webnn: Add the lstmCell operator

This CL adds the IDL and mojo definition for lstmCell, implements
`MLGraphBuilder::lstmCell()` and adds validations on services side. The
DirectML backend implementation is shared with lstm.

This CL also adds lstmCell validation tests in WPT and unit tests in
`WebNNGraphImplTest`.

Bug: 40206287
Change-Id: I8c740ffa43f79d4667bddca93a064ab788cf8129
Cq-Include-Trybots: luci.chromium.try:gpu-fyi-try-win11-qualcomm-rel-64
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/5347306
Reviewed-by: Austin Sullivan <asully@chromium.org>
Reviewed-by: ningxin hu <ningxin.hu@intel.com>
Reviewed-by: Reilly Grant <reillyg@chromium.org>
Auto-Submit: Shiyi Zou <shiyi.zou@intel.com>
Commit-Queue: Shiyi Zou <shiyi.zou@intel.com>
Cr-Commit-Position: refs/heads/main@{#1278827}

webnn/validation_tests/lstmCell.https.any.js

@@ -204,3 +204,397 @@ multi_builder_test(async (t, builder, otherBuilder) => {
           input, weight, recurrentWeight, hiddenState, cellState, hiddenSize,
           options));
 }, '[lstmCell] throw if activation option is from another builder');
+
+const tests = [
+  {
+    name: '[lstmCell] Test with default options',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    outputs: [
+      {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+      {dataType: 'float16', dimensions: [batchSize, hiddenSize]}
+    ]
+  },
+  {
+    name: '[lstmCell] Test with given options',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {
+      bias: {dataType: 'float32', dimensions: [4 * hiddenSize]},
+      recurrentBias: {dataType: 'float32', dimensions: [4 * hiddenSize]},
+      peepholeWeight: {dataType: 'float32', dimensions: [3 * hiddenSize]},
+      layout: 'ifgo',
+      activations: ['sigmoid', 'relu', 'tanh']
+    },
+    outputs: [
+      {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+      {dataType: 'float32', dimensions: [batchSize, hiddenSize]}
+    ]
+  },
+  {
+    name: '[lstmCell] Throw if hiddenSize is equal to zero',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: 0
+  },
+  {
+    name: '[lstmCell] Throw if hiddenSize is too large',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: 4294967295
+  },
+  {
+    name:
+        '[lstmCell] Throw if the input data type is not one of the floating point types',
+    input: {dataType: 'uint32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the rank of input is not 2',
+    input: {dataType: 'float32', dimensions: [batchSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the shape of input is incorrect',
+    input: {dataType: 'float32', dimensions: [batchSize, 1000]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the data type of weight is incorrect',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the rank of weight is not 2',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize, 1000]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the shape of weight is incorrect',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [1000, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the data type of recurrentWeight is incorrect',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the rank of recurrentWeight is not 2',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [1000, 4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the shape of recurrentWeight is incorrect',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight: {dataType: 'float32', dimensions: [1000, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the data type of hiddenState is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'int64', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the rank of hiddenState is not 2',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the shape of hiddenState is incorrect',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, 1000]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the data type of cellState is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the rank of cellState is not 2',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the shape of cellState is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, 1000]},
+    hiddenSize: hiddenSize
+  },
+  {
+    name: '[lstmCell] Throw if the data type of options.bias is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {bias: {dataType: 'int8', dimensions: [4 * hiddenSize]}}
+  },
+  {
+    name: '[lstmCell] Throw if the rank of options.bias is not 1',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {bias: {dataType: 'float16', dimensions: [4 * hiddenSize, 1000]}}
+  },
+  {
+    name: '[lstmCell] Throw if the shape of options.bias is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {bias: {dataType: 'float16', dimensions: [1000]}}
