1 files changed, 475 insertions, 0 deletions
diff --git a/testing/web-platform/tests/webnn/validation_tests/conv2d.https.any.js b/testing/web-platform/tests/webnn/validation_tests/conv2d.https.any.js
index ffc9c2c65d..7dac654951 100644
--- a/testing/web-platform/tests/webnn/validation_tests/conv2d.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/conv2d.https.any.js
@@ -55,3 +55,478 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   const filter = builder.input('filter', kExampleFilterDescriptor);
   assert_throws_js(TypeError, () => builder.conv2d(input, filter, options));
 }, '[conv2d] throw if activation option is from another builder');
+
+const tests = [
+  {
+    name: '[conv2d] Test with default options.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    output: {dataType: 'float32', dimensions: [1, 1, 3, 3]}
+  },
+  {
+    name: '[conv2d] Test with padding.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [1, 1, 1, 1],
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 5, 5]}
+  },
+  {
+    name: '[conv2d] Test with strides and padding.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [1, 1, 1, 1],
+      strides: [2, 2],
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 3, 3]}
+  },
+  {
+    name: '[conv2d] Test with strides and asymmetric padding.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 4, 2]},
+    options: {
+      padding: [1, 2, 0, 1],
+      strides: [2, 2],
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 3, 3]}
+  },
+  {
+    name: '[conv2d] Test depthwise conv2d by setting groups to input channels.',
+    input: {dataType: 'float32', dimensions: [1, 4, 2, 2]},
+    filter: {dataType: 'float32', dimensions: [4, 1, 2, 2]},
+    options: {
+      groups: 4,
+    },
+    output: {dataType: 'float32', dimensions: [1, 4, 1, 1]}
+  },
+  {
+    name:
+        '[conv2d] Test depthwise conv2d with groups, inputLayout="nhwc" and filterLayout="ihwo".',
+    input: {dataType: 'float32', dimensions: [1, 2, 2, 4]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 2, 4]},
+    options: {
+      groups: 4,
+      inputLayout: 'nhwc',
+      filterLayout: 'ihwo',
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 1, 4]}
+  },
+  {
+    name:
+        '[conv2d] Test with dilations, inputLayout="nhwc" and filterLayout="ihwo".',
+    input: {dataType: 'float32', dimensions: [1, 65, 65, 1]},
+    filter: {dataType: 'float32', dimensions: [1, 3, 3, 1]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'ihwo',
+      dilations: [4, 4],
+    },
+    output: {dataType: 'float32', dimensions: [1, 57, 57, 1]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nchw" and filterLayout="oihw".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'oihw',
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 3, 3]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nchw" and filterLayout="hwio".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [3, 3, 2, 1]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'hwio',
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 3, 3]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nchw" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 3, 3, 2]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'ohwi',
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 3, 3]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nchw" and filterLayout="ihwo".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'ihwo',
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 3, 3]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nhwc" and filterLayout="oihw".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'oihw',
+    },
+    output: {dataType: 'float32', dimensions: [1, 3, 3, 1]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nhwc" and filterLayout="hwio".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [3, 3, 2, 1]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'hwio',
+    },
+    output: {dataType: 'float32', dimensions: [1, 3, 3, 1]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nhwc" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 3, 3, 2]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'ohwi',
+    },
+    output: {dataType: 'float32', dimensions: [1, 3, 3, 1]}
+  },
+  {
+    name: '[conv2d] Test with inputLayout="nhwc" and filterLayout="ihwo".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'ihwo',
+    },
+    output: {dataType: 'float32', dimensions: [1, 3, 3, 1]}
+  },
+  {
+    name: '[conv2d] Throw if the input is not a 4-D tensor.',
+    input: {dataType: 'float32', dimensions: [1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 2, 1]},
+  },
+  {
+    name: '[conv2d] Throw if the input data type is not floating point.',
+    input: {dataType: 'int32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'int32', dimensions: [1, 1, 2, 2]},
+  },
+  {
+    name: '[conv2d] Throw if the filter is not a 4-D tensor.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [2, 2]},
+  },
+  {
+    name:
+        '[conv2d] Throw if the filter data type doesn\'t match the input data type.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'int32', dimensions: [1, 1, 2, 2]},
+  },
+  {
+    name: '[conv2d] Throw if the length of padding is not 4.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      padding: [2, 2],
+    },
+  },
+  {
+    name: '[conv2d] Throw if the length of strides is not 2.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      strides: [2],
+    },
+  },
+  {
+    name: '[conv2d] Throw if strideHeight is smaller than 1.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      strides: [0, 1],
+    },
+  },
+  {
+    name: '[conv2d] Throw if strideWidth is smaller than 1.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      strides: [1, 0],
+    },
+  },
+  {
