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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-19 01:13:27 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-19 01:13:27 +0000
commit40a355a42d4a9444dc753c04c6608dade2f06a23 (patch)
tree871fc667d2de662f171103ce5ec067014ef85e61 /testing/web-platform/tests/webnn
parentAdding upstream version 124.0.1. (diff)
downloadfirefox-40a355a42d4a9444dc753c04c6608dade2f06a23.tar.xz
firefox-40a355a42d4a9444dc753c04c6608dade2f06a23.zip
Adding upstream version 125.0.1.upstream/125.0.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'testing/web-platform/tests/webnn')
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/arg_min_max.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/arg_min_max.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/batch_normalization.https.any.js (renamed from testing/web-platform/tests/webnn/batch_normalization.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/buffer.https.any.js12
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/cast.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/cast.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/clamp.https.any.js (renamed from testing/web-platform/tests/webnn/clamp.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/concat.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/concat.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/constant.https.any.js10
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/conv2d.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/conv2d.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/conv_transpose2d.https.any.js (renamed from testing/web-platform/tests/webnn/conv_transpose2d.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/elementwise_binary.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/elementwise_binary.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/elementwise_logical.https.any.js (renamed from testing/web-platform/tests/webnn/elementwise_logical.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/elementwise_unary.https.any.js (renamed from testing/web-platform/tests/webnn/elementwise_unary.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/elu.https.any.js (renamed from testing/web-platform/tests/webnn/elu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/expand.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/expand.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gather.https.any.js (renamed from testing/web-platform/tests/webnn/gather.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gemm.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/gemm.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/arg_min_max.https.any.js (renamed from testing/web-platform/tests/webnn/arg_min_max.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/batch_normalization.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/batch_normalization.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/buffer.https.any.js12
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/cast.https.any.js (renamed from testing/web-platform/tests/webnn/cast.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/clamp.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/clamp.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/concat.https.any.js (renamed from testing/web-platform/tests/webnn/concat.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/constant.https.any.js10
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/conv2d.https.any.js (renamed from testing/web-platform/tests/webnn/conv2d.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/conv_transpose2d.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/conv_transpose2d.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_binary.https.any.js (renamed from testing/web-platform/tests/webnn/elementwise_binary.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_logical.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/elementwise_logical.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_unary.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/elementwise_unary.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/elu.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/elu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/expand.https.any.js (renamed from testing/web-platform/tests/webnn/expand.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/gather.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/gather.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/gemm.https.any.js (renamed from testing/web-platform/tests/webnn/gemm.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/hard_sigmoid.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/hard_sigmoid.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/hard_swish.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/hard_swish.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/instance_normalization.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/instance_normalization.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/layer_normalization.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/layer_normalization.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/leaky_relu.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/leaky_relu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/linear.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/linear.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/matmul.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/matmul.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/pad.https.any.js (renamed from testing/web-platform/tests/webnn/pad.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/pooling.https.any.js (renamed from testing/web-platform/tests/webnn/pooling.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/prelu.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/prelu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/reduction.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/reduction.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/relu.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/relu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/resample2d.https.any.js10
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/reshape.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/reshape.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/sigmoid.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/sigmoid.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/slice.https.any.js (renamed from testing/web-platform/tests/webnn/slice.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/softmax.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/softmax.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/softplus.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/softplus.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/softsign.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/softsign.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/split.https.any.js (renamed from testing/web-platform/tests/webnn/split.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/tanh.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/tanh.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/transpose.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/transpose.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/triangular.https.any.js10
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/gpu/where.https.any.js (renamed from testing/web-platform/tests/webnn/where.https.any.js)4
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/hard_sigmoid.https.any.js (renamed from testing/web-platform/tests/webnn/hard_sigmoid.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/hard_swish.https.any.js (renamed from testing/web-platform/tests/webnn/hard_swish.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/instance_normalization.https.any.js (renamed from testing/web-platform/tests/webnn/instance_normalization.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/layer_normalization.https.any.js (renamed from testing/web-platform/tests/webnn/layer_normalization.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/leaky_relu.https.any.js (renamed from testing/web-platform/tests/webnn/leaky_relu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/linear.https.any.js (renamed from testing/web-platform/tests/webnn/linear.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/matmul.https.any.js (renamed from testing/web-platform/tests/webnn/matmul.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/pad.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/pad.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/pooling.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/pooling.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/prelu.https.any.js (renamed from testing/web-platform/tests/webnn/prelu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/reduction.https.any.js (renamed from testing/web-platform/tests/webnn/reduction.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/relu.https.any.js (renamed from testing/web-platform/tests/webnn/relu.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/resample2d.https.any.js10
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/reshape.https.any.js (renamed from testing/web-platform/tests/webnn/reshape.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/sigmoid.https.any.js (renamed from testing/web-platform/tests/webnn/sigmoid.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/slice.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/slice.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js (renamed from testing/web-platform/tests/webnn/softmax.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/softplus.https.any.js (renamed from testing/web-platform/tests/webnn/softplus.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/softsign.https.any.js (renamed from testing/web-platform/tests/webnn/softsign.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/split.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/split.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/tanh.https.any.js (renamed from testing/web-platform/tests/webnn/tanh.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/transpose.https.any.js (renamed from testing/web-platform/tests/webnn/transpose.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/triangular.https.any.js10
-rw-r--r--testing/web-platform/tests/webnn/conformance_tests/where.https.any.js (renamed from testing/web-platform/tests/webnn/gpu/where.https.any.js)2
-rw-r--r--testing/web-platform/tests/webnn/idlharness.https.any.js37
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json335
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/constant.json754
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/conv2d.json351
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json547
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/l2_pool2d.json1174
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json335
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/resample2d.json527
-rw-r--r--testing/web-platform/tests/webnn/resources/test_data/triangular.json1101
-rw-r--r--testing/web-platform/tests/webnn/resources/utils.js172
-rw-r--r--testing/web-platform/tests/webnn/resources/utils_validation.js359
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/arg_min_max.https.any.js8
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/batch_normalization.https.any.js190
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/elementwise_binary.https.any.js11
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/gather.https.any.js62
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/gru.https.any.js398
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/layer_normalization.https.any.js8
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/lstm.https.any.js386
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/reduction.https.any.js21
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/resample2d.https.any.js8
-rw-r--r--testing/web-platform/tests/webnn/validation_tests/triangular.https.any.js16
101 files changed, 5317 insertions, 1735 deletions
diff --git a/testing/web-platform/tests/webnn/gpu/arg_min_max.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/arg_min_max.https.any.js
index 76092ea92e..123c8b1048 100644
--- a/testing/web-platform/tests/webnn/gpu/arg_min_max.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/arg_min_max.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-argminmax
-testWebNNOperation(['argMin', 'argMax'], buildOperationWithSingleInput, 'gpu'); \ No newline at end of file
+testWebNNOperation(['argMin', 'argMax'], buildOperationWithSingleInput); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/batch_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/batch_normalization.https.any.js
index 15e66a8bc0..9a1c85db19 100644
--- a/testing/web-platform/tests/webnn/batch_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/batch_normalization.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API batchNormalization operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
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
new file mode 100644
index 0000000000..5b0f46dae0
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/buffer.https.any.js
@@ -0,0 +1,12 @@
+// 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);
+
+testDestroyWebNNBuffer("destroyTwice"); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/cast.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/cast.https.any.js
index 1830364eb5..bde2b9a4ce 100644
--- a/testing/web-platform/tests/webnn/gpu/cast.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/cast.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-cast
-testWebNNOperation('cast', buildCast, 'gpu'); \ No newline at end of file
