Merging upstream version 127.0.

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
author: Daniel Baumann <daniel.baumann@progress-linux.org> 2024-06-12 05:43:14 +0000
committer: Daniel Baumann <daniel.baumann@progress-linux.org> 2024-06-12 05:43:14 +0000
commit: 8dd16259287f58f9273002717ec4d27e97127719 (patch)
tree: 3863e62a53829a84037444beab3abd4ed9dfc7d0 /testing/web-platform/tests/webnn
parent: Releasing progress-linux version 126.0.1-1~progress7.99u1. (diff)
download: firefox-8dd16259287f58f9273002717ec4d27e97127719.tar.xz
firefox-8dd16259287f58f9273002717ec4d27e97127719.zip
118 files changed, 2652 insertions, 1094 deletions
diff --git a/testing/web-platform/tests/webnn/conformance_tests/arg_min_max.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/arg_min_max.https.any.js
index 123c8b1048..0f9e590fc8 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/arg_min_max.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/arg_min_max.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API argMin/Max operations
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-argminmax
 
-testWebNNOperation(['argMin', 'argMax'], buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests(['argMin', 'argMax'], buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/batch_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/batch_normalization.https.any.js
index 9a1c85db19..d3107820db 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/batch_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/batch_normalization.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API batchNormalization operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-batchnorm
 
-testWebNNOperation('batchNormalization', buildBatchNorm);
-\ No newline at end of file
+runWebNNConformanceTests('batchNormalization', buildBatchNorm);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/buffer.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/buffer.https.any.js
index 9391be8dbf..5a09b05c7d 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/buffer.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/buffer.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API buffer operations
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,10 +9,11 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlbuffer
 
-testCreateWebNNBuffer("create", 4);
-
-testDestroyWebNNBuffer('destroyTwice');
-
-testReadWebNNBuffer('read');
-
-testWriteWebNNBuffer('write');
+if (navigator.ml) {
+  testCreateWebNNBuffer('create', 4);
+  testDestroyWebNNBuffer('destroyTwice');
+  testReadWebNNBuffer('read');
+  testWriteWebNNBuffer('write');
+} else {
+  test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
+}
diff --git a/testing/web-platform/tests/webnn/conformance_tests/cast.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/cast.https.any.js
index bde2b9a4ce..086428dd96 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/cast.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/cast.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API cast operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-cast
 
-testWebNNOperation('cast', buildCast);
-\ No newline at end of file
+runWebNNConformanceTests('cast', buildCast);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/clamp.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/clamp.https.any.js
index 7b60c41f2c..ab47ac9c5c 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/clamp.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/clamp.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API clamp operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-clamp
 
-testWebNNOperation('clamp', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('clamp', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/compute-arraybufferview-with-bigger-arraybuffer.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/compute-arraybufferview-with-bigger-arraybuffer.https.any.js
new file mode 100644
index 0000000000..62ce16c93e
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/compute-arraybufferview-with-bigger-arraybuffer.https.any.js
@@ -0,0 +1,61 @@
+// META: title=test WebNN MLContext.compute() for ArrayBufferView created from bigger ArrayBuffer
+// META: global=window,dedicatedworker
+// META: variant=?gpu
+// META: script=../resources/utils.js
+
+'use strict';
+
+// These tests are used to reproduce the Chromium issue:
+// https://issues.chromium.org/issues/332151809
+
+if (navigator.ml) {
+  const variant = location.search.substring(1);
+  const contextOptions = kContextOptionsForVariant[variant];
+
+  let context;
+  let builder;
+
+  promise_setup(async () => {
+    let supported = false;
+    try {
+      context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
+    builder = new MLGraphBuilder(context);
+  });
+
+  promise_test(async t => {
+    const a = builder.input('a', {dataType: 'float32', dimensions: [2]});
+    const b = builder.relu(a);
+    const graph = await builder.build({b});
+    const arraybuffer = new ArrayBuffer(100);
+    const aBuffer =
+        new Float32Array(arraybuffer, /*byteOffset*/ 4, /*length*/ 2)
+    aBuffer.set([1, -1]);
+    const bBuffer = new Float32Array(2);
+    const results =
+        await context.compute(graph, {'a': aBuffer}, {'b': bBuffer});
+    assert_array_approx_equals_ulp(
+        results.outputs.b, [1, 0], /*nulp*/ 0, 'float32');
+  }, 'Test compute() working for input ArrayBufferView created from bigger ArrayBuffer');
+
+  promise_test(async t => {
+    const a = builder.input('a', {dataType: 'float32', dimensions: [2]});
+    const b = builder.relu(a);
+    const graph = await builder.build({b});
+    const aBuffer = new Float32Array(2);
+    aBuffer.set([1, -1]);
+    const arraybuffer = new ArrayBuffer(100);
+    const bBuffer =
+        new Float32Array(arraybuffer, /*byteOffset*/ 8, /*length*/ 2);
+    const results =
+        await context.compute(graph, {'a': aBuffer}, {'b': bBuffer});
+    assert_array_approx_equals_ulp(
+        results.outputs.b, [1, 0], /*nulp*/ 0, 'float32');
+  }, 'Test compute() working for output ArrayBufferView created from bigger ArrayBuffer');
+} else {
+  test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
+}
diff --git a/testing/web-platform/tests/webnn/conformance_tests/concat.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/concat.https.any.js
index 254e0b657b..619f20fe1c 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/concat.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/concat.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API concat operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-concat
 
-testWebNNOperation('concat', buildConcat);
-\ No newline at end of file
+runWebNNConformanceTests('concat', buildConcat);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/constant.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/constant.https.any.js
index 4814734886..79362947f1 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/constant.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/constant.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API constant
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-constant-range
 
-testWebNNOperation('constant', buildConstantRange);
-\ No newline at end of file
+runWebNNConformanceTests('constant', buildConstantRange);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/conv2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/conv2d.https.any.js
index 0d9a621356..34af583162 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/conv2d.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/conv2d.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API conv2d operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-conv2d
 
-testWebNNOperation('conv2d', buildConv2d);
-\ No newline at end of file
+runWebNNConformanceTests('conv2d', buildConv2d);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/conv_transpose2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/conv_transpose2d.https.any.js
index ee5d28c72a..2943e67851 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/conv_transpose2d.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/conv_transpose2d.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API convTranspose2d operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-convtranspose2d
 
-testWebNNOperation('convTranspose2d', buildConvTranspose2d);
-\ No newline at end of file
+runWebNNConformanceTests('convTranspose2d', buildConvTranspose2d);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/elementwise_binary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elementwise_binary.https.any.js
index 5db14a43a1..a85a06e1d2 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/elementwise_binary.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elementwise_binary.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API element-wise binary operations
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,6 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-binary
 
-testWebNNOperation(['add', 'sub', 'mul', 'div', 'max', 'min', 'pow'], buildOperationWithTwoInputs);
-\ No newline at end of file
+runWebNNConformanceTests(
+    ['add', 'sub', 'mul', 'div', 'max', 'min', 'pow'],
+    buildOperationWithTwoInputs);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/elementwise_logical.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elementwise_logical.https.any.js
index a60c199447..3d3a825f9c 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/elementwise_logical.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elementwise_logical.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API element-wise logical operations
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,14 +9,17 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-logical
 
-testWebNNOperation(
-  [
-    'equal',
-    'greater',
-    'greaterOrEqual',
-    'lesser',
-    'lesserOrEqual',
-  ],
-  buildOperationWithTwoInputs
-);
-testWebNNOperation('logicalNot', buildOperationWithSingleInput);
-\ No newline at end of file
+if (navigator.ml) {
+  testWebNNOperation(
+      [
+        'equal',
+        'greater',
+        'greaterOrEqual',
+        'lesser',
+        'lesserOrEqual',
+      ],
+      buildOperationWithTwoInputs);
+  testWebNNOperation('logicalNot', buildOperationWithSingleInput);
+} else {
+  test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
+}
diff --git a/testing/web-platform/tests/webnn/conformance_tests/elementwise_unary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elementwise_unary.https.any.js
index 8029539eda..f202af01e5 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/elementwise_unary.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elementwise_unary.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API element-wise unary operations
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,7 +9,9 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-unary
 
-testWebNNOperation(
-  ['abs', 'ceil', 'cos', 'erf', 'exp', 'floor', 'identity', 'log', 'neg', 'reciprocal', 'sin', 'sqrt', 'tan'],
-  buildOperationWithSingleInput
-);
-\ No newline at end of file
+runWebNNConformanceTests(
+    [
+      'abs', 'ceil', 'cos', 'erf', 'exp', 'floor', 'identity', 'log', 'neg',
+      'reciprocal', 'sin', 'sqrt', 'tan'
+    ],
+    buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/elu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elu.https.any.js
index 382faa97fd..ac1c19a80b 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/elu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elu.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API elu operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-elu
 
-testWebNNOperation('elu', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('elu', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/expand.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/expand.https.any.js
index b1be129eac..e7bf106f96 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/expand.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/expand.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API expand operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,5 +9,5 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-expand
 
-// reuse buildReshape method
-testWebNNOperation('expand', buildReshape);
-\ No newline at end of file
+// Reuse buildReshape method
+runWebNNConformanceTests('expand', buildReshape);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gather.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gather.https.any.js
index 39b1970563..504f2dd792 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/gather.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gather.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API gather operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-gather
 
-testWebNNOperation('gather', buildOperationWithTwoInputs);
-\ No newline at end of file
+runWebNNConformanceTests('gather', buildOperationWithTwoInputs);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gemm.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gemm.https.any.js
index 61fd7c9b39..03a836a44a 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/gemm.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gemm.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API gemm operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-gemm
 
