},
+    output: {dataType: 'float32', shape: [3, 3]}
+  },
+  {
+    name: '[scatterElements] Test scatterElements with axis = 0',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 3]},
+    updates: {dataType: 'float32', shape: [2, 3]},
+    axis: 0,
+    output: {dataType: 'float32', shape: [3, 3]}
+  },
+  {
+    name: '[scatterElements] Test scatterElements with axis = 1',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [3, 2]},
+    updates: {dataType: 'float32', shape: [3, 2]},
+    axis: 1,
+    output: {dataType: 'float32', shape: [3, 3]}
+  },
+  {
+    name: '[scatterElements] Throw if axis is greater than input rank',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 3]},
+    updates: {dataType: 'float32', shape: [2, 3]},
+    axis: 2
+  },
+  {
+    name:
+        '[scatterElements] Throw if updates tensor data type is not the same as input data type',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 3]},
+    updates: {dataType: 'float16', shape: [2, 3]},
+  },
+  {
+    name: '[scatterElements] Throw if input, indices and updates are scalar',
+    input: {dataType: 'float32', shape: []},
+    indices: {dataType: 'int32', shape: []},
+    updates: {dataType: 'float32', shape: []},
+  },
+  {
+    name:
+        '[scatterElements] Throw if indices rank is not the same as input rank',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 3, 3]},
+    updates: {dataType: 'float32', shape: [2, 3, 3]},
+  },
+  {
+    name:
+        '[scatterElements] Throw if indices size is not the same as input size along axis 1',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 4]},
+    updates: {dataType: 'float32', shape: [2, 4]},
+    axis: 0
+  },
+  {
+    name:
+        '[scatterElements] Throw if indices size is not the same as input size along axis 0',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 2]},
+    updates: {dataType: 'float32', shape: [2, 2]},
+    axis: 1
+  },
+  {
+    name:
+        '[scatterElements] Throw if indices rank is not the same as updates rank',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 3]},
+    updates: {dataType: 'float32', shape: [2, 3, 3]},
+  },
+  {
+    name:
+        '[scatterElements] Throw if indices shape is not the same as updates shape',
+    input: {dataType: 'float32', shape: [3, 3]},
+    indices: {dataType: 'int32', shape: [2, 3]},
+    updates: {dataType: 'float32', shape: [2, 4]},
+  }
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const builder = new MLGraphBuilder(context);
+      const input = builder.input('input', test.input);
+      const indices = builder.input('indices', test.indices);
+      const updates = builder.input('updates', test.updates);
+
+      const options = {};
+      if (test.axis) {
+        options.axis = test.axis;
+      }
+
+      if (test.output) {
+        const output =
+            builder.scatterElements(input, indices, updates, options);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.shape);
+      } else {
+        const label = 'a_scatter_elements'
+        options.label = label;
+        const regexp = new RegExp('\\[' + label + '\\]');
+        assert_throws_with_label(
+            () => builder.scatterElements(input, indices, updates, options),
+            regexp);
+      }
+    }, test.name));
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const input =
+      otherBuilder.input('input', {dataType: 'float32', shape: [3, 3]});
+  const indices = builder.input('indices', {dataType: 'int32', shape: [2, 3]});
+  const updates =
+      builder.input('updates', {dataType: 'float32', shape: [2, 3]});
+
+  assert_throws_js(
+      TypeError, () => builder.scatterElements(input, indices, updates));
+}, '[scatterElements] Throw if input is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const input = builder.input('input', {dataType: 'float32', shape: [3, 3]});
+  const indices =
+      otherBuilder.input('indices', {dataType: 'int32', shape: [2, 3]});
+  const updates =
+      builder.input('updates', {dataType: 'float32', shape: [2, 3]});
+
+  assert_throws_js(
+      TypeError, () => builder.scatterElements(input, indices, updates));
+}, '[scatterElements] Throw if indices is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const input = builder.input('input', {dataType: 'float32', shape: [3, 3]});
+  const indices = builder.input('indices', {dataType: 'int32', shape: [2, 3]});
+  const updates =
+      otherBuilder.input('updates', {dataType: 'float32', shape: [2, 3]});
+
+  assert_throws_js(
+      TypeError, () => builder.scatterElements(input, indices, updates));
+}, '[scatterElements] Throw if updates is from another builder');