+testWebNNOperation('cast', buildCast); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/clamp.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/clamp.https.any.js
index 9818aed7c1..7b60c41f2c 100644
--- a/testing/web-platform/tests/webnn/clamp.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/clamp.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API clamp operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/concat.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/concat.https.any.js
index 07073724fe..254e0b657b 100644
--- a/testing/web-platform/tests/webnn/gpu/concat.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/concat.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-concat
-testWebNNOperation('concat', buildConcat, 'gpu'); \ No newline at end of file
+testWebNNOperation('concat', buildConcat); \ No newline at end of file
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
new file mode 100644
index 0000000000..4814734886
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/constant.https.any.js
@@ -0,0 +1,10 @@
+// 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); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/conv2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/conv2d.https.any.js
index b3986b6555..0d9a621356 100644
--- a/testing/web-platform/tests/webnn/gpu/conv2d.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/conv2d.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-conv2d
-testWebNNOperation('conv2d', buildConv2d, 'gpu'); \ No newline at end of file
+testWebNNOperation('conv2d', buildConv2d); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/conv_transpose2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/conv_transpose2d.https.any.js
index 99e76b825e..ee5d28c72a 100644
--- a/testing/web-platform/tests/webnn/conv_transpose2d.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/conv_transpose2d.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API convTranspose2d operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/elementwise_binary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elementwise_binary.https.any.js
index 035d0c77c0..5db14a43a1 100644
--- a/testing/web-platform/tests/webnn/gpu/elementwise_binary.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elementwise_binary.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-binary
-testWebNNOperation(['add', 'sub', 'mul', 'div', 'max', 'min', 'pow'], buildOperationWithTwoInputs, 'gpu'); \ No newline at end of file
+testWebNNOperation(['add', 'sub', 'mul', 'div', 'max', 'min', 'pow'], buildOperationWithTwoInputs); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/elementwise_logical.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elementwise_logical.https.any.js
index e614b94df5..a60c199447 100644
--- a/testing/web-platform/tests/webnn/elementwise_logical.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elementwise_logical.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API element-wise logical operations
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/elementwise_unary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elementwise_unary.https.any.js
index 4cdfee5bcb..8029539eda 100644
--- a/testing/web-platform/tests/webnn/elementwise_unary.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elementwise_unary.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API element-wise unary operations
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/elu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/elu.https.any.js
index 57b624b5da..382faa97fd 100644
--- a/testing/web-platform/tests/webnn/elu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/elu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API elu operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/expand.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/expand.https.any.js
index 82fa891a39..b1be129eac 100644
--- a/testing/web-platform/tests/webnn/gpu/expand.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/expand.https.any.js
@@ -8,4 +8,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-expand
// reuse buildReshape method
-testWebNNOperation('expand', buildReshape, 'gpu'); \ No newline at end of file
+testWebNNOperation('expand', buildReshape); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gather.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gather.https.any.js
index 52bcece804..39b1970563 100644
--- a/testing/web-platform/tests/webnn/gather.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gather.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API gather operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/gemm.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gemm.https.any.js
index a19dc39bbc..61fd7c9b39 100644
--- a/testing/web-platform/tests/webnn/gpu/gemm.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gemm.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-gemm
-testWebNNOperation('gemm', buildGemm, 'gpu'); \ No newline at end of file
+testWebNNOperation('gemm', buildGemm); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/arg_min_max.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/arg_min_max.https.any.js
index cff1d6a955..c700ee5cad 100644
--- a/testing/web-platform/tests/webnn/arg_min_max.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/arg_min_max.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API argMin/Max operations
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-argminmax
-testWebNNOperation(['argMin', 'argMax'], buildOperationWithSingleInput); \ No newline at end of file
+testWebNNOperation(['argMin', 'argMax'], buildOperationWithSingleInput, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/batch_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/batch_normalization.https.any.js
index 90b6def636..534cdf6365 100644
--- a/testing/web-platform/tests/webnn/gpu/batch_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/batch_normalization.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API batchNormalization operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
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
new file mode 100644
index 0000000000..66bba9ef4a
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/buffer.https.any.js
@@ -0,0 +1,12 @@
+// 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'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/cast.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/cast.https.any.js
index c9be45a770..e4309ffd8e 100644
--- a/testing/web-platform/tests/webnn/cast.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/cast.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API cast operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-cast
-testWebNNOperation('cast', buildCast); \ No newline at end of file
+testWebNNOperation('cast', buildCast, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/clamp.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/clamp.https.any.js
index 98313868b6..9b3f93ecc7 100644
--- a/testing/web-platform/tests/webnn/gpu/clamp.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/clamp.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API clamp operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/concat.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/concat.https.any.js
index cce43e492f..c0cfb8626b 100644
--- a/testing/web-platform/tests/webnn/concat.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/concat.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API concat operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-concat
-testWebNNOperation('concat', buildConcat); \ No newline at end of file
+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
new file mode 100644
index 0000000000..77b4d889a2
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/constant.https.any.js
@@ -0,0 +1,10 @@
+// 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/conv2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/conv2d.https.any.js
index b26b35ec67..770540abd8 100644
--- a/testing/web-platform/tests/webnn/conv2d.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/conv2d.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API conv2d operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-conv2d
-testWebNNOperation('conv2d', buildConv2d); \ No newline at end of file
+testWebNNOperation('conv2d', buildConv2d, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/conv_transpose2d.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/conv_transpose2d.https.any.js
index 020bfa9c97..08c441b5b4 100644
--- a/testing/web-platform/tests/webnn/gpu/conv_transpose2d.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/conv_transpose2d.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API convTranspose2d operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/elementwise_binary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_binary.https.any.js
index 06c2404f95..8b9fa486f8 100644
--- a/testing/web-platform/tests/webnn/elementwise_binary.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_binary.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API element-wise binary operations
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// 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); \ No newline at end of file
+testWebNNOperation(['add', 'sub', 'mul', 'div', 'max', 'min', 'pow'], buildOperationWithTwoInputs, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/elementwise_logical.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_logical.https.any.js
index f597ce8e0b..70a887a147 100644
--- a/testing/web-platform/tests/webnn/gpu/elementwise_logical.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_logical.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API element-wise logical operations
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/elementwise_unary.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_unary.https.any.js
index 45978f91ec..8871129311 100644
--- a/testing/web-platform/tests/webnn/gpu/elementwise_unary.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/elementwise_unary.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API element-wise unary operations
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/elu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/elu.https.any.js
index 965bb4d35f..db14442641 100644
--- a/testing/web-platform/tests/webnn/gpu/elu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/elu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API elu operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/expand.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/expand.https.any.js
index 11abb9baa8..f46f463781 100644
--- a/testing/web-platform/tests/webnn/expand.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/expand.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API expand operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
@@ -8,4 +8,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-expand
// reuse buildReshape method
-testWebNNOperation('expand', buildReshape); \ No newline at end of file
+testWebNNOperation('expand', buildReshape, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/gather.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/gather.https.any.js
index 7c8a685c5c..8e457192d8 100644
--- a/testing/web-platform/tests/webnn/gpu/gather.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/gather.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API gather operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gemm.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/gemm.https.any.js
index e5de9521fb..f288c31bed 100644
--- a/testing/web-platform/tests/webnn/gemm.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/gemm.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API gemm operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-gemm
-testWebNNOperation('gemm', buildGemm); \ No newline at end of file
+testWebNNOperation('gemm', buildGemm, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/hard_sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_sigmoid.https.any.js
index b6f2f53b32..d40e42a211 100644
--- a/testing/web-platform/tests/webnn/gpu/hard_sigmoid.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_sigmoid.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API hardSigmoid operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/hard_swish.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_swish.https.any.js
index a1731490bd..031e65ee16 100644
--- a/testing/web-platform/tests/webnn/gpu/hard_swish.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/hard_swish.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API tanh operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/instance_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/instance_normalization.https.any.js
index e1d73de387..ecfaac71ee 100644
--- a/testing/web-platform/tests/webnn/gpu/instance_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/instance_normalization.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API instanceNormalization operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/layer_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/layer_normalization.https.any.js
index 1deb43bee5..0e4f6caebf 100644
--- a/testing/web-platform/tests/webnn/gpu/layer_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/layer_normalization.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API layerNormalization operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/leaky_relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/leaky_relu.https.any.js
index f3a7bd8ba5..9fab2353b9 100644
--- a/testing/web-platform/tests/webnn/gpu/leaky_relu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/leaky_relu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API leakyRelu operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/linear.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/linear.https.any.js