-testWebNNOperation('gemm', buildGemm);
-\ No newline at end of file
+runWebNNConformanceTests('gemm', buildGemm);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/arg_min_max.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/arg_min_max.https.any.js
deleted file mode 100644
index c700ee5cad..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/arg_min_max.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API argMin/Max operations
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-argminmax
-
-testWebNNOperation(['argMin', 'argMax'], buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/batch_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/batch_normalization.https.any.js
deleted file mode 100644
index 534cdf6365..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/batch_normalization.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API batchNormalization operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-batchnorm
-
-testWebNNOperation('batchNormalization', buildBatchNorm, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/buffer.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/buffer.https.any.js
deleted file mode 100644
index 225bc40185..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/buffer.https.any.js
+++ /dev/null
@@ -1,16 +0,0 @@
-// META: title=test WebNN API buffer operations
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlbuffer
-
-testCreateWebNNBuffer("create", 4, 'gpu');
-
-testDestroyWebNNBuffer('destroyTwice', 'gpu');
-
-testReadWebNNBuffer('read', 'gpu');
-
-testWriteWebNNBuffer('write', 'gpu');
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/cast.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/cast.https.any.js
deleted file mode 100644
index e4309ffd8e..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/cast.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API cast operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-cast
-
-testWebNNOperation('cast', buildCast, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/clamp.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/clamp.https.any.js
deleted file mode 100644
index 9b3f93ecc7..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/clamp.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API clamp operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-clamp
-
-testWebNNOperation('clamp', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/concat.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/concat.https.any.js
deleted file mode 100644
index c0cfb8626b..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/concat.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API concat operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-concat
-
-testWebNNOperation('concat', buildConcat, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/constant.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/constant.https.any.js
deleted file mode 100644
index 77b4d889a2..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/constant.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API constant
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-constant-range
-
-testWebNNOperation('constant', buildConstantRange, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/conv2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/conv2d.https.any.js
deleted file mode 100644
index 770540abd8..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/conv2d.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API conv2d operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-conv2d
-
-testWebNNOperation('conv2d', buildConv2d, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/conv_transpose2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/conv_transpose2d.https.any.js
deleted file mode 100644
index 08c441b5b4..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/conv_transpose2d.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API convTranspose2d operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-convtranspose2d
-
-testWebNNOperation('convTranspose2d', buildConvTranspose2d, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_binary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_binary.https.any.js
deleted file mode 100644
index 8b9fa486f8..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_binary.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API element-wise binary operations
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-binary
-
-testWebNNOperation(['add', 'sub', 'mul', 'div', 'max', 'min', 'pow'], buildOperationWithTwoInputs, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_logical.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_logical.https.any.js
deleted file mode 100644
index 70a887a147..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_logical.https.any.js
+++ /dev/null
@@ -1,20 +0,0 @@
-// META: title=test WebNN API element-wise logical operations
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-logical
-
-testWebNNOperation(
-  [
-    'equal',
-    'greater',
-    'greaterOrEqual',
-    'lesser',
-    'lesserOrEqual',
-  ],
-  buildOperationWithTwoInputs, 'gpu'
-);
-testWebNNOperation('logicalNot', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_unary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_unary.https.any.js
deleted file mode 100644
index 8871129311..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_unary.https.any.js
+++ /dev/null
@@ -1,13 +0,0 @@
-// META: title=test WebNN API element-wise unary operations
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-unary
-
-testWebNNOperation(
-  ['abs', 'ceil', 'cos', 'erf', 'exp', 'floor', 'identity', 'log', 'neg', 'reciprocal', 'sin', 'sqrt', 'tan'],
-  buildOperationWithSingleInput, 'gpu'
-);
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/elu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elu.https.any.js
deleted file mode 100644
index db14442641..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/elu.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API elu operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-elu
-
-testWebNNOperation('elu', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/expand.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/expand.https.any.js
deleted file mode 100644
index f46f463781..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/expand.https.any.js
+++ /dev/null
@@ -1,11 +0,0 @@
-// META: title=test WebNN API expand operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-expand
-
-// reuse buildReshape method
-testWebNNOperation('expand', buildReshape, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/gather.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/gather.https.any.js
deleted file mode 100644
index 8e457192d8..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/gather.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API gather operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-gather
-
-testWebNNOperation('gather', buildOperationWithTwoInputs, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/gemm.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/gemm.https.any.js
deleted file mode 100644
index f288c31bed..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/gemm.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API gemm operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-gemm
-
-testWebNNOperation('gemm', buildGemm, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_sigmoid.https.any.js
deleted file mode 100644
index d40e42a211..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_sigmoid.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API hardSigmoid operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-hard-sigmoid
-
-testWebNNOperation('hardSigmoid', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_swish.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_swish.https.any.js
deleted file mode 100644
index 031e65ee16..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_swish.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API tanh operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-hard-swish
-
-testWebNNOperation('hardSwish', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/instance_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/instance_normalization.https.any.js
deleted file mode 100644
index ecfaac71ee..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/instance_normalization.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API instanceNormalization operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-instancenorm
-
-testWebNNOperation('instanceNormalization', buildLayerNorm, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/layer_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/layer_normalization.https.any.js
deleted file mode 100644
index 0e4f6caebf..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/layer_normalization.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API layerNormalization operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-layernorm
-
-testWebNNOperation('layerNormalization', buildLayerNorm, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/leaky_relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/leaky_relu.https.any.js
deleted file mode 100644
index 9fab2353b9..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/leaky_relu.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API leakyRelu operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-leakyrelu
-
-testWebNNOperation('leakyRelu', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/linear.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/linear.https.any.js
deleted file mode 100644
index ccec2c3eac..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/linear.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API linear operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-linear
-
-testWebNNOperation('linear', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/matmul.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/matmul.https.any.js
deleted file mode 100644
index 635ce84ac6..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/matmul.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API matmul operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-matmul
-
-testWebNNOperation('matmul', buildOperationWithTwoInputs, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/pad.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/pad.https.any.js
deleted file mode 100644
index f313e2c9f9..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/pad.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API pad operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pad
-
-testWebNNOperation('pad', buildPad, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/pooling.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/pooling.https.any.js
deleted file mode 100644
index 837bca2c71..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/pooling.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API pooling operations
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pool2d
-
-testWebNNOperation(['averagePool2d', 'l2Pool2d', 'maxPool2d'], buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/prelu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/prelu.https.any.js
deleted file mode 100644
index 475cd9e5ce..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/prelu.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API prelu operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-prelu
-
-testWebNNOperation('prelu', buildOperationWithTwoInputs, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/reduction.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/reduction.https.any.js
deleted file mode 100644
index 0f3cefa02e..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/reduction.https.any.js
+++ /dev/null
@@ -1,24 +0,0 @@
-// META: title=test WebNN API reduction  operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-reduce
-
-testWebNNOperation(
-  [
-    'reduceL1',
-    'reduceL2',
-    'reduceLogSum',
-    'reduceLogSumExp',
-    'reduceMax',
-    'reduceMean',
-    'reduceMin',
-    'reduceProduct',
-    'reduceSum',
-    'reduceSumSquare',
-  ],
-  buildOperationWithSingleInput, 'gpu'
-);
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/relu.https.any.js
deleted file mode 100644
index d1a35367df..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/relu.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API relu operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-relu
-
-testWebNNOperation('relu', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/resample2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/resample2d.https.any.js
deleted file mode 100644
index dd8e441946..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/resample2d.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API resample2d operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-resample2d-method
-
-testWebNNOperation('resample2d', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/reshape.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/reshape.https.any.js
deleted file mode 100644
index b0217d2e67..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/reshape.https.any.js
+++ /dev/null
@@ -1,11 +0,0 @@
-// META: title=test WebNN API reshape operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-reshape
-
-testWebNNOperation('reshape', buildReshape, 'gpu');
-
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/sigmoid.https.any.js
deleted file mode 100644
index 26116c0ff9..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/sigmoid.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API sigmoid operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-sigmoid
-
-testWebNNOperation('sigmoid', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/slice.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/slice.https.any.js
deleted file mode 100644
index 1710c79a9c..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/slice.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API slice operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-slice
-
-testWebNNOperation('slice', buildSlice, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/softmax.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/softmax.https.any.js
deleted file mode 100644
index 9eaffe2beb..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/softmax.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API softmax operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-softmax
-
-testWebNNOperation('softmax', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/softplus.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/softplus.https.any.js
deleted file mode 100644
index 5f06846113..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/softplus.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API softplus operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-softplus
-
-testWebNNOperation('softplus', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/softsign.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/softsign.https.any.js
deleted file mode 100644
index eac0b7ec40..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/softsign.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API softsign operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-softsign
-
-testWebNNOperation('softsign', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/split.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/split.https.any.js
deleted file mode 100644
index 3b0aafd787..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/split.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API split operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-split
-
-testWebNNOperation('split', buildSplit, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/tanh.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/tanh.https.any.js
deleted file mode 100644
index 3029f4865a..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/tanh.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API tanh operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-tanh
-
-testWebNNOperation('tanh', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/transpose.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/transpose.https.any.js
deleted file mode 100644
index 295ef43ec1..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/transpose.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API transpose operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-transpose
-
-testWebNNOperation('transpose', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/triangular.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/triangular.https.any.js
deleted file mode 100644
index 3e1b0d5ab1..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/triangular.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API triangular operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-triangular
-
-testWebNNOperation('triangular', buildOperationWithSingleInput, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/gpu/where.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/where.https.any.js
deleted file mode 100644
index 49c6cbd4e3..0000000000
--- a/testing/web-platform/tests/webnn/conformance_tests/gpu/where.https.any.js
+++ /dev/null
@@ -1,10 +0,0 @@
-// META: title=test WebNN API where operation
-// META: global=window,dedicatedworker
-// META: script=../../resources/utils.js
-// META: timeout=long
-
-'use strict';
-
-// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-where
-
-testWebNNOperation('where', buildWhere, 'gpu');
-\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conformance_tests/hard_sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/hard_sigmoid.https.any.js
index 8161a24538..55391e7f1c 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/hard_sigmoid.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/hard_sigmoid.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API hardSigmoid operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-hard-sigmoid
 
-testWebNNOperation('hardSigmoid', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('hardSigmoid', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/hard_swish.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/hard_swish.https.any.js
index b4a7c53d8d..24b8c413bb 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/hard_swish.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/hard_swish.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API tanh operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-hard-swish
 
-testWebNNOperation('hardSwish', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('hardSwish', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/instance_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/instance_normalization.https.any.js
index fce879172e..fc339e5bab 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/instance_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/instance_normalization.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API instanceNormalization operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-instancenorm
 
-testWebNNOperation('instanceNormalization', buildLayerNorm);
-\ No newline at end of file
+runWebNNConformanceTests('instanceNormalization', buildLayerNorm);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/layer_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/layer_normalization.https.any.js
index ab8a50cc03..ea3cd04240 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/layer_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/layer_normalization.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API layerNormalization operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-layernorm
 
-testWebNNOperation('layerNormalization', buildLayerNorm);
-\ No newline at end of file
+runWebNNConformanceTests('layerNormalization', buildLayerNorm);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/leaky_relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/leaky_relu.https.any.js
index 2b6f17e95d..b2a4055bde 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/leaky_relu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/leaky_relu.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API leakyRelu operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-leakyrelu
 
-testWebNNOperation('leakyRelu', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('leakyRelu', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/linear.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/linear.https.any.js
index 465b697f29..0e22f7a036 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/linear.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/linear.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API linear operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-linear
 
-testWebNNOperation('linear', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('linear', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/matmul.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/matmul.https.any.js
index 64eeb37f08..da78230579 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/matmul.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/matmul.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API matmul operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-matmul
 
-testWebNNOperation('matmul', buildOperationWithTwoInputs);
-\ No newline at end of file
+runWebNNConformanceTests('matmul', buildOperationWithTwoInputs);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/pad.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/pad.https.any.js
index f1a2400d1c..d733cbb6ed 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/pad.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/pad.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API pad operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pad
 
-testWebNNOperation('pad', buildPad);
-\ No newline at end of file
+runWebNNConformanceTests('pad', buildPad);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/parallel-compute.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/parallel-compute.https.any.js
new file mode 100644
index 0000000000..642fec9f73
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/parallel-compute.https.any.js
@@ -0,0 +1,19 @@
+// META: title=test parallel WebNN API compute operations
+// META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
+// META: script=../resources/utils.js
+// META: timeout=long
+
+'use strict';
+
+// https://webmachinelearning.github.io/webnn/#api-mlcontext-compute
+
+if (navigator.ml) {
+  testParallelCompute();
+} else {
+  // Show indication to users why the test failed
+  test(
+      () => assert_not_equals(
+          navigator.ml, undefined, 'ml property is defined on navigator'));
+}
diff --git a/testing/web-platform/tests/webnn/conformance_tests/pooling.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/pooling.https.any.js
index 400d5ed37d..de2ae35a9c 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/pooling.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/pooling.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API pooling operations
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,5 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pool2d
 
-testWebNNOperation(['averagePool2d', 'l2Pool2d', 'maxPool2d'], buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests(
+    ['averagePool2d', 'l2Pool2d', 'maxPool2d'], buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/prelu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/prelu.https.any.js
index 83cc9db4b4..9337211e54 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/prelu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/prelu.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API prelu operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-prelu
 
-testWebNNOperation('prelu', buildOperationWithTwoInputs);
-\ No newline at end of file
+runWebNNConformanceTests('prelu', buildOperationWithTwoInputs);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduction.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduction.https.any.js
index 30bfb4ba7a..c291906ba1 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/reduction.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/reduction.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API reduction  operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,18 +9,17 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-reduce
 
-testWebNNOperation(
-  [
-    'reduceL1',
-    'reduceL2',
-    'reduceLogSum',
-    'reduceLogSumExp',
-    'reduceMax',
-    'reduceMean',
-    'reduceMin',
-    'reduceProduct',
-    'reduceSum',
-    'reduceSumSquare',
-  ],
-  buildOperationWithSingleInput
-);
-\ No newline at end of file
+runWebNNConformanceTests(
+    [
+      'reduceL1',
+      'reduceL2',
+      'reduceLogSum',
+      'reduceLogSumExp',
+      'reduceMax',
+      'reduceMean',
+      'reduceMin',
+      'reduceProduct',
+      'reduceSum',
+      'reduceSumSquare',
+    ],
+    buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/relu.https.any.js
index 51e427898f..7cb23eea1b 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/relu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/relu.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API relu operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-relu
 
-testWebNNOperation('relu', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('relu', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/resample2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/resample2d.https.any.js
index 0b5b3e0032..b5bdda7197 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/resample2d.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/resample2d.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API resample2d operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-resample2d-method
 
-testWebNNOperation('resample2d', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('resample2d', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reshape.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reshape.https.any.js
index c0dafb176c..a7d03b2a0c 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/reshape.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/reshape.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API reshape operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,5 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-reshape
 
-testWebNNOperation('reshape', buildReshape);
-
+runWebNNConformanceTests('reshape', buildReshape);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/sigmoid.https.any.js
index 186f468918..9730b548b5 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/sigmoid.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/sigmoid.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API sigmoid operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-sigmoid
 
