1 files changed, 178 insertions, 2 deletions
diff --git a/testing/web-platform/tests/webnn/validation_tests/layerNormalization.https.any.js b/testing/web-platform/tests/webnn/validation_tests/layerNormalization.https.any.js
index e9e9141aa6..63f9c0dbc5 100644
--- a/testing/web-platform/tests/webnn/validation_tests/layerNormalization.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/layerNormalization.https.any.js
@@ -9,8 +9,6 @@ const kExampleInputDescriptor = {
   dimensions: [2, 2]
 };
 
-validateOptionsAxes('layerNormalization', 4);
-
 validateInputFromAnotherBuilder('layerNormalization');
 
 multi_builder_test(async (t, builder, otherBuilder) => {
@@ -30,3 +28,181 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   const input = builder.input('input', kExampleInputDescriptor);
   assert_throws_js(TypeError, () => builder.layerNormalization(input, options));
 }, '[layerNormalization] throw if bias option is from another builder');
+
+const tests = [
+  {
+    name: '[layerNormalization] Test with default options for scalar input.',
+    input: {dataType: 'float32', dimensions: []},
+    output: {dataType: 'float32', dimensions: []},
+  },
+  {
+    name: '[layerNormalization] Test when the input data type is float16.',
+    input: {dataType: 'float16', dimensions: []},
+    output: {dataType: 'float16', dimensions: []},
+  },
+  {
+    name: '[layerNormalization] Test with given axes.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      axes: [3],
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+  },
+  {
+    name: '[layerNormalization] Test with given scale.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [2, 3, 4]},
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+  },
+  {
+    name: '[layerNormalization] Test with a non-default epsilon value.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      epsilon: 1e-4,  // default epsilon=1e-5
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+  },
+  {
+    name: '[layerNormalization] Test with given axes, scale and bias.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [3, 4]},
+      bias: {dataType: 'float32', dimensions: [3, 4]},
+      axes: [2, 3],
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+  },
+  {
+    name: '[layerNormalization] Test with nonconsecutive axes.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4, 5, 6]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [2, 4, 6]},
+      bias: {dataType: 'float32', dimensions: [2, 4, 6]},
+      axes: [1, 3, 5],
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4, 5, 6]},
+  },
+  {
+    name: '[layerNormalization] Test with axes in descending order.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4, 5, 6]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [6, 5, 4, 3, 2]},
+      bias: {dataType: 'float32', dimensions: [6, 5, 4, 3, 2]},
+      axes: [5, 4, 3, 2, 1]
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4, 5, 6]},
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the input data type is not one of the floating point types.',
+    input: {dataType: 'uint32', dimensions: [1, 2, 3, 4]},
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the axis is greater than the input rank.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      axes: [1, 2, 4],
+    },
+  },
+  {
+    name: '[layerNormalization] Throw if the axes have duplications.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {axes: [3, 3]},
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the bias data type doesn\'t match input data type',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [3, 4]},
+      bias: {dataType: 'float16', dimensions: [3, 4]},
+      axes: [2, 3],
+    },
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the scale data type doesn\'t match input data type',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      scale: {dataType: 'float16', dimensions: [3, 4]},
+      bias: {dataType: 'float32', dimensions: [3, 4]},
+      axes: [2, 3],
+    },
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the bias dimensions doesn\'t match axis dimensions.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      bias: {
+        dataType: 'float32',
+        dimensions: [3, 3, 4]
+      },  // for 4D input, default axes = [1,2,3]
+    },
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the scale dimensions doesn\'t match axis dimensions.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      scale: {
+        dataType: 'float32',
+        dimensions: [3, 3, 4]
+      },  // for 4D input, default axes = [1,2,3]
+    },
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the bias rank doesn\'t match axis rank.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      bias: {
+        dataType: 'float32',
+        dimensions: [1, 2, 3, 4]
+      },  // for 4D input, default axes = [1,2,3]
+    },
+  },
+  {
+    name:
+        '[layerNormalization] Throw if the scale rank doesn\'t match axis rank.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      scale: {
+        dataType: 'float32',
+        dimensions: [1, 2, 3, 4]
+      },  // for 4D input, default axes = [1,2,3]
+    },
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.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.options && test.options.scale) {
+        test.options.scale = builder.input('scale', {
+          dataType: test.options.scale.dataType,
+          dimensions: test.options.scale.dimensions
+        });
+      }
+
+      if (test.output) {
+        const output = builder.layerNormalization(input, test.options);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(
+            TypeError, () => builder.layerNormalization(input, test.options));
+      }
+    }, test.name));