index 48b8d82c1e..ccec2c3eac 100644
--- a/testing/web-platform/tests/webnn/gpu/linear.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/linear.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API linear operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/matmul.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/matmul.https.any.js
index 01fed04e3d..635ce84ac6 100644
--- a/testing/web-platform/tests/webnn/gpu/matmul.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/matmul.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API matmul operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/pad.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/pad.https.any.js
index 05eec653c6..f313e2c9f9 100644
--- a/testing/web-platform/tests/webnn/pad.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/pad.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API pad operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pad
-testWebNNOperation('pad', buildPad); \ No newline at end of file
+testWebNNOperation('pad', buildPad, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/pooling.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/pooling.https.any.js
index df19e57709..837bca2c71 100644
--- a/testing/web-platform/tests/webnn/pooling.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/pooling.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API pooling operations
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pool2d
-testWebNNOperation(['averagePool2d', 'maxPool2d'], buildOperationWithSingleInput); \ No newline at end of file
+testWebNNOperation(['averagePool2d', 'l2Pool2d', 'maxPool2d'], buildOperationWithSingleInput, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/prelu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/prelu.https.any.js
index 5a1580e662..475cd9e5ce 100644
--- a/testing/web-platform/tests/webnn/gpu/prelu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/prelu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API prelu operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/reduction.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/reduction.https.any.js
index 69f9b64df4..0f3cefa02e 100644
--- a/testing/web-platform/tests/webnn/gpu/reduction.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/reduction.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API reduction operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/relu.https.any.js
index dc09846e3b..d1a35367df 100644
--- a/testing/web-platform/tests/webnn/gpu/relu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/relu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API relu operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
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
new file mode 100644
index 0000000000..dd8e441946
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/resample2d.https.any.js
@@ -0,0 +1,10 @@
+// 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/gpu/reshape.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/reshape.https.any.js
index e5145e2403..b0217d2e67 100644
--- a/testing/web-platform/tests/webnn/gpu/reshape.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/reshape.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API reshape operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/sigmoid.https.any.js
index 6c85f5b303..26116c0ff9 100644
--- a/testing/web-platform/tests/webnn/gpu/sigmoid.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/sigmoid.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API sigmoid operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/slice.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/slice.https.any.js
index cb7acefc05..1710c79a9c 100644
--- a/testing/web-platform/tests/webnn/slice.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/slice.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API slice operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-slice
-testWebNNOperation('slice', buildSlice); \ No newline at end of file
+testWebNNOperation('slice', buildSlice, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/softmax.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/softmax.https.any.js
index 9170dd0e14..9eaffe2beb 100644
--- a/testing/web-platform/tests/webnn/gpu/softmax.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/softmax.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API softmax operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/softplus.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/softplus.https.any.js
index a61e5beaef..5f06846113 100644
--- a/testing/web-platform/tests/webnn/gpu/softplus.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/softplus.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API softplus operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/softsign.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/softsign.https.any.js
index f598cbfcef..eac0b7ec40 100644
--- a/testing/web-platform/tests/webnn/gpu/softsign.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/softsign.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API softsign operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/split.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/split.https.any.js
index b6fc5b4d98..3b0aafd787 100644
--- a/testing/web-platform/tests/webnn/split.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/split.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API split operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-split
-testWebNNOperation('split', buildSplit); \ No newline at end of file
+testWebNNOperation('split', buildSplit, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/tanh.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/tanh.https.any.js
index 15a9eeb013..3029f4865a 100644
--- a/testing/web-platform/tests/webnn/gpu/tanh.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/tanh.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API tanh operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/transpose.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/transpose.https.any.js
index 074e18a488..295ef43ec1 100644
--- a/testing/web-platform/tests/webnn/gpu/transpose.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/transpose.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API transpose operation
// META: global=window,dedicatedworker
-// META: script=../resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
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
new file mode 100644
index 0000000000..3e1b0d5ab1
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/triangular.https.any.js
@@ -0,0 +1,10 @@
+// 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/where.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/gpu/where.https.any.js
index 306128a814..49c6cbd4e3 100644
--- a/testing/web-platform/tests/webnn/where.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/gpu/where.https.any.js
@@ -1,10 +1,10 @@
// META: title=test WebNN API where operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../../resources/utils.js
// META: timeout=long
'use strict';
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-where
-testWebNNOperation('where', buildWhere); \ No newline at end of file
+testWebNNOperation('where', buildWhere, 'gpu'); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/hard_sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/hard_sigmoid.https.any.js
index 81bd5124ce..8161a24538 100644
--- a/testing/web-platform/tests/webnn/hard_sigmoid.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/hard_sigmoid.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API hardSigmoid operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/hard_swish.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/hard_swish.https.any.js
index 052c7f2a20..b4a7c53d8d 100644
--- a/testing/web-platform/tests/webnn/hard_swish.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/hard_swish.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API tanh operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/instance_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/instance_normalization.https.any.js
index 0b7a708917..fce879172e 100644
--- a/testing/web-platform/tests/webnn/instance_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/instance_normalization.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API instanceNormalization operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/layer_normalization.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/layer_normalization.https.any.js
index 380db4ea52..ab8a50cc03 100644
--- a/testing/web-platform/tests/webnn/layer_normalization.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/layer_normalization.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API layerNormalization operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/leaky_relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/leaky_relu.https.any.js
index 61539ce92e..2b6f17e95d 100644
--- a/testing/web-platform/tests/webnn/leaky_relu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/leaky_relu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API leakyRelu operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/linear.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/linear.https.any.js
index 4b2c05540b..465b697f29 100644
--- a/testing/web-platform/tests/webnn/linear.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/linear.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API linear operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/matmul.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/matmul.https.any.js
index 8a9882afe6..64eeb37f08 100644
--- a/testing/web-platform/tests/webnn/matmul.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/matmul.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API matmul operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/pad.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/pad.https.any.js
index 26d1bf0f38..f1a2400d1c 100644
--- a/testing/web-platform/tests/webnn/gpu/pad.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/pad.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pad
-testWebNNOperation('pad', buildPad, 'gpu'); \ No newline at end of file
+testWebNNOperation('pad', buildPad); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/pooling.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/pooling.https.any.js
index ab12881881..400d5ed37d 100644
--- a/testing/web-platform/tests/webnn/gpu/pooling.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/pooling.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-pool2d
-testWebNNOperation(['averagePool2d', 'maxPool2d'], buildOperationWithSingleInput, 'gpu'); \ No newline at end of file
+testWebNNOperation(['averagePool2d', 'l2Pool2d', 'maxPool2d'], buildOperationWithSingleInput); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/prelu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/prelu.https.any.js
index c1b2e9fa2a..83cc9db4b4 100644
--- a/testing/web-platform/tests/webnn/prelu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/prelu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API prelu operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/reduction.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduction.https.any.js
index 20bd74d8de..30bfb4ba7a 100644
--- a/testing/web-platform/tests/webnn/reduction.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/reduction.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API reduction operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/relu.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/relu.https.any.js
index 42b64e11de..51e427898f 100644
--- a/testing/web-platform/tests/webnn/relu.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/relu.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API relu operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
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
new file mode 100644
index 0000000000..0b5b3e0032
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/resample2d.https.any.js
@@ -0,0 +1,10 @@
+// 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); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/reshape.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reshape.https.any.js
index e0733635f8..c0dafb176c 100644
--- a/testing/web-platform/tests/webnn/reshape.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/reshape.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API reshape operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/sigmoid.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/sigmoid.https.any.js
index e904d8dfa7..186f468918 100644
--- a/testing/web-platform/tests/webnn/sigmoid.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/sigmoid.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API sigmoid operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/slice.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/slice.https.any.js
index 98e5f422da..6441204517 100644
--- a/testing/web-platform/tests/webnn/gpu/slice.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/slice.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-slice
-testWebNNOperation('slice', buildSlice, 'gpu'); \ No newline at end of file
+testWebNNOperation('slice', buildSlice); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/softmax.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
index 8e5342bd75..143b7d969f 100644
--- a/testing/web-platform/tests/webnn/softmax.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API softmax operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/softplus.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/softplus.https.any.js
index 7096f64a04..fcd6410bdb 100644