-testWebNNOperation('sigmoid', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('sigmoid', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/slice.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/slice.https.any.js
index 6441204517..b316ea58c4 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/slice.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/slice.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API slice operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-slice
 
-testWebNNOperation('slice', buildSlice);
-\ No newline at end of file
+runWebNNConformanceTests('slice', buildSlice);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
index 143b7d969f..a68a32c45f 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API softmax operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-softmax
 
-testWebNNOperation('softmax', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('softmax', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/softplus.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/softplus.https.any.js
index fcd6410bdb..7d89b117eb 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/softplus.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/softplus.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API softplus operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-softplus
 
-testWebNNOperation('softplus', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('softplus', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/softsign.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/softsign.https.any.js
index 6e26afdade..e175e0de56 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/softsign.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/softsign.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API softsign operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-softsign
 
-testWebNNOperation('softsign', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('softsign', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/split.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/split.https.any.js
index 0de6cb4d8d..78d707687f 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/split.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/split.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API split operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-split
 
-testWebNNOperation('split', buildSplit);
-\ No newline at end of file
+runWebNNConformanceTests('split', buildSplit);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/tanh.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/tanh.https.any.js
index c5d1f86ab1..e3ab5e9192 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/tanh.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/tanh.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API tanh operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-tanh
 
-testWebNNOperation('tanh', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('tanh', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/transpose.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/transpose.https.any.js
index 746e53d512..83bd7a45c1 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/transpose.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/transpose.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API transpose operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-transpose
 
-testWebNNOperation('transpose', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('transpose', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/triangular.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/triangular.https.any.js
index 503f310620..499f60ed36 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/triangular.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/triangular.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API triangular operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-triangular
 
-testWebNNOperation('triangular', buildOperationWithSingleInput);
-\ No newline at end of file
+runWebNNConformanceTests('triangular', buildOperationWithSingleInput);
diff --git a/testing/web-platform/tests/webnn/conformance_tests/where.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/where.https.any.js
index 7926221d3a..4ab453ab24 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/where.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/where.https.any.js
@@ -1,5 +1,7 @@
 // META: title=test WebNN API where operation
 // META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
 // META: script=../resources/utils.js
 // META: timeout=long
 
@@ -7,4 +9,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-where
 
-testWebNNOperation('where', buildWhere);
-\ No newline at end of file
+runWebNNConformanceTests('where', buildWhere);
diff --git a/testing/web-platform/tests/webnn/resources/test_data/arg_max.json b/testing/web-platform/tests/webnn/resources/test_data/arg_max.json
index d2fe9e62ca..348a54dc24 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/arg_max.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/arg_max.json
@@ -460,7 +460,7 @@
         }
       },
       "options": {
-        "keepDimensions": true
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
diff --git a/testing/web-platform/tests/webnn/resources/test_data/arg_min.json b/testing/web-platform/tests/webnn/resources/test_data/arg_min.json
index 132a2dc3e8..330afbc710 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/arg_min.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/arg_min.json
@@ -460,7 +460,7 @@
         }
       },
       "options": {
-        "keepDimensions": true
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
diff --git a/testing/web-platform/tests/webnn/resources/test_data/matmul.json b/testing/web-platform/tests/webnn/resources/test_data/matmul.json
index f3a03e442e..cc1789ee25 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/matmul.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/matmul.json
@@ -1,332 +1,6 @@
 {
   "tests": [
     {
-      "name": "matmul float32 constant 1D and 1D tensors all positive produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32",
-          "constant": true
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            27.829805134194842,
-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32",
-          "constant": true
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": 7458.89013671875,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 1D tensors all positive produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            27.829805134194842,
-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": 7458.89013671875,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 1D tensors all negative produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            -86.60583871803968,
-            -94.74202421330796,
-            -86.16720380573273,
-            -76.0215630990851
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            -21.22328469397374,
-            -56.66441199254357,
-            -77.66753889428908,
-            -56.55797454862353
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": 18198.58203125,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 positive 1D and negative 1D tensors produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            -21.22328469397374,
-            -56.66441199254357,
-            -77.66753889428908,
-            -56.55797454862353
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": -7069.85546875,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 negative 1D and positive 1D tensors produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            -86.60583871803968,
-            -94.74202421330796,
-            -86.16720380573273,
-            -76.0215630990851
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            27.829805134194842,
-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": -19578.140625,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 2D tensors",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4, 5],
-          "data": [
-            88.17004408170853,
-            78.40126706348094,
-            14.819002753540623,
-            3.692303791736573,
-            45.9064286713635,
-            43.08391896733015,
-            47.19946845924572,
-            60.925216107016425,
-            8.162760351602216,
-            20.33326305093228,
-            20.438397895943282,
-            27.01940859922867,
-            15.601424432184263,
-            87.46969388883927,
-            65.79554455585657,
-            69.31696864490797,
-            31.984439910782992,
-            12.291812891860388,
-            13.304834654547172,
-            85.26705387930089
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [1, 5],
-        "data": [
-          8602.796875,
-          7075.7802734375,
-          3083.654052734375,
-          3881.228271484375,
-          8131.462890625
-        ],
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 4D tensors",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [2, 2, 4, 2],
-          "data": [
-            71.54684436671175,
-            78.61926127874348,
-            2.246814764541316,
-            12.044773359659434,
-            1.8342867333124069,
-            82.09732511549477,
-            43.884761946067094,
-            5.616231825100204,
-            34.67424097413332,
-            49.152710076333506,
-            75.34904358690912,
-            84.74523302920429,
-            36.56497325521975,
-            22.89479672718755,
-            15.02636975800511,
-            66.49530785246675,
-            65.81345056776044,
-            26.749681209347376,
-            19.415639234175774,
-            98.60692665127114,
-            65.39448996549784,
-            56.47023672202065,
-            80.64523905250766,
-            82.20401464839868,
-            70.84606482516416,
-            50.27994995977012,
-            67.39406108056262,
-            75.35806805146241,
-            2.7487208784167327,
-            68.0645872775828,
-            70.73791158057968,
-            46.26436742398676
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [2, 2, 1, 2],
-        "data": [
-          5293.36376953125,
-          7255.7626953125,
-          5224.80322265625,
-          7556.21142578125,
-          8926.5361328125,
-          8476.359375,
-          7713.62158203125,
-          8234.0224609375
-        ],
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 2D and 1D tensors",
-      "inputs": {
-        "a": {
-          "shape": [5, 4],
-          "data": [
-            88.17004408170853,
-            43.08391896733015,
-            20.438397895943282,
-            69.31696864490797,
-            78.40126706348094,
-            47.19946845924572,
-            27.01940859922867,
-            31.984439910782992,
-            14.819002753540623,
-            60.925216107016425,
-            15.601424432184263,
-            12.291812891860388,
-            3.692303791736573,
-            8.162760351602216,
-            87.46969388883927,
-            13.304834654547172,
-            45.9064286713635,
-            20.33326305093228,
-            65.79554455585657,
-            85.26705387930089
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [5, 1],
-        "data": [
-          8602.796875,
-          7075.7802734375,
-          3083.654052734375,
-          3881.228271484375,
-          8131.462890625
-        ],
-        "type": "float32"
-      }
-    },
-    {
       "name": "matmul float32 2D and 2D tensors",
       "inputs": {
         "a": {
@@ -750,64 +424,6 @@
       }
     },
     {
-      "name": "matmul float32 3D and 1D tensors",
-      "inputs": {
-        "a": {
-          "shape": [2, 3, 4],
-          "data": [
-            56.46701250066562,
-            99.86045478237251,
-            71.05493372292567,
-            32.45438455331333,
-            17.310747999630017,
-            2.586275053048559,
-            92.31499166302054,
-            96.9758519231732,
-            26.4721315276526,
-            77.67031776320978,
-            29.278788710989147,
-            82.12142428847062,
-            89.89308471484885,
-            82.49795321217854,
-            64.36866008901963,
-            23.75928513568486,
-            6.67026681065197,
-            81.55583129445503,
-            16.142963270263433,
-            57.45134849716054,
-            26.82641739603182,
-            85.0296980735713,
-            36.198863464757956,
-            89.60960360138286
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            27.829805134194842,
-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [2, 3, 1],
-        "data": [
-          15019.9462890625,
-          11942.376953125,
-          15035.0322265625,
-          13553.013671875,
-          12302.328125,
-          16517.9765625
-        ],
-        "type": "float32"
-      }
-    },
-    {
       "name": "matmul float32 4D and 4D (broadcast) tensors",
       "inputs": {
         "a": {
diff --git a/testing/web-platform/tests/webnn/resources/test_data/prelu.json b/testing/web-platform/tests/webnn/resources/test_data/prelu.json
index cf79bee7a9..14a7c412dd 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/prelu.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/prelu.json
@@ -1,6 +1,34 @@
 {
   "tests": [
     {
+      "name": "prelu float32 0D scalar",
+      "inputs": {
+        "x": {
+          "shape": [],
+          "data": [
+            -4.794857500523286
+          ],
+          "type": "float32"
+        },
+        "slope": {
+          "shape": [],
+          "data": [
+            1.1202747481570352
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [],
+        "data": [
+          -5.371557712554932
+        ],
+        "type": "float32"
+      }
+    },
+    {
       "name": "prelu float32 1D constant tensors",
       "inputs": {
         "x": {
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json
index 7cbc442511..c3f2b618e9 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           108.43173217773438,
           315.6007995605469,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json
index 7e59a45d5e..d83eea9dfb 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           138.580078125,
           166.67791748046875,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum.json
index 250398d227..061e12ad51 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum.json
@@ -596,7 +596,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -645,11 +646,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           5.7273993492126465,
           5.64375114440918,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum_exp.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum_exp.json
index b7f39abd52..3577d6aa9e 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum_exp.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum_exp.json
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           8.563796997070312,
           5.500619411468506,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json
index 967aea8bf4..11ed0ed919 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json
@@ -556,7 +556,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -605,11 +606,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           90.42288208007812,
           94.99645233154297,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json
index 5a48952c06..8c26d0a562 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json
@@ -670,7 +670,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "shape": [2, 2],
@@ -718,10 +719,11 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           52.287559509277344,
           45.10261917114258,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json
index 92de75e92a..6c26df5db1 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json
@@ -556,7 +556,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -605,11 +606,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           -87.9623031616211,
           -53.747413635253906,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json
index 691bf4da9b..d58af30ec1 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json
@@ -556,7 +556,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -605,11 +606,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           -3638925568,
           6523364352,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json
index df47a1a2b2..7027d38b67 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json
@@ -670,7 +670,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "shape": [2, 2],
@@ -718,10 +719,11 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           355.21942138671875,
           185.98255920410156,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_sum_square.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum_square.json
index 8ac373e4b3..bd2ebb341a 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_sum_square.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum_square.json
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           12302.474609375,
           22772.77734375,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/softplus.json b/testing/web-platform/tests/webnn/resources/test_data/softplus.json
index eb05b7b281..373612d5ca 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/softplus.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/softplus.json
@@ -1,7 +1,7 @@
-{ // softplus: The calculation follows the expression ln(1 + exp(steepness * x)) / steepness.
+{ // softplus: The calculation follows the expression ln(1 + exp(x)).
   "tests": [
     {
-      "name": "softplus float32 1D constant tensor default options", // default options: {steepness: 1}
+      "name": "softplus float32 1D constant tensor",
       "inputs": {
         "x": {
           "shape": [24],
@@ -68,7 +68,7 @@
      }
     },
     {
-      "name": "softplus float32 1D tensor default options", // default options: {steepness: 1}
+      "name": "softplus float32 1D tensor",
       "inputs": {
         "x": {
           "shape": [24],
@@ -134,7 +134,7 @@
      }
     },
     {
-      "name": "softplus float32 2D tensor default options",
+      "name": "softplus float32 2D tensor",
       "inputs": {
         "x": {
           "shape": [4, 6],
@@ -200,7 +200,7 @@
      }
     },
     {
-      "name": "softplus float32 3D tensor default options",
+      "name": "softplus float32 3D tensor",
       "inputs": {
         "x": {
           "shape": [2, 3, 4],
@@ -266,7 +266,7 @@
      }
     },
     {
-      "name": "softplus float32 4D tensor default options",
+      "name": "softplus float32 4D tensor",
       "inputs": {
         "x": {
           "shape": [1, 2, 3, 4],
@@ -332,7 +332,7 @@
      }
     },
     {
-      "name": "softplus float32 5D tensor default options",
+      "name": "softplus float32 5D tensor",
       "inputs": {
         "x": {
           "shape": [1, 2, 1, 3, 4],
@@ -396,144 +396,6 @@
         ],
         "type": "float32"
      }
-    },
-    {
-      "name": "softplus both positive float32 4D tensor and options.steepness",
-      "inputs": {
-        "x": {
-          "shape": [1, 2, 3, 4],
-          "data": [
-            5.626614582460632,
-            5.167487045486892,
-            4.0146356193402655,
-            9.48003299650489,
-            9.989938045769978,
-            7.0654412821434125,
-            2.132681001794825,
-            8.187151346059956,
-            5.169976220175496,
-            2.1044997879382077,
-            3.523329401138895,
-            4.136340646976668,
-            1.7418719794295656,
-            5.145224066290767,
-            5.015515309165462,
-            0.045903935074711466,
-            2.9570898924917377,
-            3.959244712098706,
-            5.517926978255181,
-            7.192322388417094,
-            8.76492480390928,
-            1.3734704039113388,
-            8.930669016709397,
-            8.660283210871246
-          ],
-          "type": "float32"
-        }
-      },
-      "options": {
-        "steepness": 1.5104469060897827
-      },
-      "expected": {
-        "name": "output",
-        "shape": [1, 2, 3, 4],
-        "data": [
-          5.626749515533447,
-          5.167757034301758,
-          4.016173362731934,
-          9.480032920837402,
-          9.989937782287598,
-          7.065456390380859,
-          2.158585548400879,
-          8.187153816223145,
-          5.170245170593262,
-          2.1315081119537354,
-          3.526555061340332,
-          4.137620449066162,
-          1.7879058122634888,
-          5.145503044128418,
-          5.015854835510254,
-          0.4822517931461334,
-          2.964651584625244,
-          3.960916519165039,
-          5.518085956573486,
-          7.19233512878418,
-          8.764925956726074,
-          1.4518096446990967,
-          8.930669784545898,
-          8.660284042358398
-        ],
-        "type": "float32"
-     }
-    },
-    {
-      "name": "softplus both negative float32 4D tensor and options.steepness",
-      "inputs": {
-        "x": {
-          "shape": [1, 2, 3, 4],
-          "data": [
-            -5.584833476104802,
-            -8.188738740810354,
-            -8.981280004134987,
-            -1.7315531899284586,
-            -0.7266543578958906,
-            -0.0034800119290885334,
-            -7.378389455552106,
-            -8.907525953796949,
-            -6.0483786568116304,
-            -6.328561142365743,
-            -2.6006513567654626,
-            -5.02005264196455,
-            -2.0647716093484414,
-            -1.5499896740695434,
-            -2.221591675966657,
-            -1.1088025713211636,
-            -2.7854626064634385,
-            -2.105037489961294,
-            -5.144277741727352,
-            -5.081219916574497,
-            -7.499426297617635,
-            -2.4305558382286545,
-            -8.390520024268328,
-            -0.07117499202643174
-          ],
-          "type": "float32"
-        }
-      },
-      "options": {
-        "steepness": -1.2985155767552126
-      },
-      "expected": {
-        "name": "output",
-        "shape": [1, 2, 3, 4],
-        "data": [
-          -5.585379123687744,
-          -8.188756942749023,
-          -8.981287002563477,
-          -1.8088372945785522,
-          -0.9798305630683899,
-          -0.5355416536331177,
-          -7.378442287445068,
-          -8.907533645629883,
-          -6.048677444458008,
-          -6.328769207000732,
-          -2.626511573791504,
-          -5.021188259124756,
-          -2.1157851219177246,
-          -1.6465802192687988,
-          -2.2634570598602295,
-          -1.2725814580917358,
-          -2.805877923965454,
-          -2.1535322666168213,
-          -5.145244121551514,
-          -5.082269191741943,
-          -7.499471664428711,
-          -2.4626762866973877,
-          -8.390534400939941,
-          -0.5702091455459595
-        ],
-        "type": "float32"
-     }
     }
   ]
 }
 \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/utils.js b/testing/web-platform/tests/webnn/resources/utils.js
index d1dc0675a7..e5b80ae9f7 100644
--- a/testing/web-platform/tests/webnn/resources/utils.js
+++ b/testing/web-platform/tests/webnn/resources/utils.js
@@ -13,6 +13,15 @@ const TypedArrayDict = {
   int64: BigInt64Array,
 };
 