+    name: '[conv2d] Throw if the length of dilations is not 2.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      dilations: [1],
+    },
+  },
+  {
+    name: '[conv2d] Throw if dilationHeight is smaller than 1.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      dilations: [0, 1],
+    },
+  },
+  {
+    name: '[conv2d] Throw if dilationWidth is smaller than 1.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      dilations: [1, 0],
+    },
+  },
+  {
+    name: '[conv2d] Throw if inputChannels % groups is not 0.',
+    input: {dataType: 'float32', dimensions: [1, 4, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      groups: 3,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels.',
+    input: {dataType: 'float32', dimensions: [1, 4, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      groups: 2,
+    },
+  },
+  {
+    name: '[conv2d] Throw if the groups is smaller than 1.',
+    input: {dataType: 'float32', dimensions: [1, 4, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      groups: 0,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw due to overflow when calculating the effective filter height.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 434983, 2]},
+    options: {
+      dilations: [328442, 1],
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw due to overflow when calculating the effective filter width.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 234545]},
+    options: {
+      dilations: [2, 843452],
+    },
+  },
+  {
+    name: '[conv2d] Throw due to overflow when dilation height is too large.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      dilations: [kMaxUnsignedLong, 1],
+    },
+  },
+  {
+    name: '[conv2d] Throw due to overflow when dilation width is too large.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      dilations: [1, kMaxUnsignedLong],
+    },
+  },
+  {
+    name: '[conv2d] Throw due to underflow when calculating the output height.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 4, 2]},
+    options: {
+      dilations: [4, 1],
+      padding: [1, 1, 1, 1],
+      strides: [2, 2],
+    },
+  },
+  {
+    name: '[conv2d] Throw due to underflow when calculating the output width.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 8]},
+    options: {
+      dilations: [1, 4],
+      padding: [1, 1, 1, 1],
+      strides: [2, 2],
+    },
+  },
+  {
+    name: '[conv2d] Throw if the bias is not a 1-D tensor.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      bias: {dataType: 'float32', dimensions: [1, 2]},
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if the bias shape is not equal to [output_channels] with filterLayout="oihw".',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if the bias shape is not equal to [output_channels] with filterLayout="hwio".',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [2, 2, 1, 1]},
+    options: {
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if the bias shape is not equal to [output_channels] with filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 2, 1]},
+    options: {
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if the bias shape is not equal to [output_channels] with filterLayout="ihwo".',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 2, 1]},
+    options: {
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if the bias data type doesn\'t match input data type.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      bias: {dataType: 'int32', dimensions: [1]},
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nchw" and filterLayout="oihw".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'oihw',
+      groups: 2,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nchw" and filterLayout="hwio".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [3, 3, 2, 1]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'hwio',
+      groups: 2,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nchw" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 3, 3, 2]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'ohwi',
+      groups: 2,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nchw" and filterLayout="ihwo".',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      inputLayout: 'nchw',
+      filterLayout: 'ihwo',
+      groups: 2,
+    },
+
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nhwc" and filterLayout="oihw".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'oihw',
+      groups: 2,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nhwc" and filterLayout="hwio".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [3, 3, 2, 1]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'hwio',
+      groups: 2,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nhwc" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 3, 3, 2]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'ohwi',
+      groups: 2,
+    },
+  },
+  {
+    name:
+        '[conv2d] Throw if inputChannels / groups is not equal to filterInputChannels with inputLayout="nhwc" and filterLayout="ihwo".',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      inputLayout: 'nhwc',
+      filterLayout: 'ihwo',
+      groups: 2,
+    },
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.dimensions});
+      const filter = builder.input(
+          'filter',
+          {dataType: test.filter.dataType, dimensions: test.filter.dimensions});
+
+      if (test.options && test.options.bias) {
+        test.options.bias = builder.input('bias', {
+          dataType: test.options.bias.dataType,
+          dimensions: test.options.bias.dimensions
+        });
+      }
+
+      if (test.output) {
+        const output = builder.conv2d(input, filter, test.options);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(
+            TypeError, () => builder.conv2d(input, filter, test.options));
+      }
+    }, test.name));