--- a/testing/web-platform/tests/webnn/softplus.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/softplus.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API softplus operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/softsign.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/softsign.https.any.js
index 61a7d5365f..6e26afdade 100644
--- a/testing/web-platform/tests/webnn/softsign.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/softsign.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API softsign operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/gpu/split.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/split.https.any.js
index 8eecd76fa1..0de6cb4d8d 100644
--- a/testing/web-platform/tests/webnn/gpu/split.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/split.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-split
-testWebNNOperation('split', buildSplit, 'gpu'); \ No newline at end of file
+testWebNNOperation('split', buildSplit); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/tanh.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/tanh.https.any.js
index d0d45e754b..c5d1f86ab1 100644
--- a/testing/web-platform/tests/webnn/tanh.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/tanh.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API tanh operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
diff --git a/testing/web-platform/tests/webnn/transpose.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/transpose.https.any.js
index 63a123342a..746e53d512 100644
--- a/testing/web-platform/tests/webnn/transpose.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/transpose.https.any.js
@@ -1,6 +1,6 @@
// META: title=test WebNN API transpose operation
// META: global=window,dedicatedworker
-// META: script=./resources/utils.js
+// META: script=../resources/utils.js
// META: timeout=long
'use strict';
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
new file mode 100644
index 0000000000..503f310620
--- /dev/null
+++ b/testing/web-platform/tests/webnn/conformance_tests/triangular.https.any.js
@@ -0,0 +1,10 @@
+// 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); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/gpu/where.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/where.https.any.js
index ec0c5530a0..7926221d3a 100644
--- a/testing/web-platform/tests/webnn/gpu/where.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/where.https.any.js
@@ -7,4 +7,4 @@
// https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-where
-testWebNNOperation('where', buildWhere, 'gpu'); \ No newline at end of file
+testWebNNOperation('where', buildWhere); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/idlharness.https.any.js b/testing/web-platform/tests/webnn/idlharness.https.any.js
index 65e21d5a1d..93e88294ef 100644
--- a/testing/web-platform/tests/webnn/idlharness.https.any.js
+++ b/testing/web-platform/tests/webnn/idlharness.https.any.js
@@ -28,29 +28,18 @@ idl_test(
MLGraph: ['graph']
});
- for (const executionType of ExecutionArray) {
- const isSync = executionType === 'sync';
- if (self.GLOBAL.isWindow() && isSync) {
- continue;
- }
-
- if (isSync) {
- self.context = navigator.ml.createContextSync();
- } else {
- self.context = await navigator.ml.createContext();
- }
-
- self.builder = new MLGraphBuilder(self.context);
- self.input = builder.input('input', {dataType: 'float32', dimensions: [1, 1, 5, 5]});
- self.filter = builder.constant({dataType: 'float32', dimensions: [1, 1, 3, 3]}, new Float32Array(9).fill(1));
- self.relu = builder.relu();
- self.output = builder.conv2d(input, filter, {activation: relu, inputLayout: "nchw"});
-
- if (isSync) {
- self.graph = builder.buildSync({output});
- } else {
- self.graph = await builder.build({output});
- }
- }
+ self.context = await navigator.ml.createContext();
+
+ self.builder = new MLGraphBuilder(self.context);
+ self.input =
+ builder.input('input', {dataType: 'float32', dimensions: [1, 1, 5, 5]});
+ self.filter = builder.constant(
+ {dataType: 'float32', dimensions: [1, 1, 3, 3]},
+ new Float32Array(9).fill(1));
+ self.relu = builder.relu();
+ self.output =
+ builder.conv2d(input, filter, {activation: relu, inputLayout: "nchw"});
+
+ self.graph = await builder.build({output});
}
);
diff --git a/testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json b/testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json
index 5a9f4e28b1..3d0c432273 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json
@@ -534,340 +534,6 @@
}
},
{
- "name": "averagePool2d float32 4D tensor options.autoPad=explicit",
- "inputs": {
- "input": {
- "shape": [1, 2, 5, 5],
- "data": [
- 22.975555502750634,
- 78.15438048012338,
- 9.68611138116071,
- 51.29803808129347,
- 32.19308601456918,
- 87.65037289600019,
- 87.25082191311348,
- 39.49793996935087,
- 80.09963591169489,
- 10.220142557736978,
- 52.60270021646585,
- 1.4128639882603933,
- 11.954064466077474,
- 85.0007506374375,
- 64.7837446465813,
- 88.03128735720126,
- 11.333851214909307,
- 70.61659435728073,
- 84.90442561999888,
- 79.06688041781518,
- 7.328724951604215,
- 35.97796581186121,
- 10.17730631094398,
- 1.4140757517112412,
- 78.10038172113374,
- 91.59549689157087,
- 65.64701225681809,
- 55.14215004436653,
- 18.432438840756184,
- 49.34624267439973,
- 15.648024969290454,
- 68.02723372727797,
- 20.342549040418124,
- 26.72794900604616,
- 64.87446829774323,
- 46.56714896227794,
- 79.57832937136276,
- 4.338463748959498,
- 38.18383968382213,
- 45.253981324455175,
- 80.9717996657439,
- 67.58124910163149,
- 6.026499585657263,
- 29.77881349289366,
- 58.58993337807239,
- 2.2384984647495054,
- 14.505490166700486,
- 68.72449589246624,
- 76.45657404642184,
- 23.53263275794233
- ],
- "type": "float32"
- }
- },
- "options": {
- "padding": [1, 0, 0, 1],
- "autoPad": "explicit"
- },
- "expected": {
- "name": "output",
- "shape": [1, 2, 2, 2],
- "data": [
- 52.43666076660156,
- 49.84208297729492,
- 47.26926803588867,
- 46.15715408325195,
- 46.63268280029297,
- 43.616947174072266,
- 44.72445297241211,
- 44.05451583862305
- ],
- "type": "float32"
- }
- },
- {
- "name": "averagePool2d float32 4D tensor options.autoPad=same-upper",
- "inputs": {
- "input": {
- "shape": [1, 2, 4, 4],
- "data": [
- 18.669797402066955,
- 95.74087629574039,
- 24.142204556566483,
- 51.13168108230512,
- 32.59428648032041,
- 36.33802591707573,
- 27.143744148346705,
- 61.289996123672566,
- 0.728295383811961,
- 60.81457168719891,
- 95.0135160845949,
- 65.57073366405261,
- 24.878494968304032,
- 54.664386232007665,
- 26.61406921126077,
- 52.134243150024886,
- 12.628756510724926,
- 83.86613668699508,
- 10.754655927067148,
- 14.330409913484088,
- 29.797547470611676,
- 4.38582170135331,
- 3.052249580313382,
- 22.562494369151654,
- 6.22880691096237,
- 84.28155043844244,
- 11.095604502619949,
- 43.65773966541213,
- 20.380576521492454,
- 94.70740415350079,
- 29.785210365576088,
- 49.15286022732512
- ],
- "type": "float32"
- }
- },
- "options": {
- "windowDimensions": [3, 3],
- "strides": [2, 2],
- "autoPad": "same-upper"
- },
- "expected": {
- "name": "output",
- "shape": [1, 2, 2, 2],
- "data": [
- 43.46503448486328,
- 54.04864501953125,
- 43.78555679321289,
- 59.8331413269043,
- 27.34345817565918,
- 17.575525283813477,
- 41.079856872558594,
- 33.422855377197266
- ],
- "type": "float32"
- }
- },
- {
- "name": "averagePool2d float32 4D tensor options.autoPad=same-lower",
- "inputs": {
- "input": {
- "shape": [1, 2, 4, 4],
- "data": [
- 18.669797402066955,
- 95.74087629574039,
- 24.142204556566483,
- 51.13168108230512,
- 32.59428648032041,
- 36.33802591707573,
- 27.143744148346705,
- 61.289996123672566,
- 0.728295383811961,
- 60.81457168719891,
- 95.0135160845949,
- 65.57073366405261,
- 24.878494968304032,
- 54.664386232007665,
- 26.61406921126077,
- 52.134243150024886,
- 12.628756510724926,
- 83.86613668699508,
- 10.754655927067148,
- 14.330409913484088,
- 29.797547470611676,
- 4.38582170135331,
- 3.052249580313382,
- 22.562494369151654,
- 6.22880691096237,
- 84.28155043844244,
- 11.095604502619949,
- 43.65773966541213,
- 20.380576521492454,
- 94.70740415350079,
- 29.785210365576088,
- 49.15286022732512
- ],
- "type": "float32"
- }
- },
- "options": {
- "windowDimensions": [3, 3],
- "strides": [2, 2],
- "autoPad": "same-lower"
- },
- "expected": {
- "name": "output",
- "shape": [1, 2, 2, 2],
- "data": [
- 45.83574676513672,
- 49.297752380371094,
- 35.00300979614258,
- 53.28703308105469,
- 32.6695671081543,
- 23.158628463745117,
- 39.963619232177734,
- 38.075660705566406
- ],
- "type": "float32"
- }
- },
- {
- "name": "averagePool2d float32 4D tensor options.autoPad=same-upper ignores options.padding",
- "inputs": {
- "input": {
- "shape": [1, 2, 4, 4],
- "data": [
- 18.669797402066955,
- 95.74087629574039,
- 24.142204556566483,
- 51.13168108230512,
- 32.59428648032041,
- 36.33802591707573,
- 27.143744148346705,
- 61.289996123672566,
- 0.728295383811961,
- 60.81457168719891,
- 95.0135160845949,
- 65.57073366405261,
- 24.878494968304032,
- 54.664386232007665,
- 26.61406921126077,
- 52.134243150024886,
- 12.628756510724926,
- 83.86613668699508,
- 10.754655927067148,
- 14.330409913484088,
- 29.797547470611676,
- 4.38582170135331,
- 3.052249580313382,
- 22.562494369151654,
- 6.22880691096237,
- 84.28155043844244,
- 11.095604502619949,
- 43.65773966541213,
- 20.380576521492454,
- 94.70740415350079,
- 29.785210365576088,
- 49.15286022732512
- ],
- "type": "float32"
- }
- },
- "options": {
- "windowDimensions": [3, 3],
- "padding": [2, 2, 2, 2],
- "strides": [2, 2],
- "autoPad": "same-upper"
- },
- "expected": {
- "name": "output",
- "shape": [1, 2, 2, 2],
- "data": [
- 43.46503448486328,
- 54.04864501953125,
- 43.78555679321289,
- 59.8331413269043,
- 27.34345817565918,
- 17.575525283813477,
- 41.079856872558594,
- 33.422855377197266
- ],
- "type": "float32"
- }
- },
- {
- "name": "averagePool2d float32 4D tensor options.autoPad=same-lower ignores options.padding",
- "inputs": {
- "input": {
- "shape": [1, 2, 4, 4],
- "data": [
- 18.669797402066955,
- 95.74087629574039,
- 24.142204556566483,
- 51.13168108230512,
- 32.59428648032041,
- 36.33802591707573,
- 27.143744148346705,
- 61.289996123672566,
- 0.728295383811961,
- 60.81457168719891,
- 95.0135160845949,
- 65.57073366405261,
- 24.878494968304032,
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- 26.61406921126077,
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- 12.628756510724926,
- 83.86613668699508,
- 10.754655927067148,
- 14.330409913484088,
- 29.797547470611676,
- 4.38582170135331,
- 3.052249580313382,
- 22.562494369151654,
- 6.22880691096237,
- 84.28155043844244,
- 11.095604502619949,
- 43.65773966541213,
- 20.380576521492454,
- 94.70740415350079,
- 29.785210365576088,
- 49.15286022732512
- ],
- "type": "float32"
- }
- },
- "options": {
- "windowDimensions": [3, 3],
- "padding": [2, 2, 2, 2],
- "strides": [2, 2],
- "autoPad": "same-lower"
- },
- "expected": {
- "name": "output",
- "shape": [1, 2, 2, 2],
- "data": [
- 45.83574676513672,
- 49.297752380371094,
- 35.00300979614258,
- 53.28703308105469,
- 32.6695671081543,
- 23.158628463745117,
- 39.963619232177734,
- 38.075660705566406
- ],
- "type": "float32"
- }
- },
- {
"name": "averagePool2d float32 4D tensor options.layout=nchw",
"inputs": {
"input": {
@@ -1650,7 +1316,6 @@
"options": {
"windowDimensions": [3, 3],
"padding": [1, 0, 0, 1],
- "autoPad": "explicit",
"strides": [2, 2],
"layout": "nhwc"
},
diff --git a/testing/web-platform/tests/webnn/resources/test_data/constant.json b/testing/web-platform/tests/webnn/resources/test_data/constant.json
new file mode 100644
index 0000000000..06fe0a7a95
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/constant.json
@@ -0,0 +1,754 @@
+{
+ "tests": [
+ {
+ "name": "constant float32 0D tensor of default float32 type",
+ "inputs": {
+ "start": {
+ "data": 0.22992068529129028,
+ "type": "float32"
+ },
+ "step": {
+ "data": 0.7537541389465332,
+ "type": "float32"
+ }
+ },
+ "outputShape": [],
+ "expected": {
+ "name": "output",
+ "shape": [],
+ "data": [
+ 0.22992068529129028
+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "constant float32 1D tensor of default float32 type",
+ "inputs": {
+ "start": {
+ "data": 0.22992068529129028,
+ "type": "float32"
+ },
+ "step": {
+ "data": 0.7537541389465332,
+ "type": "float32"
+ }
+ },
+ "outputShape": [24],
+ "expected": {
+ "name": "output",
+ "shape": [24],
+ "data": [
+ 0.22992068529129028,
+ 0.9836748242378235,
+ 1.737428903579712,
+ 2.491183042526245,
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+ 15.30500316619873,
+ 16.058757781982422,
+ 16.812511444091797,
+ 17.566265106201172
+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "constant float32 2D tensor of default float32 type",
+ "inputs": {
+ "start": {
+ "data": 0.22992068529129028,
+ "type": "float32"
+ },
+ "step": {
+ "data": 0.7537541389465332,
+ "type": "float32"
+ }
+ },
+ "outputShape": [4, 6],
+ "expected": {
+ "name": "output",
+ "shape": [4, 6],
+ "data": [
+ 0.22992068529129028,
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+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "constant float32 3D tensor of default float32 type",
+ "inputs": {
+ "start": {
+ "data": 0.22992068529129028,
+ "type": "float32"
+ },
+ "step": {
+ "data": 0.7537541389465332,
+ "type": "float32"
+ }
+ },
+ "outputShape": [2, 3, 4],
+ "expected": {
+ "name": "output",
+ "shape": [2, 3, 4],
+ "data": [
+ 0.22992068529129028,
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+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of default float32 type",
+ "inputs": {
+ "start": {
+ "data": 0.22992068529129028,
+ "type": "float32"
+ },
+ "step": {
+ "data": 0.7537541389465332,
+ "type": "float32"
+ }
+ },
+ "outputShape": [2, 2, 2, 3],
+ "expected": {
+ "name": "output",
+ "shape": [2, 2, 2, 3],
+ "data": [
+ 0.22992068529129028,
+ 0.9836748242378235,
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+ 17.566265106201172
+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of default float32 type step > 0",
+ "inputs": {
+ "start": {
+ "data": 0.22992068529129028,