+const kContextOptionsForVariant = {
+  cpu: {
+    deviceType: 'cpu',
+  },
+  gpu: {
+    deviceType: 'gpu',
+  }
+};
+
 // The maximum index to validate for the output's expected value.
 const kMaximumIndexToValidate = 1000;
 
@@ -867,17 +876,15 @@ const run = async (operationName, context, builder, resources, buildFunc) => {
   checkResults(operationName, namedOutputOperands, result.outputs, resources);
 };
 
+const variant = location.search.substring(1);
+const contextOptions = kContextOptionsForVariant[variant];
+
 /**
  * Run WebNN operation tests.
  * @param {(String[]|String)} operationName - An operation name array or an operation name
  * @param {Function} buildFunc - A build function for an operation
- * @param {String} deviceType - The execution device type for this test
  */
-const testWebNNOperation = (operationName, buildFunc, deviceType = 'cpu') => {
-  test(() => assert_not_equals(navigator.ml, undefined, "ml property is defined on navigator"));
-  if (navigator.ml === undefined) {
-    return;
-  }
+const testWebNNOperation = (operationName, buildFunc) => {
   let operationNameArray;
   if (typeof operationName === 'string') {
     operationNameArray = [operationName];
@@ -890,7 +897,14 @@ const testWebNNOperation = (operationName, buildFunc, deviceType = 'cpu') => {
   operationNameArray.forEach((subOperationName) => {
     const tests = loadTests(subOperationName);
     promise_setup(async () => {
-      context = await navigator.ml.createContext({deviceType});
+      let supported = false;
+      try {
+        context = await navigator.ml.createContext(contextOptions);
+        supported = true;
+      } catch (e) {
+      }
+      assert_implements(
+          supported, `Unable to create context for ${variant} variant`);
       builder = new MLGraphBuilder(context);
     });
     for (const subTest of tests) {
@@ -901,6 +915,65 @@ const testWebNNOperation = (operationName, buildFunc, deviceType = 'cpu') => {
   });
 };
 
+/**
+ * WebNN parallel compute operation test.
+ */
+const testParallelCompute = () => {
+  let ml_context;
+  let ml_graph;
+
+  promise_setup(async () => {
+    let supported = false;
+    try {
+      ml_context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
+    // Construct a simple graph: A = B * 2.
+    const builder = new MLGraphBuilder(ml_context);
+    const operandType = {dataType: 'float32', dimensions: [1]};
+    const input_operand = builder.input('input', operandType);
+    const const_operand = builder.constant(operandType, Float32Array.from([2]));
+    const output_operand = builder.mul(input_operand, const_operand);
+    ml_graph = await builder.build({'output': output_operand});
+  });
+
+  promise_test(async () => {
+    const test_inputs = [1, 2, 3, 4];
+
+    const actual_outputs = await Promise.all(test_inputs.map(async (input) => {
+      let inputs = {'input': Float32Array.from([input])};
+      let outputs = {'output': new Float32Array(1)};
+      ({inputs, outputs} = await ml_context.compute(ml_graph, inputs, outputs));
+      return outputs.output[0];
+    }));
+
+    const expected_outputs = [2, 4, 6, 8];
+    assert_array_equals(actual_outputs, expected_outputs);
+  });
+};
+
+/**
+ * Run WebNN conformance tests by specified operation.
+ * @param {(String[]|String)} operationName - An operation name array or an
+ *     operation name
+ * @param {Function} buildFunc - A build function for an operation
+ */
+const runWebNNConformanceTests = (operationName, buildFunc) => {
+  // Link to https://github.com/web-platform-tests/wpt/pull/44883
+  // Check navigator.ml is defined before trying to run WebNN tests
+  if (navigator.ml) {
+    testWebNNOperation(operationName, buildFunc);
+  } else {
+    // Show indication to users why the test failed
+    test(
+        () => assert_not_equals(
+            navigator.ml, undefined, 'ml property is defined on navigator'));
+  }
+};
+
 // ref: http://stackoverflow.com/questions/32633585/how-do-you-convert-to-half-floats-in-javascript
 const toHalf = (value) => {
   let floatView = new Float32Array(1);
@@ -970,13 +1043,19 @@ const createBuffer = (context, bufferSize) => {
 /**
  * WebNN destroy buffer twice test.
  * @param {String} testName - The name of the test operation.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testDestroyWebNNBuffer = (testName, deviceType = 'cpu') => {
+const testDestroyWebNNBuffer = (testName) => {
   let context;
   let buffer;
   promise_setup(async () => {
-    context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
     buffer = createBuffer(context, 4);
   });
   promise_test(async () => {
@@ -993,12 +1072,19 @@ const testDestroyWebNNBuffer = (testName, deviceType = 'cpu') => {
  * WebNN create buffer test.
  * @param {String} testName - The name of the test operation.
  * @param {Number} bufferSize - Size of the buffer to create, in bytes.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testCreateWebNNBuffer = (testName, bufferSize, deviceType = 'cpu') => {
+const testCreateWebNNBuffer = (testName, bufferSize) => {
   let context;
+
   promise_setup(async () => {
-      context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
   });
   promise_test(async () => {
     createBuffer(context, bufferSize);
@@ -1021,12 +1107,18 @@ const assert_buffer_data_equals = async (ml_context, ml_buffer, expected) => {
 /**
  * WebNN write buffer operation test.
  * @param {String} testName - The name of the test operation.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testWriteWebNNBuffer = (testName, deviceType = 'cpu') => {
+const testWriteWebNNBuffer = (testName) => {
   let ml_context;
   promise_setup(async () => {
-    ml_context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      ml_context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
   });
 
   promise_test(async () => {
@@ -1117,7 +1209,7 @@ const testWriteWebNNBuffer = (testName, deviceType = 'cpu') => {
       return;
     }
 
-    let another_ml_context = await navigator.ml.createContext({deviceType});
+    let another_ml_context = await navigator.ml.createContext(contextOptions);
     let another_ml_buffer = createBuffer(another_ml_context, ml_buffer.size);
 
     let input_data = new Uint8Array(ml_buffer.size).fill(0xAA);
@@ -1131,12 +1223,18 @@ const testWriteWebNNBuffer = (testName, deviceType = 'cpu') => {
 /**
  * WebNN read buffer operation test.
  * @param {String} testName - The name of the test operation.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testReadWebNNBuffer = (testName, deviceType = 'cpu') => {
+const testReadWebNNBuffer = (testName) => {
   let ml_context;
   promise_setup(async () => {
-    ml_context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      ml_context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
   });
 
   promise_test(async t => {
@@ -1277,7 +1375,7 @@ const testReadWebNNBuffer = (testName, deviceType = 'cpu') => {
       return;
     }
 