+  },
+  {
+    name:
+        '[lstmCell] Throw if the data type of options.recurrentBias is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {recurrentBias: {dataType: 'uint8', dimensions: [4 * hiddenSize]}}
+  },
+  {
+    name: '[lstmCell] Throw if the rank of options.recurrentBias is not 1',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {
+      recurrentBias: {dataType: 'float16', dimensions: [4 * hiddenSize, 1000]}
+    }
+  },
+  {
+    name: '[lstmCell] Throw if the shape of options.recurrentBias is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {recurrentBias: {dataType: 'float16', dimensions: [1000]}}
+  },
+  {
+    name:
+        '[lstmCell] Throw if the data type of options.peepholeWeight is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options:
+        {peepholeWeight: {dataType: 'float32', dimensions: [3 * hiddenSize]}}
+  },
+  {
+    name: '[lstmCell] Throw if the rank of options.peepholeWeight is not 1',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {peepholeWeight: {dataType: 'float16', dimensions: []}}
+  },
+  {
+    name:
+        '[lstmCell] Throw if the shape of options.peepholeWeight is incorrect',
+    input: {dataType: 'float16', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float16', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float16', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float16', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {peepholeWeight: {dataType: 'float16', dimensions: [1000]}}
+  },
+  {
+    name: '[lstmCell] Throw if the size of options.activations is not 3',
+    input: {dataType: 'float32', dimensions: [batchSize, inputSize]},
+    weight: {dataType: 'float32', dimensions: [4 * hiddenSize, inputSize]},
+    recurrentWeight:
+        {dataType: 'float32', dimensions: [4 * hiddenSize, hiddenSize]},
+    hiddenState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    cellState: {dataType: 'float32', dimensions: [batchSize, hiddenSize]},
+    hiddenSize: hiddenSize,
+    options: {activations: ['sigmoid', 'tanh', 'sigmoid', 'tanh']}
+  }
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.dimensions});
+      const weight = builder.input(
+          'weight',
+          {dataType: test.weight.dataType, dimensions: test.weight.dimensions});
+      const recurrentWeight = builder.input('recurrentWeight', {
+        dataType: test.recurrentWeight.dataType,
+        dimensions: test.recurrentWeight.dimensions
+      });
+      const hiddenState = builder.input('hiddenState', {
+        dataType: test.hiddenState.dataType,
+        dimensions: test.hiddenState.dimensions
+      });
+      const cellState = builder.input('cellState', {
+        dataType: test.cellState.dataType,
+        dimensions: test.cellState.dimensions
+      });
+
+      const options = {};
+      if (test.options) {
+        if (test.options.bias) {
+          options.bias = builder.input('bias', {
+            dataType: test.options.bias.dataType,
+            dimensions: test.options.bias.dimensions
+          });
+        }
+        if (test.options.recurrentBias) {
+          options.bias = builder.input('recurrentBias', {
+            dataType: test.options.recurrentBias.dataType,
+            dimensions: test.options.recurrentBias.dimensions
+          });
+        }
+        if (test.options.peepholeWeight) {
+          options.peepholeWeight = builder.input('peepholeWeight', {
+            dataType: test.options.peepholeWeight.dataType,
+            dimensions: test.options.peepholeWeight.dimensions
+          });
+        }
+        if (test.options.layout) {
+          options.layout = test.options.layout;
+        }
+        if (test.options.activations) {
+          options.activations = [];
+          test.options.activations.forEach(
+              activation => options.activations.push(builder[activation]()));
+        }
+      }
+
+      if (test.outputs) {
+        const outputs = builder.lstmCell(
+            input, weight, recurrentWeight, hiddenState, cellState,
+            test.hiddenSize, options);
+        assert_equals(outputs.length, test.outputs.length);
+        for (let i = 0; i < outputs.length; ++i) {
+          assert_equals(outputs[i].dataType(), test.outputs[i].dataType);
+          assert_array_equals(outputs[i].shape(), test.outputs[i].dimensions);
+        }
+      } else {
+        assert_throws_js(
+            TypeError,
+            () => builder.lstmCell(
+                input, weight, recurrentWeight, hiddenState, cellState,
+                test.hiddenSize, options));
+      }
+    }, test.name));