+ "type": "float32"
+ },
+ "step": {
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+ "type": "float32"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of default float32 type step = 0",
+ "inputs": {
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+ "type": "float32"
+ },
+ "step": {
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+ "type": "float32"
+ }
+ },
+ "outputShape": [2, 2, 2, 3],
+ "expected": {
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+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of default float32 type step < 0",
+ "inputs": {
+ "start": {
+ "data": 0.22992068529129028,
+ "type": "float32"
+ },
+ "step": {
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+ "type": "float32"
+ }
+ },
+ "outputShape": [2, 2, 2, 3],
+ "expected": {
+ "name": "output",
+ "shape": [2, 2, 2, 3],
+ "data": [
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+ "type": "float32"
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+ "step": {
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+ {
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+ {
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+ "type": "float32"
+ },
+ "step": {
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+ 25,
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+ 27,
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+ 29,
+ 30
+ ],
+ "type": "int32"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of uint32 type",
+ "inputs": {
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+ "data": 7,
+ "type": "float32"
+ },
+ "step": {
+ "data": 1,
+ "type": "float32"
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+ 30
+ ],
+ "type": "uint32"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of int64 type",
+ "inputs": {
+ "start": {
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+ "type": "float32"
+ },
+ "step": {
+ "data": 1,
+ "type": "float32"
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+ "26",
+ "27",
+ "28",
+ "29",
+ "30"
+ ],
+ "type": "int64"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of int8 type step > 0",
+ "inputs": {
+ "start": {
+ "data": -9,
+ "type": "float32"
+ },
+ "step": {
+ "data": 1,
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+ "outputShape": [2, 2, 2, 3],
+ "type": "int8",
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+ 13,
+ 14
+ ],
+ "type": "int8"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of int8 type step < 0",
+ "inputs": {
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+ "type": "float32"
+ },
+ "step": {
+ "data": -2,
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+ -31,
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+ -35,
+ -37,
+ -39
+ ],
+ "type": "int8"
+ }
+ },
+ {
+ "name": "constant float32 4D tensor of uint8 type",
+ "inputs": {
+ "start": {
+ "data": 7,
+ "type": "float32"
+ },
+ "step": {
+ "data": 1,
+ "type": "float32"
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+ "outputShape": [2, 2, 2, 3],
+ "type": "uint8",
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+ ],
+ "type": "uint8"
+ }
+ }
+ ]
+} \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/conv2d.json b/testing/web-platform/tests/webnn/resources/test_data/conv2d.json
index 5f8cd814a9..13e6b17242 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/conv2d.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/conv2d.json
@@ -421,356 +421,6 @@
}
},
{
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"name": "depthwise conv2d float32 4D input and filter tensors options.groups= input_channels",
"inputs": {
"input": {
@@ -1990,7 +1640,6 @@
"options": {
"padding": [1, 0, 0, 1],
"strides": [1, 1],
- "autoPad": "explicit",
"dilations": [1, 1],
"groups": 2,
"inputLayout": "nchw",
diff --git a/testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json b/testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json
index 42274e6fa3..742752fd41 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json
@@ -972,553 +972,6 @@
}
},
{
- "name": "convTranspose2d float32 4D input and filter tensors options.autoPad=explicit options.padding",
- "inputs": {
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- {
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diff --git a/testing/web-platform/tests/webnn/resources/test_data/l2_pool2d.json b/testing/web-platform/tests/webnn/resources/test_data/l2_pool2d.json
new file mode 100644
index 0000000000..a65687721a
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/l2_pool2d.json
@@ -0,0 +1,1174 @@
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+ "outputSizes": [2, 2]
+ },
+ "expected": {
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+ "data": [
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+ "expected": {
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+ ]
+} \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json b/testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json
index 4532843d2b..216b4c55dd 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json
@@ -464,340 +464,6 @@
}
},
{
- "name": "maxPool2d float32 4D tensor options.autoPad=explicit",
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"name": "maxPool2d float32 4D tensor options.layout=nchw",
"inputs": {
"input": {
@@ -1404,7 +1070,6 @@
"options": {
"windowDimensions": [3, 3],
"padding": [1, 0, 0, 1],
- "autoPad": "explicit",
"strides": [2, 2],
"dilations": [1, 1],
"layout": "nhwc"
diff --git a/testing/web-platform/tests/webnn/resources/test_data/resample2d.json b/testing/web-platform/tests/webnn/resources/test_data/resample2d.json
new file mode 100644
index 0000000000..605d1b55c0
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/resample2d.json
@@ -0,0 +1,527 @@
+{
+ "tests": [
+ {
+ "name": "resample2d float32 4D tensor default options",
+ "inputs": {
+ "input": {
+ "shape": [1, 1, 4, 6], // nchw
+ "data": [
+ 3.8600528355143604,
+ 45.18463077286585,
+ 87.67153742917091,
+ 98.78210347338205,
+ 66.3741434682883,
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+ ],
+ "type": "float32"
+ }
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+ "expected": {
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+ "data": [
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+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "resample2d(upsample) float32 4D tensor options.scales",
+ "inputs": {
+ "input": {
+ "shape": [1, 1, 2, 3],
+ "data": [
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+ 79.10004839481242
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+ "type": "float32"
+ }
+ },
+ "options": {
+ "scales": [2.0, 2.0]
+ },
+ "expected": {
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+ "data": [
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+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "resample2d(upsample) float32 4D tensor options.sizes",
+ "inputs": {
+ "input": {
+ "shape": [1, 1, 2, 3],
+ "data": [
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+ ],
+ "type": "float32"
+ }
+ },
+ "options": {
+ "sizes": [4, 6]
+ },
+ "expected": {
+ "shape": [1, 1, 4, 6],
+ "data": [
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+ 59.92947006225586,
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+ 41.98918914794922,
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+ ],
+ "type": "float32"
+ }
+ },
+ {
+ "name": "resample2d(upsample) float32 4D tensor options.sizes ignored options.scales",
+ "inputs": {
+ "input": {
+ "shape": [1, 1, 2, 3],
+ "data": [
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+ "type": "float32"
+ }
+ },
+ "options": {
+ "scales": [0.5, 0.5],
+ "sizes": [4, 6]
+ },
+ "expected": {
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+ "data": [
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+ "type": "float32"
+ }
+ },
+ {
+ "name": "resample2d(upsample) float32 4D tensor options.axes=[1, 2]",
+ "inputs": {
+ "input": {
+ "shape": [1, 2, 3, 1], // nhwc
+ "data": [
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+ 41.989187594696546,
+ 66.39534663077877,
+ 90.70066412516924,
+ 86.95106056135486,
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+ "type": "float32"
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+ "options": {
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+ "axes": [1, 2]
+ },
+ "expected": {
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+ "data": [
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+ }
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+ {
+ "name": "resample2d(upsample) float32 4D tensor explicit options.axes=[2, 3]",
+ "inputs": {
+ "input": {
+ "shape": [1, 1, 2, 3], // nchw
+ "data": [
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+ {
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+ {
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+ ],
+ "type": "float32"
+ }
+ }
+ ]
+} \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/triangular.json b/testing/web-platform/tests/webnn/resources/test_data/triangular.json
new file mode 100644
index 0000000000..652f780d58
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/triangular.json
@@ -0,0 +1,1101 @@
+{
+ "tests": [
+ {
+ "name": "triangular float32 2D tensor default options",
+ "inputs": {
+ "input": {
+ "shape": [4, 6],
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+ {
+ "name": "triangular float32 3D tensor default options",
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+ {
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+ "options": {
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+ "expected": {
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+ }
+ ]
+} \ 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 f91d6622d3..375c71174a 100644
--- a/testing/web-platform/tests/webnn/resources/utils.js
+++ b/testing/web-platform/tests/webnn/resources/utils.js
@@ -1,7 +1,5 @@
'use strict';
-const ExecutionArray = ['sync', 'async'];
-
// https://webmachinelearning.github.io/webnn/#enumdef-mloperanddatatype
const TypedArrayDict = {
// workaround use Uint16 for Float16
@@ -193,7 +191,7 @@ const getMatmulPrecisionTolerance = (resources, operationName) => {
};
/**
- * Get ULP tolerance of averagePool2d operation.
+ * Get ULP tolerance of averagePool2d or l2Pool2d operation.
* @param {Object} resources - Resources used for building a graph
* @param {String} operationName - An operation name
* @returns {Number} A tolerance number
@@ -284,6 +282,32 @@ const getReductionPrecisionTolerance = (resources, operationName) => {
return tolerance;
};
+/**
+ * Get ULP tolerance of resample2d operations.
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} operationName - An operation name
+ * @returns {Number} A tolerance number
+ */
+const getResample2dPrecisionTolerance = (resources, operationName) => {
+ const options = {...resources.options};
+ let tolerance;
+ if (options.mode && options.mode === 'linear') {
+ // interpolation mode is linear
+ const precisionType = resources.expected.type;
+ if (precisionType === 'float32') {
+ tolerance = 84;
+ } else if (precisionType === 'float16') {
+ tolerance = 10;
+ } else {
+ tolerance = 1;
+ }
+ } else {
+ // interpolation mode is nearest-neighbor
+ tolerance = 0;
+ }
+ return tolerance;
+};
+
// Refer to precision metrics on https://github.com/webmachinelearning/webnn/issues/265#issuecomment-1256242643
const PrecisionMetrics = {
argMax: {ULP: {int64: 0}},
@@ -292,6 +316,7 @@ const PrecisionMetrics = {
cast: {ULP: {float32: 1, float16: 1, int32: 0, uint32: 0, int64: 0, int8: 0, uint8: 0}},
clamp: {ULP: {float32: 0, float16: 0}},
concat: {ULP: {float32: 0, float16: 0}},
+ constant: {ULP: {float32: 2, float16: 2, int32: 0, uint32: 0, int64: 0, int8: 0, uint8: 0}},
conv2d: {ULP: {float32: getConv2dPrecisionTolerance, float16: getConv2dPrecisionTolerance}},
convTranspose2d: {ULP: {float32: getConv2dPrecisionTolerance, float16: getConv2dPrecisionTolerance}},
// Begin Element-wise binary operations
@@ -340,6 +365,7 @@ const PrecisionMetrics = {
pad: {ULP: {float32: 0, float16: 0}},
// Begin Pooling operations
averagePool2d: {ULP: {float32: getAveragePool2dPrecisionTolerance, float16: getAveragePool2dPrecisionTolerance}},
+ l2Pool2d: {ULP: {float32: getAveragePool2dPrecisionTolerance, float16: getAveragePool2dPrecisionTolerance}},
maxPool2d: {ULP: {float32: 0, float16: 0}},
// End Pooling operations
prelu: {ULP: {float32: 1, float16: 1}},
@@ -356,6 +382,7 @@ const PrecisionMetrics = {
reduceSumSquare: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
// End Reduction operations
relu: {ULP: {float32: 0, float16: 0}},
+ resample2d: {ULP: {float32: getResample2dPrecisionTolerance, float16: getResample2dPrecisionTolerance}},
reshape: {ULP: {float32: 0, float16: 0}},
sigmoid: {ULP: {float32: 32+2, float16: 3}}, // float32 (leaving a few ULP for roundoff)
slice: {ULP: {float32: 0, float16: 0}},
@@ -365,6 +392,7 @@ const PrecisionMetrics = {
split: {ULP: {float32: 0, float16: 0}},
tanh: {ATOL: {float32: 1/1024, float16: 1/512}},
transpose: {ULP: {float32: 0, float16: 0}},
+ triangular: {ULP: {float32: 0, float16: 0}},
where: {ULP: {float32: 0, float16: 0}},
};
@@ -635,6 +663,13 @@ const buildConcat = (operationName, builder, resources) => {
return namedOutputOperand;
};
+const buildConstantRange = (operationName, builder, resources) => {
+ const namedOutputOperand = {};
+ // invoke builder.constant(start, step, outputShape, type)
+ namedOutputOperand[resources.expected.name] = builder[operationName](resources.inputs.start, resources.inputs.step, resources.outputShape, resources.type);
+ return namedOutputOperand;
+};
+
const buildConvTranspose2d = (operationName, builder, resources) => {
// MLOperand convTranspose2d(MLOperand input, MLOperand filter, optional MLConvTranspose2dOptions options = {});
const namedOutputOperand = {};
@@ -793,25 +828,7 @@ const buildGraph = (operationName, builder, resources, buildFunc) => {
};
/**
- * Build a graph, synchronously compile graph and execute, then check computed results.