-    let another_ml_context = await navigator.ml.createContext({deviceType});
+    let another_ml_context = await navigator.ml.createContext(contextOptions);
     let another_ml_buffer = createBuffer(another_ml_context, ml_buffer.size);
 
     await promise_rejects_js(
diff --git a/testing/web-platform/tests/webnn/validation_tests/clamp.https.any.js b/testing/web-platform/tests/webnn/validation_tests/clamp.https.any.js
index 85cd19a566..126fa90e16 100644
--- a/testing/web-platform/tests/webnn/validation_tests/clamp.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/clamp.https.any.js
@@ -5,3 +5,56 @@
 'use strict';
 
 validateInputFromAnotherBuilder('clamp');
+
+validateUnaryOperation(
+    'clamp', allWebNNOperandDataTypes, /*alsoBuildActivation=*/ true);
+
+promise_test(async t => {
+  const options = {minValue: 1.0, maxValue: 3.0};
+  const input =
+      builder.input('input', {dataType: 'uint32', dimensions: [1, 2, 3]});
+  const output = builder.clamp(input, options);
+  assert_equals(output.dataType(), 'uint32');
+  assert_array_equals(output.shape(), [1, 2, 3]);
+}, '[clamp] Test building an operator with options');
+
+promise_test(async t => {
+  const options = {minValue: 0, maxValue: 0};
+  const input =
+      builder.input('input', {dataType: 'int32', dimensions: [1, 2, 3, 4]});
+  const output = builder.clamp(input, options);
+  assert_equals(output.dataType(), 'int32');
+  assert_array_equals(output.shape(), [1, 2, 3, 4]);
+}, '[clamp] Test building an operator with options.minValue == options.maxValue');
+
+promise_test(async t => {
+  const options = {minValue: 2.0};
+  builder.clamp(options);
+}, '[clamp] Test building an activation with options');
+
+promise_test(async t => {
+  const options = {minValue: 3.0, maxValue: 1.0};
+  const input =
+      builder.input('input', {dataType: 'uint8', dimensions: [1, 2, 3]});
+  assert_throws_js(TypeError, () => builder.clamp(input, options));
+}, '[clamp] Throw if options.minValue > options.maxValue when building an operator');
+
+// To be removed once infinite `minValue` is allowed. Tracked in
+// https://github.com/webmachinelearning/webnn/pull/647.
+promise_test(async t => {
+  const options = {minValue: -Infinity};
+  const input = builder.input('input', {dataType: 'float16', dimensions: []});
+  assert_throws_js(TypeError, () => builder.clamp(input, options));
+}, '[clamp] Throw if options.minValue is -Infinity when building an operator');
+
+promise_test(async t => {
+  const options = {minValue: 2.0, maxValue: -1.0};
+  assert_throws_js(TypeError, () => builder.clamp(options));
+}, '[clamp] Throw if options.minValue > options.maxValue when building an activation');
+
+// To be removed once NaN `maxValue` is allowed. Tracked in
+// https://github.com/webmachinelearning/webnn/pull/647.
+promise_test(async t => {
+  const options = {maxValue: NaN};
+  assert_throws_js(TypeError, () => builder.clamp(options));
+}, '[clamp] Throw if options.maxValue is NaN when building an activation');
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));
diff --git a/testing/web-platform/tests/webnn/validation_tests/convTranspose2d.https.any.js b/testing/web-platform/tests/webnn/validation_tests/convTranspose2d.https.any.js
index c14f445bf3..02822c5274 100644
--- a/testing/web-platform/tests/webnn/validation_tests/convTranspose2d.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/convTranspose2d.https.any.js
@@ -57,3 +57,473 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   assert_throws_js(
       TypeError, () => builder.convTranspose2d(input, filter, options));
 }, '[convTranspose2d] throw if activation option is from another builder');
+
+const tests = [
+  {
+    name: '[convTranspose2d] Test with default options.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    output: {dataType: 'float32', dimensions: [1, 1, 5, 5]}
+  },
+  {
+    name:
+        '[convTranspose2d] Test with inputLayout="nchw" and filterLayout="hwoi".',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [3, 3, 2, 1]},
+    options: {
+      filterLayout: 'hwoi',
+      inputLayout: 'nchw',
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 5, 5]}
+  },
+  {
+    name:
+        '[convTranspose2d] Test with inputLayout="nchw" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      filterLayout: 'ohwi',
+      inputLayout: 'nchw',
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 5, 5]}
+  },
+  {
+    name:
+        '[convTranspose2d] Test with inputLayout="nhwc" and filterLayout="iohw".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 1]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      filterLayout: 'iohw',
+      inputLayout: 'nhwc',
+    },
+    output: {dataType: 'float32', dimensions: [1, 5, 5, 2]}
+  },
+  {
+    name:
+        '[convTranspose2d] Test with inputLayout="nhwc" and filterLayout="hwoi".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 1]},
+    filter: {dataType: 'float32', dimensions: [3, 3, 2, 1]},
+    options: {
+      filterLayout: 'hwoi',
+      inputLayout: 'nhwc',
+    },
+    output: {dataType: 'float32', dimensions: [1, 5, 5, 2]}
+  },
+  {
+    name:
+        '[convTranspose2d] Test with inputLayout="nhwc" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 1]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      filterLayout: 'ohwi',
+      inputLayout: 'nhwc',
+    },
+    output: {dataType: 'float32', dimensions: [1, 5, 5, 2]}
+  },
+  {
+    name: '[convTranspose2d] Test with strides=[3, 2], outputSizes=[10, 8].',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      strides: [3, 2],
+      outputSizes: [10, 8],
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 10, 8]}
+  },
+  {
+    name: '[convTranspose2d] Test with strides=[3, 2], outputPadding=[1, 1].',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      strides: [3, 2],
+      outputPadding: [1, 1],
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 10, 8]}
+  },
+  {
+    name: '[convTranspose2d] Test with padding=1.',
+    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: '[convTranspose2d] Test with padding=1, groups=3.',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [1, 1, 1, 1],
+      groups: 3,
+    },
+    output: {dataType: 'float32', dimensions: [1, 3, 5, 5]}
+  },
+  {
+    name: '[convTranspose2d] Test with strides=2.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      strides: [2, 2],
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 7, 7]}
+  },
+  {
+    name: '[convTranspose2d] Test with strides=2 and padding=1.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [1, 1, 1, 1],
+      strides: [2, 2],
+    },
+    output: {dataType: 'float32', dimensions: [1, 1, 5, 5]}
+  },
+  {
+    name:
+        '[convTranspose2d] Test when the output sizes are explicitly specified, the output padding values are ignored though padding value is not smaller than stride along the same axis.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      outputPadding: [3, 3],
+      strides: [3, 2],
+      outputSizes: [10, 8],
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 10, 8]}
+  },
+  {
+    name: '[convTranspose2d] Throw if the input is not a 4-D tensor.',
+    input: {dataType: 'float32', dimensions: [1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+  },
+  {
+    name:
+        '[convTranspose2d] 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: '[convTranspose2d] 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:
+        '[convTranspose2d] 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: '[convTranspose2d] 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: '[convTranspose2d] 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: '[convTranspose2d] Throw if one stride value 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: '[convTranspose2d] 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:
+        '[convTranspose2d] Throw if the one dilation value 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:
+        '[convTranspose2d] Throw if the input channels is not equal to the filter input channels with inputLayout="nchw" and filterLayout="iohw".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      filterLayout: 'iohw',
+      inputLayout: 'nchw',
+      groups: 1,
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the input channels is not equal to the filter input channels with inputLayout="nchw" and filterLayout="hwoi".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [3, 1, 2, 1]},
+    options: {
+      filterLayout: 'hwoi',
+      inputLayout: 'nchw',
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the input channels is not equal to the filter input channels with inputLayout="nchw" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      filterLayout: 'ohwi',
+      inputLayout: 'nchw',
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the input channels is not equal to the filter input channels with inputLayout="nhwc" and filterLayout="iohw".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      filterLayout: 'iohw',
+      inputLayout: 'nhwc',
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the input channels is not equal to the filter input channels inputLayout="nhwc" and filterLayout="hwoi".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 2]},
+    filter: {dataType: 'float32', dimensions: [3, 3, 2, 1]},
+    options: {
+      filterLayout: 'hwoi',
+      inputLayout: 'nhwc',
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the input channels is not equal to the filter input channels with inputLayout="nhwc" and filterLayout="ohwi".',
+    input: {dataType: 'float32', dimensions: [1, 3, 3, 2]},
+    filter: {dataType: 'float32', dimensions: [2, 3, 3, 1]},
+    options: {
+      filterLayout: 'ohwi',
+      inputLayout: 'nhwc',
+    },
+  },
+  {
+    name: '[convTranspose2d] Throw if output channels is too large.',
+    input: {dataType: 'float32', dimensions: [1, 4, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [4, 2, 2, 2]},
+    options: {
+      groups: kMaxUnsignedLong,
+    },
+  },
+  {
+    name: '[convTranspose2d] 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:
+        '[convTranspose2d] 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: [328443, 1],
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] 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:
+        '[convTranspose2d] 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, 2]},
+    options: {
+      dilations: [kMaxUnsignedLong, 1],
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] 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, 2]},
+    options: {
+      dilations: [1, kMaxUnsignedLong],
+    },
+  },
+  {
+    name: '[convTranspose2d] 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:
+        '[convTranspose2d] Throw if the bias shape is not equal to [output_channels] with filterLayout="iohw".',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    options: {
+      filterLayout: 'iohw',
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the bias shape is not equal to [output_channels] with filterLayout="hwoi".',
+    input: {dataType: 'float32', dimensions: [1, 1, 5, 5]},
+    filter: {dataType: 'float32', dimensions: [2, 2, 1, 1]},
+    options: {
+      filterLayout: 'hwoi',
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] 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: {
+      filterLayout: 'ohwi',
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] 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:
+        '[convTranspose2d] Throw if the outputPadding is not a sequence of length 2.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      strides: [3, 2],
+      outputPadding: [1, 1, 1, 1],
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the outputPadding is not smaller than stride along the width dimension.',
+    input: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [0, 0, 3, 3],
+      strides: [2, 2],
+      outputPadding: [0, 2],
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the outputPadding is not smaller than stride along the height dimension.',
+    input: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [0, 0, 3, 3],
+      strides: [2, 2],
+      outputPadding: [2, 0],
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw if the outputSizes is not a sequence of length 2.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 2, 3, 3]},
+    options: {
+      strides: [3, 2],
+      outputSizes: [1, 2, 10, 8],
+    },
+  },
+  {
+    name: '[convTranspose2d] Throw if the padding height is too large.',
+    input: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [4, 4, 0, 0],
+      strides: [2, 2],
+      outputPadding: [1, 0],
+    },
+  },
+  {
+    name: '[convTranspose2d] Throw if the padding width is too large.',
+    input: {dataType: 'float32', dimensions: [1, 1, 2, 2]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [0, 0, 4, 4],
+      strides: [2, 2],
+      outputPadding: [0, 1],
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw due to outputSizes values are smaller than the output sizes calculated by not using outputPadding.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [1, 1, 1, 1],
+      strides: [2, 2],
+      outputSizes: [4, 4],
+      outputPadding: [1, 1],
+    },
+  },
+  {
+    name:
+        '[convTranspose2d] Throw due to outputSizes values are greater than the output sizes calculated by not using outputPadding.',
+    input: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    filter: {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+    options: {
+      padding: [1, 1, 1, 1],
+      strides: [2, 2],
+      outputSizes: [6, 8],
+      outputPadding: [1, 1],
+    },
+  },
+];
+
+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.convTranspose2d(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.convTranspose2d(input, filter, test.options));
+      }
+    }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/elu.https.any.js b/testing/web-platform/tests/webnn/validation_tests/elu.https.any.js
index 6e842cb691..53ec5e54ae 100644
--- a/testing/web-platform/tests/webnn/validation_tests/elu.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/elu.https.any.js
@@ -5,3 +5,43 @@
 'use strict';
 