- * @param {String} operationName - An operation name
- * @param {MLContext} context - A ML context
- * @param {MLGraphBuilder} builder - A ML graph builder
- * @param {Object} resources - Resources used for building a graph
- * @param {Function} buildFunc - A build function for an operation
- */
-const runSync = (operationName, context, builder, resources, buildFunc) => {
- // build a graph
- const [namedOutputOperands, inputs, outputs] = buildGraph(operationName, builder, resources, buildFunc);
- // synchronously compile the graph up to the output operand
- const graph = builder.buildSync(namedOutputOperands);
- // synchronously execute the compiled graph.
- context.computeSync(graph, inputs, outputs);
- checkResults(operationName, namedOutputOperands, outputs, resources);
-};
-
-/**
- * Build a graph, asynchronously compile graph and execute, then check computed results.
+ * Build a graph, compile graph and execute, then check computed results.
* @param {String} operationName - An operation name
* @param {MLContext} context - A ML context
* @param {MLGraphBuilder} builder - A ML graph builder
@@ -821,9 +838,9 @@ const runSync = (operationName, context, builder, resources, buildFunc) => {
const run = async (operationName, context, builder, resources, buildFunc) => {
// build a graph
const [namedOutputOperands, inputs, outputs] = buildGraph(operationName, builder, resources, buildFunc);
- // asynchronously compile the graph up to the output operand
+ // compile the graph up to the output operand
const graph = await builder.build(namedOutputOperands);
- // asynchronously execute the compiled graph
+ // execute the compiled graph
const result = await context.compute(graph, inputs, outputs);
checkResults(operationName, namedOutputOperands, result.outputs, resources);
};
@@ -835,6 +852,10 @@ const run = async (operationName, context, builder, resources, buildFunc) => {
* @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;
+ }
let operationNameArray;
if (typeof operationName === 'string') {
operationNameArray = [operationName];
@@ -842,41 +863,18 @@ const testWebNNOperation = (operationName, buildFunc, deviceType = 'cpu') => {
operationNameArray = operationName;
}
- ExecutionArray.forEach(executionType => {
- const isSync = executionType === 'sync';
- if (self.GLOBAL.isWindow() && isSync) {
- return;
- }
- let context;
- let builder;
- if (isSync) {
- // test sync
- operationNameArray.forEach((subOperationName) => {
- const tests = loadTests(subOperationName);
- setup(() => {
- context = navigator.ml.createContextSync({deviceType});
- builder = new MLGraphBuilder(context);
- });
- for (const subTest of tests) {
- test(() => {
- runSync(subOperationName, context, builder, subTest, buildFunc);
- }, `${subTest.name} / ${executionType}`);
- }
- });
- } else {
- // test async
- operationNameArray.forEach((subOperationName) => {
- const tests = loadTests(subOperationName);
- promise_setup(async () => {
- context = await navigator.ml.createContext({deviceType});
- builder = new MLGraphBuilder(context);
- });
- for (const subTest of tests) {
- promise_test(async () => {
- await run(subOperationName, context, builder, subTest, buildFunc);
- }, `${subTest.name} / ${executionType}`);
- }
- });
+ let context;
+ let builder;
+ operationNameArray.forEach((subOperationName) => {
+ const tests = loadTests(subOperationName);
+ promise_setup(async () => {
+ context = await navigator.ml.createContext({deviceType});
+ builder = new MLGraphBuilder(context);
+ });
+ for (const subTest of tests) {
+ promise_test(async () => {
+ await run(subOperationName, context, builder, subTest, buildFunc);
+ }, `${subTest.name}`);
}
});
};
@@ -926,4 +924,60 @@ const toHalf = (value) => {
* the exponent, which is OK. */
bits += m & 1;
return bits;
+};
+
+
+/**
+ * WebNN buffer creation.
+ * @param {MLContext} context - the context used to create the buffer.
+ * @param {Number} bufferSize - Size of the buffer to create, in bytes.
+ */
+const createBuffer = (context, bufferSize) => {
+ let buffer;
+ try {
+ buffer = context.createBuffer({size: bufferSize});
+ assert_equals(buffer.size, bufferSize);
+ } catch (e) {
+ assert_true(e instanceof DOMException);
+ assert_equals(e.name, "NotSupportedError");
+ }
+ return buffer;
+};
+
+/**
+ * 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') => {
+ let context;
+ let buffer;
+ promise_setup(async () => {
+ context = await navigator.ml.createContext({deviceType});
+ buffer = createBuffer(context, 4);
+ });
+ promise_test(async () => {
+ // MLBuffer is not supported for this deviceType.
+ if (buffer === undefined) {
+ return;
+ }
+ buffer.destroy();
+ buffer.destroy();
+ }, `${testName}`);
+};
+
+/**
+ * WebNN create buffer test.
+ * @param {String} testName - The name of the test operation.
+ * @param {Number} bufferSize - Size of the buffer to create, in bytes.
+ * @param {String} deviceType - The execution device type for this test.
+ */
+const testCreateWebNNBuffer = (testName, bufferSize, deviceType = 'cpu') => {
+ let context;
+ promise_setup(async () => {
+ context = await navigator.ml.createContext({deviceType});
+ });
+ promise_test(async () => {
+ createBuffer(context, bufferSize);
+ }, `${testName} / ${bufferSize}`);
}; \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/utils_validation.js b/testing/web-platform/tests/webnn/resources/utils_validation.js
new file mode 100644
index 0000000000..7f1d4a4a94
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/utils_validation.js
@@ -0,0 +1,359 @@
+'use strict';
+
+// https://webmachinelearning.github.io/webnn/#enumdef-mloperanddatatype
+const allWebNNOperandDataTypes = [
+ 'float32',
+ 'float16',
+ 'int32',
+ 'uint32',
+ 'int64',
+ 'uint64',
+ 'int8',
+ 'uint8'
+];
+
+const unsignedLongType = 'unsigned long';
+
+const dimensions0D = [];
+const dimensions1D = [2];
+const dimensions2D = [2, 3];
+const dimensions3D = [2, 3, 4];
+const dimensions4D = [2, 3, 4, 5];
+const dimensions5D = [2, 3, 4, 5, 6];
+
+const adjustOffsetsArray = [
+ // Decrease 1
+ -1,
+ // Increase 1
+ 1
+];
+
+// TODO
+// Add more 5+ dimensions
+const allWebNNDimensionsArray = [
+ dimensions0D,
+ dimensions1D,
+ dimensions2D,
+ dimensions3D,
+ dimensions4D,
+ dimensions5D
+];
+
+const notUnsignedLongAxisArray = [
+ // String
+ 'abc',
+ // BigInt
+ BigInt(100),
+ // Object
+ {
+ value: 1
+ },
+ // Array Object
+ [0, 1],
+ // Date Object
+ new Date("2024-01-01"),
+];
+
+function getRank(inputDimensions) {
+ return inputDimensions.length;
+}
+
+function getAxisArray(inputDimensions) {
+ return Array.from({length: inputDimensions.length}, (_, i) => i);
+}
+
+function getAxesArrayContainSameValues(inputDimensions) {
+ // TODO
+ // Currently this function returns an array containing each element which all have the same value.
+ // For example axes: [0, 1, 2] for 3D input tensor
+ // this function returns
+ // [
+ // // two values are same
+ // [0, 0],
+ // [1, 1],
+ // [2, 2],
+ // // three values are same
+ // [0, 0, 0],
+ // [1, 1, 1]
+ // [2, 2, 2]
+ // ]
+ // while it should return
+ // [
+ // // two values are same
+ // [0, 0],
+ // [1, 1],
+ // [2, 2],
+ // [0, 0, 1],
+ // [0, 0, 2],
+ // [0, 1, 0],
+ // [0, 2, 0],
+ // [1, 0, 0],
+ // [2, 0, 0],
+ // [1, 1, 0],
+ // [1, 1, 2],
+ // [1, 0, 1],
+ // [1, 2, 1],
+ // [0, 1, 1],
+ // [2, 1, 1],
+ // [2, 2, 0],
+ // [2, 2, 1],
+ // [2, 0, 2],
+ // [2, 1, 2],
+ // [0, 2, 2],
+ // [1, 2, 2],
+ // // three (all) values are same
+ // [0, 0, 0],
+ // [1, 1, 1]
+ // [2, 2, 2]
+ // ]
+ const axesArrayContainSameValues = [];
+ const length = inputDimensions.length;
+ if (length >= 2) {
+ const validAxesArrayFull = getAxisArray(inputDimensions);
+ for (let index = 0; index < length; index++) {
+ axesArrayContainSameValues.push(new Array(2).fill(validAxesArrayFull[index]));
+ if (length > 2) {
+ axesArrayContainSameValues.push(new Array(3).fill(validAxesArrayFull[index]));
+ }
+ }
+ }
+ return axesArrayContainSameValues;
+}
+
+function generateUnbroadcastableDimensionsArray(dimensions) {
+ // Currently this function returns an array of some unbroadcastable dimensions.
+ // for example given dimensions [2, 3, 4]
+ // this function returns
+ // [
+ // [3, 3, 4],
+ // [2, 2, 4],
+ // [2, 4, 4],
+ // [2, 3, 3],
+ // [2, 3, 5],
+ // [3],
+ // [5],
+ // [1, 3],
+ // [1, 5],
+ // [1, 1, 3],
+ // [1, 1, 5],
+ // [1, 1, 1, 3],
+ // [1, 1, 1, 5],
+ // ]
+ if (dimensions.every(v => v === 1)) {
+ throw new Error(`[${dimensions}] always can be broadcasted`);
+ }
+ const resultDimensions = [];
+ const length = dimensions.length;
+ if (!dimensions.slice(0, length - 1).every(v => v === 1)) {
+ for (let i = 0; i < length; i++) {
+ if (dimensions[i] !== 1) {
+ for (let offset of [-1, 1]) {
+ const dimensionsB = dimensions.slice();
+ dimensionsB[i] += offset;
+ if (dimensionsB[i] !== 1) {
+ resultDimensions.push(dimensionsB);
+ }
+ }
+ }
+ }
+ }
+ const lastDimensionSize = dimensions[length - 1];
+ if (lastDimensionSize !== 1) {
+ for (let j = 0; j <= length; j++) {
+ if (lastDimensionSize > 2) {
+ resultDimensions.push(Array(j).fill(1).concat([lastDimensionSize - 1]));
+ }
+ resultDimensions.push(Array(j).fill(1).concat([lastDimensionSize + 1]));
+ }
+ }
+ return resultDimensions;
+}
+
+function generateOutOfRangeValuesArray(type) {
+ let range, outsideValueArray;
+ switch (type) {
+ case 'unsigned long':
+ // https://webidl.spec.whatwg.org/#idl-unsigned-long
+ // The unsigned long type is an unsigned integer type that has values in the range [0, 4294967295].
+ range = [0, 4294967295];
+ break;
+ default:
+ throw new Error(`Unsupport ${type}`);
+ }
+ outsideValueArray = [range[0] - 1, range[1] + 1];
+ return outsideValueArray;
+}
+
+let inputIndex = 0;
+let inputAIndex = 0;
+let inputBIndex = 0;
+let context, builder;
+
+test(() => assert_not_equals(navigator.ml, undefined, "ml property is defined on navigator"));
+
+promise_setup(async () => {
+ if (navigator.ml === undefined) {
+ return;
+ }
+ context = await navigator.ml.createContext();
+ builder = new MLGraphBuilder(context);
+}, {explicit_timeout: true});
+
+function validateTwoInputsBroadcastable(operationName) {
+ if (navigator.ml === undefined) {
+ return;
+ }
+ promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ for (let dimensions of allWebNNDimensionsArray) {
+ if (dimensions.length > 0) {
+ const inputA = builder.input(`inputA${++inputAIndex}`, {dataType, dimensions});
+ const unbroadcastableDimensionsArray = generateUnbroadcastableDimensionsArray(dimensions);
+ for (let unbroadcastableDimensions of unbroadcastableDimensionsArray) {
+ const inputB = builder.input(`inputB${++inputBIndex}`, {dataType, dimensions: unbroadcastableDimensions});
+ assert_throws_dom('DataError', () => builder[operationName](inputA, inputB));
+ assert_throws_dom('DataError', () => builder[operationName](inputB, inputA));
+ }
+ }
+ }
+ }
+ }, `[${operationName}] DataError is expected if two inputs aren't broadcastable`);
+}
+
+function validateTwoInputsOfSameDataType(operationName) {
+ if (navigator.ml === undefined) {
+ return;
+ }
+ let operationNameArray;
+ if (typeof operationName === 'string') {
+ operationNameArray = [operationName];
+ } else if (Array.isArray(operationName)) {
+ operationNameArray = operationName;
+ } else {
+ throw new Error(`${operationName} should be an operation name string or an operation name string array`);
+ }
+ for (let subOperationName of operationNameArray) {
+ promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ for (let dimensions of allWebNNDimensionsArray) {
+ const inputA = builder.input(`inputA${++inputAIndex}`, {dataType, dimensions});
+ for (let dataTypeB of allWebNNOperandDataTypes) {
+ if (dataType !== dataTypeB) {
+ const inputB = builder.input(`inputB${++inputBIndex}`, {dataType: dataTypeB, dimensions});
+ assert_throws_dom('DataError', () => builder[subOperationName](inputA, inputB));
+ }
+ }
+ }
+ }
+ }, `[${subOperationName}] DataError is expected if two inputs aren't of same data type`);
+ }
+}
+
+/**
+ * Validate options.axes by given operation and input rank for
+ * argMin/Max / layerNormalization / Reduction operations / resample2d operations
+ * @param {(String[]|String)} operationName - An operation name array or an operation name
+ * @param {Number} [inputRank]
+ */
+function validateOptionsAxes(operationName, inputRank) {
+ if (navigator.ml === undefined) {
+ return;
+ }
+ let operationNameArray;
+ if (typeof operationName === 'string') {
+ operationNameArray = [operationName];
+ } else if (Array.isArray(operationName)) {
+ operationNameArray = operationName;
+ } else {
+ throw new Error(`${operationName} should be an operation name string or an operation name string array`);
+ }
+ const invalidAxisArray = generateOutOfRangeValuesArray(unsignedLongType);
+ for (let subOperationName of operationNameArray) {
+ // TypeError is expected if any of options.axes elements is not an unsigned long interger
+ promise_test(async t => {
+ if (inputRank === undefined) {
+ // argMin/Max / layerNormalization / Reduction operations
+ for (let dataType of allWebNNOperandDataTypes) {
+ for (let dimensions of allWebNNDimensionsArray) {
+ const rank = getRank(dimensions);
+ if (rank >= 1) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions});
+ for (let invalidAxis of invalidAxisArray) {
+ assert_throws_js(TypeError, () => builder[subOperationName](input, {axes: invalidAxis}));
+ }
+ for (let axis of notUnsignedLongAxisArray) {
+ assert_false(typeof axis === 'number' && Number.isInteger(axis), `[${subOperationName}] any of options.axes elements should be of 'unsigned long'`);
+ assert_throws_js(TypeError, () => builder[subOperationName](input, {axes: [axis]}));
+ }
+ }
+ }
+ }
+ } else {
+ // resample2d
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: allWebNNDimensionsArray[inputRank]});
+ for (let invalidAxis of invalidAxisArray) {
+ assert_throws_js(TypeError, () => builder[subOperationName](input, {axes: invalidAxis}));
+ }
+ for (let axis of notUnsignedLongAxisArray) {
+ assert_false(typeof axis === 'number' && Number.isInteger(axis), `[${subOperationName}] any of options.axes elements should be of 'unsigned long'`);
+ assert_throws_js(TypeError, () => builder[subOperationName](input, {axes: [axis]}));
+ }
+ }
+ }
+ }, `[${subOperationName}] TypeError is expected if any of options.axes elements is not an unsigned long interger`);
+
+ // DataError is expected if any of options.axes elements is greater or equal to the size of input
+ promise_test(async t => {
+ if (inputRank === undefined) {
+ // argMin/Max / layerNormalization / Reduction operations
+ for (let dataType of allWebNNOperandDataTypes) {
+ for (let dimensions of allWebNNDimensionsArray) {
+ const rank = getRank(dimensions);
+ if (rank >= 1) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions});
+ assert_throws_dom('DataError', () => builder[subOperationName](input, {axes: [rank]}));
+ assert_throws_dom('DataError', () => builder[subOperationName](input, {axes: [rank + 1]}));
+ }
+ }
+ }
+ } else {
+ // resample2d
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: allWebNNDimensionsArray[inputRank]});
+ assert_throws_dom('DataError', () => builder[subOperationName](input, {axes: [inputRank]}));
+ assert_throws_dom('DataError', () => builder[subOperationName](input, {axes: [inputRank + 1]}));
+ }
+ }
+ }, `[${subOperationName}] DataError is expected if any of options.axes elements is greater or equal to the size of input`);
+
+ // DataError is expected if two or more values are same in the axes sequence
+ promise_test(async t => {
+ if (inputRank === undefined) {
+ // argMin/Max / layerNormalization / Reduction operations
+ for (let dataType of allWebNNOperandDataTypes) {
+ for (let dimensions of allWebNNDimensionsArray) {
+ const rank = getRank(dimensions);
+ if (rank >= 2) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions});
+ const axesArrayContainSameValues = getAxesArrayContainSameValues(dimensions);
+ for (let axes of axesArrayContainSameValues) {
+ assert_throws_dom('DataError', () => builder[subOperationName](input, {axes}));
+ }
+ }
+ }
+ }
+ } else {
+ // resample2d
+ for (let dataType of allWebNNOperandDataTypes) {
+ const dimensions = allWebNNDimensionsArray[inputRank];
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions});
+ const axesArrayContainSameValues = getAxesArrayContainSameValues(dimensions);
+ for (let axes of axesArrayContainSameValues) {
+ assert_throws_dom('DataError', () => builder[subOperationName](input, {axes}));
+ }
+ }
+ }
+ }, `[${subOperationName}] DataError is expected if two or more values are same in the axes sequence`);
+ }
+}
diff --git a/testing/web-platform/tests/webnn/validation_tests/arg_min_max.https.any.js b/testing/web-platform/tests/webnn/validation_tests/arg_min_max.https.any.js
new file mode 100644
index 0000000000..700be83b04
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/arg_min_max.https.any.js
@@ -0,0 +1,8 @@
+// META: title=validation tests for WebNN API argMin/Max operations
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+validateOptionsAxes(['argMin', 'argMax']);
diff --git a/testing/web-platform/tests/webnn/validation_tests/batch_normalization.https.any.js b/testing/web-platform/tests/webnn/validation_tests/batch_normalization.https.any.js
new file mode 100644
index 0000000000..25b542d34e
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/batch_normalization.https.any.js
@@ -0,0 +1,190 @@
+// META: title=validation tests for WebNN API batchNormalization operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+let meanIndex = 0;
+let varianceIndex = 0;
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ const invalidAxisArray = generateOutOfRangeValuesArray(unsignedLongType);
+ for (let axis of validAxisArray) {
+ let size = dimensions2D[axis];
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [size]});
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [size]});
+ for (let invalidAxis of invalidAxisArray) {
+ assert_throws_js(TypeError, () => builder.batchNormalization(input, mean, variance, {axis: invalidAxis}));
+ }
+ }
+ }
+}, "[batchNormalization] TypeError is expected if options.axis is outside the 'unsigned long' value range");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ let size = dimensions2D[axis];
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [size]});
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [size]});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance, {axis: getRank(dimensions2D)}));
+ }
+ }
+}, "[batchNormalization] DataError is expected if options.axis is 'unsigned long' and it's not in the range 0 to the rank of input, exclusive");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ let size = dimensions2D[axis];
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [size]});
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [size]});
+ for (let axis of notUnsignedLongAxisArray) {