 validateInputFromAnotherBuilder('elu');
+
+validateUnaryOperation(
+    'elu', floatingPointTypes, /*alsoBuildActivation=*/ true);
+
+promise_test(async t => {
+  const options = {alpha: 1.0};
+  const input =
+      builder.input('input', {dataType: 'float32', dimensions: [1, 2, 3]});
+  const output = builder.elu(input, options);
+  assert_equals(output.dataType(), 'float32');
+  assert_array_equals(output.shape(), [1, 2, 3]);
+}, '[elu] Test building an operator with options');
+
+promise_test(async t => {
+  const options = {alpha: 1.5};
+  builder.elu(options);
+}, '[elu] Test building an activation with options');
+
+promise_test(async t => {
+  const options = {alpha: -1.0};
+  const input =
+      builder.input('input', {dataType: 'float32', dimensions: [1, 2, 3]});
+  assert_throws_js(TypeError, () => builder.elu(input, options));
+}, '[elu] Throw if options.alpha <= 0 when building an operator');
+
+promise_test(async t => {
+  const options = {alpha: NaN};
+  const input = builder.input('input', {dataType: 'float16', dimensions: []});
+  assert_throws_js(TypeError, () => builder.elu(input, options));
+}, '[elu] Throw if options.alpha is NaN when building an operator');
+
+promise_test(async t => {
+  const options = {alpha: 0};
+  assert_throws_js(TypeError, () => builder.elu(options));
+}, '[elu] Throw if options.alpha <= 0 when building an activation');
+
+promise_test(async t => {
+  const options = {alpha: Infinity};
+  assert_throws_js(TypeError, () => builder.elu(options));
+}, '[elu] Throw if options.alpha is Infinity when building an activation');
diff --git a/testing/web-platform/tests/webnn/validation_tests/expand.https.any.js b/testing/web-platform/tests/webnn/validation_tests/expand.https.any.js
index d90ab89468..088d826df7 100644
--- a/testing/web-platform/tests/webnn/validation_tests/expand.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/expand.https.any.js
@@ -12,3 +12,66 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   assert_throws_js(
       TypeError, () => builder.expand(inputFromOtherBuilder, newShape));
 }, '[expand] throw if input is from another builder');
+
+const tests = [
+  {
+    name: '[expand] Test with 0-D scalar to 3-D tensor.',
+    input: {dataType: 'float32', dimensions: []},
+    newShape: [3, 4, 5],
+    output: {dataType: 'float32', dimensions: [3, 4, 5]}
+  },
+  {
+    name: '[expand] Test with the new shapes that are the same as input.',
+    input: {dataType: 'float32', dimensions: [4]},
+    newShape: [4],
+    output: {dataType: 'float32', dimensions: [4]}
+  },
+  {
+    name: '[expand] Test with the new shapes that are broadcastable.',
+    input: {dataType: 'int32', dimensions: [3, 1, 5]},
+    newShape: [3, 4, 5],
+    output: {dataType: 'int32', dimensions: [3, 4, 5]}
+  },
+  {
+    name:
+        '[expand] Test with the new shapes that are broadcastable and the rank of new shapes is larger than input.',
+    input: {dataType: 'int32', dimensions: [2, 5]},
+    newShape: [3, 2, 5],
+    output: {dataType: 'int32', dimensions: [3, 2, 5]}
+  },
+  {
+    name:
+        '[expand] Throw if the input shapes are the same rank but not broadcastable.',
+    input: {dataType: 'uint32', dimensions: [3, 6, 2]},
+    newShape: [4, 3, 5],
+  },
+  {
+    name: '[expand] Throw if the input shapes are not broadcastable.',
+    input: {dataType: 'uint32', dimensions: [5, 4]},
+    newShape: [5],
+  },
+  {
+    name: '[expand] Throw if the number of new shapes is too large.',
+    input: {dataType: 'float32', dimensions: [1, 2, 1, 1]},
+    newShape: [1, 2, kMaxUnsignedLong, kMaxUnsignedLong],
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.dimensions});
+      const options = {};
+      if (test.axis) {
+        options.axis = test.axis;
+      }
+
+      if (test.output) {
+        const output = builder.expand(input, test.newShape);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(TypeError, () => builder.expand(input, test.newShape));
+      }
+    }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/gelu.https.any.js b/testing/web-platform/tests/webnn/validation_tests/gelu.https.any.js
new file mode 100644
index 0000000000..c758c61f4c
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/gelu.https.any.js
@@ -0,0 +1,10 @@
+// META: title=validation tests for WebNN API gelu operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+
+'use strict';
+
+validateInputFromAnotherBuilder('gelu');
+
+validateUnaryOperation(
+    'gelu', floatingPointTypes, /*alsoBuildActivation=*/ true);
diff --git a/testing/web-platform/tests/webnn/validation_tests/gemm.https.any.js b/testing/web-platform/tests/webnn/validation_tests/gemm.https.any.js
index 77ce6383cc..abe0ba6193 100644
--- a/testing/web-platform/tests/webnn/validation_tests/gemm.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/gemm.https.any.js
@@ -19,3 +19,143 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   const b = builder.input('b', kExampleInputDescriptor);
   assert_throws_js(TypeError, () => builder.gemm(a, b, options));
 }, '[gemm] throw if c option is from another builder');
+
+const tests = [
+  {
+    name: '[gemm] Test building gemm with default option.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [3, 4]},
+    output: {dataType: 'float32', dimensions: [2, 4]}
+  },
+  {
+    name:
+        '[gemm] Throw if inputShapeA[1] is not equal to inputShapeB[0] default options.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [2, 4]},
+  },
+  {
+    name: '[gemm] Test building gemm with aTranspose=true.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [2, 4]},
+    options: {
+      aTranspose: true,
+    },
+    output: {dataType: 'float32', dimensions: [3, 4]}
+  },
+  {
+    name:
+        '[gemm] Throw if inputShapeA[0] is not equal to inputShapeB[0] with aTranspose=true.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [3, 4]},
+    options: {
+      aTranspose: true,
+    },
+  },
+  {
+    name: '[gemm] Test building gemm with bTranspose=true.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [4, 3]},
+    options: {
+      bTranspose: true,
+    },
+    output: {dataType: 'float32', dimensions: [2, 4]}
+  },
+  {
+    name:
+        '[gemm] Throw if inputShapeA[0] is not equal to inputShapeB[0] with bTranspose=true.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [3, 4]},
+    options: {
+      bTranspose: true,
+    },
+  },
+  {
+    name: '[gemm] Throw if the rank of inputA is not 2.',
+    a: {dataType: 'float32', dimensions: [2, 3, 1]},
+    b: {dataType: 'float32', dimensions: [2, 4]},
+  },
+  {
+    name: '[gemm] Throw if the rank of inputB is not 2.',
+    a: {dataType: 'float32', dimensions: [2, 4]},
+    b: {dataType: 'float32', dimensions: [2, 3, 1]},
+  },
+  {
+    name: '[gemm] Throw if data types of two inputs do not match.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float16', dimensions: [3, 4]},
+  },
+  {
+    name: '[gemm] Test building gemm with inputC.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [3, 4]},
+    options: {
+      c: {dataType: 'float32', dimensions: [4]},
+    },
+    output: {dataType: 'float32', dimensions: [2, 4]}
+  },
+  {
+    name: '[gemm] Test building gemm with scalar inputC.',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [3, 4]},
+    options: {
+      c: {dataType: 'float32', dimensions: []},
+    },
+    output: {dataType: 'float32', dimensions: [2, 4]}
+  },
+  {
+    name:
+        '[gemm] Throw if inputShapeC is not unidirectionally broadcastable to the output shape [inputShapeA[0], inputShapeB[1]].',
+    a: {dataType: 'float32', dimensions: [2, 3]},
+    b: {dataType: 'float32', dimensions: [3, 4]},
+    options: {
+      c: {dataType: 'float32', dimensions: [2, 3]},
+    },
+  },
+  {
+    name: '[gemm] Throw if the input data type is not floating point.',
+    a: {dataType: 'int32', dimensions: [2, 3]},
+    b: {dataType: 'int32', dimensions: [3, 4]}
+  },
+  {
+    name:
+        '[gemm] Throw if data type of inputC does not match ones of inputA and inputB.',
+    a: {dataType: 'float32', dimensions: [3, 2]},
+    b: {dataType: 'float32', dimensions: [4, 3]},
+    options: {
+      c: {dataType: 'float16', dimensions: [2, 4]},
+      aTranspose: true,
+      bTranspose: true,
+    },
+  },
+  {
+    name: '[gemm] Throw if the rank of inputC is 3.',
+    a: {dataType: 'float32', dimensions: [3, 2]},
+    b: {dataType: 'float32', dimensions: [4, 3]},
+    options: {
+      c: {dataType: 'float32', dimensions: [2, 3, 4]},
+      aTranspose: true,
+      bTranspose: true,
+    },
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const a = builder.input(
+          'a', {dataType: test.a.dataType, dimensions: test.a.dimensions});
+      const b = builder.input(
+          'b', {dataType: test.b.dataType, dimensions: test.b.dimensions});
+      if (test.options && test.options.c) {
+        test.options.c = builder.input('c', {
+          dataType: test.options.c.dataType,
+          dimensions: test.options.c.dimensions
+        });
+      }
+      if (test.output) {
+        const output = builder.gemm(a, b, test.options);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(TypeError, () => builder.gemm(a, b, test.options));
+      }
+    }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/hardSigmoid.https.any.js b/testing/web-platform/tests/webnn/validation_tests/hardSigmoid.https.any.js
index 01b24dbc7c..2c55d0eb9d 100644
--- a/testing/web-platform/tests/webnn/validation_tests/hardSigmoid.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/hardSigmoid.https.any.js
@@ -5,3 +5,31 @@
 'use strict';
 
 validateInputFromAnotherBuilder('hardSigmoid');
+
+validateUnaryOperation(
+    'hardSigmoid', floatingPointTypes, /*alsoBuildActivation=*/ true);
+
+promise_test(async t => {
+  const options = {alpha: 0.5, beta: 1.0};
+  const input =
+      builder.input('input', {dataType: 'float16', dimensions: [1, 2, 3]});
+  const output = builder.hardSigmoid(input, options);
+  assert_equals(output.dataType(), 'float16');
+  assert_array_equals(output.shape(), [1, 2, 3]);
+}, '[hardSigmoid] Test building an operator with options');
+
+promise_test(async t => {
+  const options = {alpha: 0.2};
+  builder.hardSigmoid(options);
+}, '[hardSigmoid] Test building an activation with options');
+
+promise_test(async t => {
+  const options = {beta: NaN};
+  const input = builder.input('input', {dataType: 'float32', dimensions: []});
+  assert_throws_js(TypeError, () => builder.hardSigmoid(input, options));
+}, '[hardSigmoid] Throw if options.beta is NaN when building an operator');
+
+promise_test(async t => {
+  const options = {alpha: Infinity};
+  assert_throws_js(TypeError, () => builder.hardSigmoid(options));
+}, '[hardSigmoid] Throw if options.alpha is Infinity when building an activation');
diff --git a/testing/web-platform/tests/webnn/validation_tests/instanceNormalization.https.any.js b/testing/web-platform/tests/webnn/validation_tests/instanceNormalization.https.any.js
index bdd338588f..4fc26ec5ae 100644
--- a/testing/web-platform/tests/webnn/validation_tests/instanceNormalization.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/instanceNormalization.https.any.js
@@ -41,3 +41,152 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   assert_throws_js(
       TypeError, () => builder.instanceNormalization(input, options));
 }, '[instanceNormalization] throw if bias option is from another builder');
+
+const tests = [
+  {
+    name: '[instanceNormalization] Test with default options for 4-D input.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]}
+  },
+  {
+    name:
+        '[instanceNormalization] Test with scale, bias and default epsilon value.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [2]},
+      bias: {dataType: 'float32', dimensions: [2]},
+      epsilon: 1e-5,
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]}
+  },
+  {
+    name: '[instanceNormalization] Test with a non-default epsilon value.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      epsilon: 1e-4,
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]}
+  },
+  {
+    name: '[instanceNormalization] Test with layout=nhwc.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {
+      layout: 'nhwc',
+      scale: {dataType: 'float32', dimensions: [4]},
+      bias: {dataType: 'float32', dimensions: [4]},
+    },
+    output: {dataType: 'float32', dimensions: [1, 2, 3, 4]}
+  },
+  {
+    name: '[instanceNormalization] Test when the input data type is float16.',
+    input: {dataType: 'float16', dimensions: [1, 2, 3, 4]},
+    output: {dataType: 'float16', dimensions: [1, 2, 3, 4]}
+  },
+  {
+    name: '[instanceNormalization] Throw if the input is not a 4-D tensor.',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5, 2]},
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the input data type is not one of floating point types.',
+    input: {dataType: 'int32', dimensions: [1, 2, 5, 5]},
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the scale data type is not the same as the input data type.',
+    input: {dataType: 'float16', dimensions: [1, 2, 5, 5]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the scale operand is not a 1-D tensor.',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [2, 1]},
+    },
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the size of scale operand is not equal to the size of the feature dimension of the input with layout=nhwc.',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    options: {
+      layout: 'nhwc',
+      scale: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the size of scale operand is not equal to the size of the feature dimension of the input with layout=nchw.',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    options: {
+      layout: 'nchw',
+      scale: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the bias data type is not the same as the input data type.',
+    input: {dataType: 'float16', dimensions: [1, 2, 5, 5]},
+    options: {
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the bias operand is not a 1-D tensor.',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    options: {
+      scale: {dataType: 'float32', dimensions: [2, 1]},
+    },
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the size of bias operand is not equal to the size of the feature dimension of the input with layout=nhwc.',
+    input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
+    options: {
+      layout: 'nhwc',
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+  {
+    name:
+        '[instanceNormalization] Throw if the size of bias operand is not equal to the size of the feature dimension of the input with layout=nchw.',
+    input: {dataType: 'float32', dimensions: [1, 5, 5, 2]},
+    options: {
+      layout: 'nchw',
+      bias: {dataType: 'float32', dimensions: [2]},
+    },
+  },
+];
+
+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.instanceNormalization(input, test.options);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(
+            TypeError,
+            () => builder.instanceNormalization(input, test.options));
+      }
+    }, test.name));
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));
diff --git a/testing/web-platform/tests/webnn/validation_tests/leakyRelu.https.any.js b/testing/web-platform/tests/webnn/validation_tests/leakyRelu.https.any.js
index 6fc19b1f0d..f250b0eda6 100644
--- a/testing/web-platform/tests/webnn/validation_tests/leakyRelu.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/leakyRelu.https.any.js
@@ -5,3 +5,31 @@
 'use strict';
 
 validateInputFromAnotherBuilder('leakyRelu');
+
+validateUnaryOperation(
+    'leakyRelu', floatingPointTypes, /*alsoBuildActivation=*/ true);
+
+promise_test(async t => {
+  const options = {alpha: 0.02};
+  const input =
+      builder.input('input', {dataType: 'float32', dimensions: [1, 2, 3]});
+  const output = builder.leakyRelu(input, options);
+  assert_equals(output.dataType(), 'float32');
+  assert_array_equals(output.shape(), [1, 2, 3]);
+}, '[leakyRelu] Test building an operator with options');
+
+promise_test(async t => {
+  const options = {alpha: 0.03};
+  builder.leakyRelu(options);
+}, '[leakyRelu] Test building an activation with options');
+
+promise_test(async t => {
+  const options = {alpha: Infinity};
+  const input = builder.input('input', {dataType: 'float16', dimensions: []});
+  assert_throws_js(TypeError, () => builder.leakyRelu(input, options));
+}, '[leakyRelu] Throw if options.alpha is Infinity when building an operator');
+
+promise_test(async t => {
+  const options = {alpha: -NaN};
+  assert_throws_js(TypeError, () => builder.leakyRelu(options));
+}, '[leakyRelu] Throw if options.alpha is -NaN when building an activation');
diff --git a/testing/web-platform/tests/webnn/validation_tests/linear.https.any.js b/testing/web-platform/tests/webnn/validation_tests/linear.https.any.js
index 99c1daad3f..6ec0389fc3 100644
--- a/testing/web-platform/tests/webnn/validation_tests/linear.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/linear.https.any.js
@@ -5,3 +5,31 @@
 'use strict';
 
 validateInputFromAnotherBuilder('linear');
+
+validateUnaryOperation(
+    'linear', floatingPointTypes, /*alsoBuildActivation=*/ true);
+
+promise_test(async t => {
+  const options = {alpha: 1.5, beta: 0.3};
+  const input =
+      builder.input('input', {dataType: 'float32', dimensions: [1, 2, 3]});
+  const output = builder.linear(input, options);
+  assert_equals(output.dataType(), 'float32');
+  assert_array_equals(output.shape(), [1, 2, 3]);
+}, '[linear] Test building an operator with options');
+
+promise_test(async t => {
+  const options = {beta: 1.5};
+  builder.linear(options);
+}, '[linear] Test building an activation with options');
+
+promise_test(async t => {
+  const options = {beta: -Infinity};
+  const input = builder.input('input', {dataType: 'float16', dimensions: []});
+  assert_throws_js(TypeError, () => builder.linear(input, options));
+}, '[linear] Throw if options.beta is -Infinity when building an operator');
+
+promise_test(async t => {
+  const options = {alpha: NaN};
+  assert_throws_js(TypeError, () => builder.linear(options));
+}, '[linear] Throw if options.alpha is NaN when building an activation');
diff --git a/testing/web-platform/tests/webnn/validation_tests/matmul.https.any.js b/testing/web-platform/tests/webnn/validation_tests/matmul.https.any.js
index 03616ddb01..8db16242c9 100644
--- a/testing/web-platform/tests/webnn/validation_tests/matmul.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/matmul.https.any.js
@@ -5,3 +5,116 @@
 'use strict';
 
 validateTwoInputsFromMultipleBuilders('matmul');
+
+const tests = [
+  {
+    name: '[matmul] Throw if first input\'s rank is less than 2',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [2]},
+      b: {dataType: 'float32', dimensions: [2, 2]}
+    }
+  },
+  {
+    name: '[matmul] Throw if second input\'s rank is less than 2',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [2, 2]},
+      b: {dataType: 'float32', dimensions: [2]}
+    }
+  },
+  {
+    name: '[matmul] Test with 2-D input and 4-D input',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [1, 4]},
+      b: {dataType: 'float32', dimensions: [2, 2, 4, 2]}
+    },
+    output: {dataType: 'float32', dimensions: [2, 2, 1, 2]}
+  },
+  {
+    name: '[matmul] Test with 2-D input and 2-D input',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [4, 2]},
+      b: {dataType: 'float32', dimensions: [2, 3]}
+    },
+    output: {dataType: 'float32', dimensions: [4, 3]}
+  },
+  {
+    // batchShape is a clone of inputShape with the spatial dimensions
+    // (last 2 items) removed.
+    name:
+        '[matmul] Test with 3-D input and 3-D input of broadcastable batchShape',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [2, 3, 4]},
+      b: {dataType: 'float32', dimensions: [1, 4, 1]}
+    },
+    output: {dataType: 'float32', dimensions: [2, 3, 1]}
+  },
+  {
+    // batchShape is a clone of inputShape with the spatial dimensions
+    // (last 2 items) removed.
+    name:
+        '[matmul] Test with 4-D input and 3-D input of broadcastable batchShape',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [2, 2, 3, 4]},
+      b: {dataType: 'float32', dimensions: [1, 4, 5]}
+    },
+    output: {dataType: 'float32', dimensions: [2, 2, 3, 5]}
+  },
+  {
+    name: '[matmul] Test with 3-D input and 3-D input',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [2, 3, 4]},
+      b: {dataType: 'float32', dimensions: [2, 4, 5]}
+    },
+    output: {dataType: 'float32', dimensions: [2, 3, 5]}
+  },
+  {
+    name: '[matmul] Throw if the input data type is not floating point',
+    inputs: {
+      a: {dataType: 'uint32', dimensions: [2, 3, 4]},
+      b: {dataType: 'uint32', dimensions: [2, 4, 5]}
+    }
+  },
+  {
+    name: '[matmul] Throw if data type of two inputs don\'t match',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [2, 3, 4]},
+      b: {dataType: 'float16', dimensions: [2, 4, 5]}
+    }
+  },
+  {
+    name:
+        '[matmul] Throw if columns of first input\'s shape doesn\'t match the rows of second input\'s shape',
+    inputs: {
+      a: {dataType: 'float32', dimensions: /* [rows, columns] */[2, 3]},
+      b: {dataType: 'float32', dimensions: /* [rows, columns] */[2, 4]}
+    },
+  },
+  {
+    // batchShape is a clone of inputShape with the spatial dimensions
+    // (last 2 items) removed.
+    name: '[matmul] Throw if batchShapes aren\'t bidirectionally broadcastable',
+    inputs: {
+      a: {dataType: 'float32', dimensions: [3, 3, 4]},
+      b: {dataType: 'float32', dimensions: [2, 4, 1]}
+    },
+  },
+];
+
+tests.forEach(test => promise_test(async t => {
+                const inputA = builder.input('a', {
+                  dataType: test.inputs.a.dataType,
+                  dimensions: test.inputs.a.dimensions
+                });
+                const inputB = builder.input('b', {
+                  dataType: test.inputs.b.dataType,
+                  dimensions: test.inputs.b.dimensions
+                });
+                if (test.output) {
+                  const output = builder.matmul(inputA, inputB);
+                  assert_equals(output.dataType(), test.output.dataType);
+                  assert_array_equals(output.shape(), test.output.dimensions);
+                } else {
+                  assert_throws_js(
+                      TypeError, () => builder.matmul(inputA, inputB));
+                }
+              }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/pad.https.any.js b/testing/web-platform/tests/webnn/validation_tests/pad.https.any.js
index 11c6a8f7ef..cc39bee4c0 100644
--- a/testing/web-platform/tests/webnn/validation_tests/pad.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/pad.https.any.js
@@ -15,3 +15,73 @@ multi_builder_test(async (t, builder, otherBuilder) => {
       () =>
           builder.pad(inputFromOtherBuilder, beginningPadding, endingPadding));
 }, '[pad] throw if input is from another builder');
+
+const tests = [
+  {
+    name:
+        '[pad] Test with default options, beginningPadding=[1, 2] and endingPadding=[1, 2].',
+    input: {dataType: 'float32', dimensions: [2, 3]},
+    beginningPadding: [1, 2],
+    endingPadding: [1, 2],
+    options: {
+      mode: 'constant',
+      value: 0,
+    },
+    output: {dataType: 'float32', dimensions: [4, 7]}
+  },
+  {
+    name: '[pad] Throw if building pad for scalar input.',
+    input: {dataType: 'float32', dimensions: []},
+    beginningPadding: [],
+    endingPadding: [],
+  },
+  {
+    name:
+        '[pad] Throw if the length of beginningPadding is not equal to the input rank.',
+    input: {dataType: 'float32', dimensions: [2, 3]},
+    beginningPadding: [1],
+    endingPadding: [1, 2],
+    options: {
+      mode: 'edge',
+      value: 0,
+    },
+  },
+  {
+    name:
+        '[pad] Throw if the length of endingPadding is not equal to the input rank.',
+    input: {dataType: 'float32', dimensions: [2, 3]},
+    beginningPadding: [1, 0],
+    endingPadding: [1, 2, 0],
+    options: {
+      mode: 'reflection',
+    },
+  },
+  {
+    name: '[pad] Throw if the padding of one dimension is too large.',
+    input: {dataType: 'float32', dimensions: [2, 3]},
+    beginningPadding: [2294967295, 0],
+    endingPadding: [3294967295, 2],
+    options: {
+      mode: 'reflection',
+    },
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.dimensions});
+      if (test.output) {
+        const output = builder.pad(
+            input, test.beginningPadding, test.endingPadding, test.options);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(
+            TypeError,
+            () => builder.pad(
+                input, test.beginningPadding, test.endingPadding,
+                test.options));
+      }
+    }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/pooling-and-reduction-keep-dims.https.any.js b/testing/web-platform/tests/webnn/validation_tests/pooling-and-reduction-keep-dims.https.any.js
new file mode 100644
index 0000000000..9f6b9fb338
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/pooling-and-reduction-keep-dims.https.any.js
@@ -0,0 +1,94 @@
+// META: title=validation tests for pooling and reduction operators keep dimensions
+// META: global=window,dedicatedworker
+// META: script=../resources/utils.js
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+// This is used to reproduce an issue(crbug.com/331841268) of averagePool2d in
+// ResNetV2 50 model.
+//      [input]
+//         |
+//  [globalAveragePool]
+//         |
+//     [conv2d]
+//         |
+//     [reshape]
+//         |
+//     [output]
+promise_test(async t => {
+  const avgPool2dInputShape = [1, 7, 7, 2048];
+  const avgPool2dInput = builder.input(
+      `avgPool2dInput`, {dataType: 'float32', dimensions: avgPool2dInputShape});
+  const avgPool2dOutput =
+      builder.averagePool2d(avgPool2dInput, {layout: 'nhwc'});
+  const conv2dFilterShape = [1001, 1, 1, 2048];
+  const conv2dFilter = builder.constant(
+      {dataType: 'float32', dimensions: conv2dFilterShape},
+      new Float32Array(sizeOfShape(conv2dFilterShape)).fill(1));
+  const conv2dBias = builder.constant(
+      {dataType: 'float32', dimensions: [1001]},
+      new Float32Array(1001).fill(0.01));
+  const conv2dOutput = builder.conv2d(avgPool2dOutput, conv2dFilter, {
+    inputLayout: 'nhwc',
+    filterLayout: 'ohwi',
+    padding: [0, 0, 0, 0],
+    bias: conv2dBias
+  });
+  const newShape = [1, 1001];
+  const reshapeOutput = builder.reshape(conv2dOutput, newShape);
+  assert_equals(reshapeOutput.dataType(), avgPool2dInput.dataType());
+  assert_array_equals(reshapeOutput.shape(), newShape);
+  const graph = await builder.build({reshapeOutput});
+  const result = await context.compute(
+      graph, {
+        'avgPool2dInput':
+            new Float32Array(sizeOfShape(avgPool2dInputShape)).fill(0.1)
+      },
+      {'reshapeOutput': new Float32Array(1001)});
+}, 'Test global average pool operator\'s output shape for ResNetV2 50 model.');
+
+// This is used to reproduce an issue(crbug.com/331841268) of reduceMean in
+// ResNetV2 50 model.
+//      [input]
+//         |
+//    [reduceMean]
+//         |
+//     [conv2d]
+//         |
+//     [reshape]
+//         |
+//     [output]
+promise_test(async t => {
+  const reduceMeanInputShape = [1, 7, 7, 2048];
+  const reduceMeanInput = builder.input(
+      `reduceMeanInput`,
+      {dataType: 'float32', dimensions: reduceMeanInputShape});
+  const reduceMeanOutput =
+      builder.reduceMean(reduceMeanInput, {axes: [1, 2], keepDimensions: true});
+  const conv2dFilterShape = [1001, 1, 1, 2048];
+  const conv2dFilter = builder.constant(
+      {dataType: 'float32', dimensions: conv2dFilterShape},
+      new Float32Array(sizeOfShape(conv2dFilterShape)).fill(1));
+  const conv2dBias = builder.constant(
+      {dataType: 'float32', dimensions: [1001]},
+      new Float32Array(1001).fill(0.01));
+  const conv2dOutput = builder.conv2d(reduceMeanOutput, conv2dFilter, {
+    inputLayout: 'nhwc',
+    filterLayout: 'ohwi',
+    padding: [0, 0, 0, 0],
+    bias: conv2dBias
+  });
+  const newShape = [1, 1001];
+  const reshapeOutput = builder.reshape(conv2dOutput, newShape);
+  assert_equals(reshapeOutput.dataType(), reduceMeanInput.dataType());
+  assert_array_equals(reshapeOutput.shape(), newShape);
+  const graph = await builder.build({reshapeOutput});
+  const result = await context.compute(
+      graph, {
+        'reduceMeanInput':
+            new Float32Array(sizeOfShape(reduceMeanInputShape)).fill(0.1)
+      },
+      {'reshapeOutput': new Float32Array(1001)});
+}, 'Test reduceMean operator\'s output shape for ResNetV2 50 model.');
diff --git a/testing/web-platform/tests/webnn/validation_tests/reshape.https.any.js b/testing/web-platform/tests/webnn/validation_tests/reshape.https.any.js
index 435551b716..67491fbc16 100644
--- a/testing/web-platform/tests/webnn/validation_tests/reshape.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/reshape.https.any.js
@@ -12,3 +12,68 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   assert_throws_js(
       TypeError, () => builder.reshape(inputFromOtherBuilder, newShape));
 }, '[reshape] throw if input is from another builder');
+
+const tests = [
+  {
+    name: '[reshape] Test with new shape=[3, 8].',
+    input: {dataType: 'float32', dimensions: [2, 3, 4]},
+    newShape: [3, 8],
+    output: {dataType: 'float32', dimensions: [3, 8]}
+  },
+  {
+    name: '[reshape] Test with new shape=[24], src shape=[2, 3, 4].',
+    input: {dataType: 'float32', dimensions: [2, 3, 4]},
+    newShape: [24],
+    output: {dataType: 'float32', dimensions: [24]}
+  },
+  {
+    name: '[reshape] Test with new shape=[1], src shape=[1].',
+    input: {dataType: 'float32', dimensions: [1]},
+    newShape: [1],
+    output: {dataType: 'float32', dimensions: [1]}
+  },
+  {
+    name: '[reshape] Test reshaping a 1-D 1-element tensor to scalar.',
+    input: {dataType: 'float32', dimensions: [1]},
+    newShape: [],
+    output: {dataType: 'float32', dimensions: []}
+  },
+  {
+    name: '[reshape] Test reshaping a scalar to 1-D 1-element tensor.',
+    input: {dataType: 'float32', dimensions: []},
+    newShape: [1],
+    output: {dataType: 'float32', dimensions: [1]}
+  },
+  {
+    name: '[reshape] Throw if one value of new shape is 0.',
+    input: {dataType: 'float32', dimensions: [2, 4]},
+    newShape: [2, 4, 0],
+  },
+  {
+    name:
+        '[reshape] Throw if the number of elements implied by new shape is not equal to the number of elements in the input tensor when new shape=[].',
+    input: {dataType: 'float32', dimensions: [2, 3, 4]},
+    newShape: [],
+  },
+  {
+    name:
+        '[reshape] Throw if the number of elements implied by new shape is not equal to the number of elements in the input tensor.',
+    input: {dataType: 'float32', dimensions: [2, 3, 4]},
+    newShape: [3, 9],
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.dimensions});
+      if (test.output) {
+        const output = builder.reshape(input, test.newShape);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(
+            TypeError, () => builder.reshape(input, test.newShape));
+      }
+    }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/slice.https.any.js b/testing/web-platform/tests/webnn/validation_tests/slice.https.any.js
index a45ecd3fcb..de42621610 100644
--- a/testing/web-platform/tests/webnn/validation_tests/slice.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/slice.https.any.js
@@ -13,3 +13,69 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   assert_throws_js(
       TypeError, () => builder.slice(inputFromOtherBuilder, starts, sizes));
 }, '[slice] throw if input is from another builder');
+
+const tests = [
+  {
+    name: '[slice] Test with starts=[0, 1, 2] and sizes=[1, 2, 3].',
+    input: {dataType: 'float32', dimensions: [3, 4, 5]},
+    starts: [0, 1, 2],
+    sizes: [1, 2, 3],
+    output: {dataType: 'float32', dimensions: [1, 2, 3]}
+  },
+  {
+    name: '[slice] Throw if input is a scalar.',
+    input: {dataType: 'float32', dimensions: []},
+    starts: [0],
+    sizes: [1]
+  },
+  {
+    name:
+        '[slice] Throw if the length of sizes is not equal to the rank of the input tensor.',
+    input: {dataType: 'float32', dimensions: [3, 4, 5]},
+    starts: [1, 2, 3],
+    sizes: [1, 1]
+  },
+  {
+    name:
+        '[slice] Throw if the length of starts is not equal to the rank of the input tensor.',
+    input: {dataType: 'float32', dimensions: [3, 4, 5]},
+    starts: [1, 2, 1, 3],
+    sizes: [1, 1, 1]
+  },
+  {
+    name:
+        '[slice] Throw if the starting index is equal to or greater than input size in the same dimension.',
+    input: {dataType: 'float32', dimensions: [3, 4, 5]},
+    starts: [0, 4, 4],
+    sizes: [1, 1, 1]
+  },
+  {
+    name: '[slice] Throw if the number of elements to slice is equal to 0.',
+    input: {dataType: 'float32', dimensions: [3, 4, 5]},
+    starts: [1, 2, 3],
+    sizes: [1, 0, 1]
+  },
+  {
+    name:
+        '[slice] Throw if the ending index to slice is greater than input size in the same dimension.',
+    input: {dataType: 'float32', dimensions: [3, 4, 5]},
+    starts: [0, 1, 2],
+    sizes: [3, 4, 1]
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.dimensions});
+
+      if (test.output) {
+        const output = builder.slice(input, test.starts, test.sizes);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(
+            TypeError, () => builder.slice(input, test.starts, test.sizes));
+      }
+    }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/softplus.https.any.js b/testing/web-platform/tests/webnn/validation_tests/softplus.https.any.js
index 347dfcd938..3cf91d26ec 100644
--- a/testing/web-platform/tests/webnn/validation_tests/softplus.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/softplus.https.any.js
@@ -5,3 +5,6 @@
 'use strict';
 
 validateInputFromAnotherBuilder('softplus');
+
+validateUnaryOperation(
+    'softplus', floatingPointTypes, /*alsoBuildActivation=*/ true);
diff --git a/testing/web-platform/tests/webnn/validation_tests/split.https.any.js b/testing/web-platform/tests/webnn/validation_tests/split.https.any.js
index 38f3126603..6f7809744a 100644
--- a/testing/web-platform/tests/webnn/validation_tests/split.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/split.https.any.js
@@ -12,3 +12,83 @@ multi_builder_test(async (t, builder, otherBuilder) => {
   assert_throws_js(
       TypeError, () => builder.split(inputFromOtherBuilder, splits));
 }, '[split] throw if input is from another builder');
+
+const tests = [
+  {
+    name: '[split] Test with default options.',
+    input: {dataType: 'float32', dimensions: [2, 6]},
+    splits: [2],
+    outputs: [
+      {dataType: 'float32', dimensions: [2, 6]},
+    ]
+  },
+  {
+    name:
+        '[split] Test with a sequence of unsigned long splits and with options.axis = 1.',
+    input: {dataType: 'float32', dimensions: [2, 6]},
+    splits: [1, 2, 3],
+    options: {axis: 1},
+    outputs: [
+      {dataType: 'float32', dimensions: [2, 1]},
+      {dataType: 'float32', dimensions: [2, 2]},
+      {dataType: 'float32', dimensions: [2, 3]},
+    ]
+  },
+  {
+    name: '[split] Throw if splitting a scalar.',
+    input: {dataType: 'float32', dimensions: []},
+    splits: [2],
+  },
+  {
+    name: '[split] Throw if axis is larger than input rank.',
+    input: {dataType: 'float32', dimensions: [2, 6]},
+    splits: [2],
+    options: {
+      axis: 2,
+    }
+  },
+  {
+    name: '[split] Throw if splits is equal to 0.',
+    input: {dataType: 'float32', dimensions: [2, 6]},
+    splits: [0],
+    options: {
+      axis: 2,
+    }
+  },
+  {
+    name:
+        '[split] Throw if the splits can not evenly divide the dimension size of input along options.axis.',
+    input: {dataType: 'float32', dimensions: [2, 5]},
+    splits: [2],
+    options: {
+      axis: 1,
+    }
+  },
+  {
+    name:
+        '[split] Throw if the sum of splits sizes not equal to the dimension size of input along options.axis.',
+    input: {dataType: 'float32', dimensions: [2, 6]},
+    splits: [2, 2, 3],
+    options: {
+      axis: 1,
+    }
+  },
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+      const input = builder.input(
+          'input',
+          {dataType: test.input.dataType, dimensions: test.input.dimensions});
+      if (test.outputs) {
+        const outputs = builder.split(input, test.splits, test.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.split(input, test.splits, test.options));
+      }
+    }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/transpose.https.any.js b/testing/web-platform/tests/webnn/validation_tests/transpose.https.any.js
index 9ea5a5dcf8..3475a427d7 100644
--- a/testing/web-platform/tests/webnn/validation_tests/transpose.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/transpose.https.any.js
@@ -5,3 +5,54 @@
 'use strict';
 
 validateInputFromAnotherBuilder('transpose');
+
+const tests = [
+  {
+    name: '[transpose] Test building transpose with default options.',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    output: {dataType: 'float32', dimensions: [4, 3, 2, 1]}
+  },
+  {
+    name: '[transpose] Test building transpose with permutation=[0, 2, 3, 1].',
+    input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+    options: {permutation: [0, 2, 3, 1]},
+    output: {dataType: 'float32', dimensions: [1, 3, 4, 2]}
+  },
+  {
+    name:
+        '[transpose] Throw if permutation\'s size is not the same as input\'s rank.',
+    input: {dataType: 'int32', dimensions: [1, 2, 4]},
+    options: {permutation: [0, 2, 3, 1]},
+  },
+  {
+    name: '[transpose] Throw if two values in permutation are same.',
+    input: {dataType: 'int32', dimensions: [1, 2, 3, 4]},
+    options: {permutation: [0, 2, 3, 2]},
+  },
+  {
+    name:
+        '[transpose] Throw if any value in permutation is not in the range [0,input\'s rank).',
+    input: {dataType: 'int32', dimensions: [1, 2, 3, 4]},
+    options: {permutation: [0, 1, 2, 4]},
+  },
+  {
+    name: '[transpose] Throw if any value in permutation is negative.',
+    input: {dataType: 'int32', dimensions: [1, 2, 3, 4]},
+    options: {permutation: [0, -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.output) {
+        const output = builder.transpose(input, test.options);
+        assert_equals(output.dataType(), test.output.dataType);
+        assert_array_equals(output.shape(), test.output.dimensions);
+      } else {
+        assert_throws_js(
+            TypeError, () => builder.transpose(input, test.options));
+      }
+    }, test.name));
author	Daniel Baumann <daniel.baumann@progress-linux.org>	2024-06-12 05:43:14 +0000
committer	Daniel Baumann <daniel.baumann@progress-linux.org>	2024-06-12 05:43:14 +0000
commit	8dd16259287f58f9273002717ec4d27e97127719 (patch)
tree	3863e62a53829a84037444beab3abd4ed9dfc7d0 /testing/web-platform/tests/webnn
parent	Releasing progress-linux version 126.0.1-1~progress7.99u1. (diff)
download	firefox-8dd16259287f58f9273002717ec4d27e97127719.tar.xz firefox-8dd16259287f58f9273002717ec4d27e97127719.zip