+ assert_false(typeof axis === 'number' && Number.isInteger(axis), "[batchNormalization] options.axis should be of 'unsigned long'");
+ assert_throws_js(TypeError, () => builder.batchNormalization(input, mean, variance, {axis}));
+ }
+ }
+ }
+}, '[batchNormalization] TypeError is expected if options.axis is not an unsigned long interger');
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [dimensions2D[axis]]});
+ for (let dimensions of allWebNNDimensionsArray) {
+ if (dimensions.length !== 1) {
+ // set mean not be 1D tensor
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance));
+ }
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if the size of mean.dimensions is not 1");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ let size = dimensions2D[axis];
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [size]});
+ for (let offset of adjustOffsetsArray) {
+ const adjustedSize = size + offset;
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [adjustedSize]});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance, {axis}));
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if mean.dimensions[0] is not equal to input.dimensions[options.axis]");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [dimensions2D[axis]]});
+ for (let dimensions of allWebNNDimensionsArray) {
+ if (dimensions.length !== 1) {
+ // set variance not be 1D tensor
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance));
+ }
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if the size of variance.dimensions is not 1");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ let size = dimensions2D[axis];
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [size]});
+ for (let offset of adjustOffsetsArray) {
+ const adjustedSize = size + offset;
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [adjustedSize]});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance, {axis}));
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if variance.dimensions[0] is not equal to input.dimensions[options.axis]");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [dimensions2D[axis]]});
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [dimensions2D[axis]]});
+ for (let dimensions of allWebNNDimensionsArray) {
+ if (dimensions.length !== 1) {
+ // set scale not be 1D tensor
+ const scale = builder.input('scale', {dataType, dimensions});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance, {axis, scale}));
+ }
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if the size of scale.dimensions is not 1");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ let size = dimensions2D[axis];
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [size]});
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [size]});
+ for (let offset of adjustOffsetsArray) {
+ const adjustedSize = size + offset;
+ const scale = builder.input('scale', {dataType, dimensions: [adjustedSize]});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance, {axis, scale}));
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if scale.dimensions[0] is not equal to input.dimensions[options.axis]");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [dimensions2D[axis]]});
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [dimensions2D[axis]]});
+ for (let dimensions of allWebNNDimensionsArray) {
+ if (dimensions.length !== 1) {
+ // set bias not be 1D tensor
+ const bias = builder.input('bias', {dataType, dimensions});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance, {axis, bias}));
+ }
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if the size of bias.dimensions is not 1");
+
+promise_test(async t => {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions: dimensions2D});
+ const validAxisArray = getAxisArray(dimensions2D);
+ for (let axis of validAxisArray) {
+ let size = dimensions2D[axis];
+ const mean = builder.input(`mean${++meanIndex}`, {dataType, dimensions: [size]});
+ const variance = builder.input(`variance${++varianceIndex}`, {dataType, dimensions: [size]});
+ for (let offset of adjustOffsetsArray) {
+ const adjustedSize = size + offset;
+ const bias = builder.input('bias', {dataType, dimensions: [adjustedSize]});
+ assert_throws_dom('DataError', () => builder.batchNormalization(input, mean, variance, {axis, bias}));
+ }
+ }
+ }
+}, "[batchNormalization] DataError is expected if bias.dimensions[0] is not equal to input.dimensions[options.axis]");
diff --git a/testing/web-platform/tests/webnn/validation_tests/elementwise_binary.https.any.js b/testing/web-platform/tests/webnn/validation_tests/elementwise_binary.https.any.js
new file mode 100644
index 0000000000..97a1a2b93c
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/elementwise_binary.https.any.js
@@ -0,0 +1,11 @@
+// META: title=validation tests for WebNN API element-wise binary operations
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+['add', 'sub', 'mul', 'div', 'max', 'min', 'pow'].forEach((operationName) => {
+ validateTwoInputsOfSameDataType(operationName);
+ validateTwoInputsBroadcastable(operationName);
+});
diff --git a/testing/web-platform/tests/webnn/validation_tests/gather.https.any.js b/testing/web-platform/tests/webnn/validation_tests/gather.https.any.js
new file mode 100644
index 0000000000..67ac7d7be3
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/gather.https.any.js
@@ -0,0 +1,62 @@
+// META: title=validation tests for WebNN API gather operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+const tests = [
+ {
+ name: '[gather] Test gather with default options and 0-D indices',
+ input: {dataType: 'int32', dimensions: [3]},
+ indices: {dataType: 'uint64', dimensions: []},
+ output: {dataType: 'int32', dimensions: []}
+ },
+ {
+ name: '[gather] Test gather with axis = 2',
+ input: {dataType: 'float32', dimensions: [1, 2, 3, 4]},
+ indices: {dataType: 'int64', dimensions: [5, 6]},
+ axis: 2,
+ output: {dataType: 'float32', dimensions: [1, 2, 5, 6, 4]}
+ },
+ {
+ name: '[gather] TypeError is expected if the input is a scalar',
+ input: {dataType: 'float16', dimensions: []},
+ indices: {dataType: 'int64', dimensions: [1]}
+ },
+ {
+ name: '[gather] TypeError is expected if the axis is greater than the rank of input',
+ input: {dataType: 'float16', dimensions: [1, 2, 3]},
+ indices: {dataType: 'int32', dimensions: [5, 6]},
+ axis: 4
+ },
+ {
+ name: '[gather] TypeError is expected if the data type of indices is invalid',
+ input: {dataType: 'float16', dimensions: [1, 2, 3, 4]},
+ indices: {dataType: 'float32', dimensions: [5, 6]}
+ }
+];
+
+tests.forEach(
+ test => promise_test(async t => {
+ const input = builder.input(
+ 'input',
+ {dataType: test.input.dataType, dimensions: test.input.dimensions});
+ const indices = builder.input(
+ 'indices',
+ {dataType: test.indices.dataType, dimensions: test.indices.dimensions});
+
+ const options = {};
+ if (test.axis) {
+ options.axis = test.axis;
+ }
+
+ if (test.output) {
+ const output = builder.gather(input, indices, options);
+ assert_equals(output.dataType(), test.output.dataType);
+ assert_array_equals(output.shape(), test.output.dimensions);
+ } else {
+ assert_throws_js(
+ TypeError, () => builder.gather(input, indices, options));
+ }
+ }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/gru.https.any.js b/testing/web-platform/tests/webnn/validation_tests/gru.https.any.js
new file mode 100644
index 0000000000..295baab9c2
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/gru.https.any.js
@@ -0,0 +1,398 @@
+// META: title=validation tests for WebNN API gru operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+const steps = 2, batchSize = 3, inputSize = 4, hiddenSize = 5,
+ numDirections = 1;
+
+const tests = [
+ {
+ name: '[gru] Test with default options',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ outputs: [
+ { dataType: 'float32', dimensions: [numDirections, batchSize, hiddenSize] }
+ ]
+ },
+ {
+ name: '[gru] Test with given options',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ bias: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 3 * hiddenSize]
+ },
+ recurrentBias: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 3 * hiddenSize]
+ },
+ initialHiddenState: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, batchSize, hiddenSize]
+ },
+ restAfter: true,
+ returnSequence: true,
+ direction: 'both',
+ layout: 'rzn',
+ activations: ['sigmoid', 'relu']
+ },
+ outputs: [
+ {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, batchSize, hiddenSize]
+ },
+ {
+ dataType: 'float32',
+ dimensions: [steps, /*numDirections=*/ 2, batchSize, hiddenSize]
+ }
+ ]
+ },
+ {
+ name: '[gru] TypeError is expected if steps equals to zero',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: 0,
+ hiddenSize: hiddenSize,
+ },
+ {
+ name: '[gru] TypeError is expected if hiddenSize equals to zero',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: 0
+ },
+ {
+ name: '[gru] TypeError is expected if hiddenSize is too large',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: 4294967295,
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the data type of the inputs is not one of the floating point types',
+ input: { dataType: 'uint32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'uint32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'uint32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the rank of input is not 3',
+ input: { dataType: 'float32', dimensions: [steps, batchSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[gru] TypeError is expected if input.dimensions[0] is not equal to steps',
+ input: { dataType: 'float32', dimensions: [1000, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name: '[gru] TypeError is expected if weight.dimensions[1] is not 3 * hiddenSize',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the rank of recurrentWeight is not 3',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight:
+ { dataType: 'float32', dimensions: [numDirections, 3 * hiddenSize] },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the recurrentWeight.dimensions is invalid',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight:
+ { dataType: 'float32', dimensions: [numDirections, 4 * hiddenSize, inputSize] },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the size of options.activations is not 2',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: { activations: ['sigmoid', 'tanh', 'relu'] }
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the rank of options.bias is not 2',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: { bias: { dataType: 'float32', dimensions: [numDirections] } }
+ },
+ {
+ name:
+ '[gru] TypeError is expected if options.bias.dimensions[1] is not 3 * hiddenSize',
+ input: { dataType: 'float32', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: { bias: { dataType: 'float32', dimensions: [numDirections, hiddenSize] } }
+ },
+ {
+ name:
+ '[gru] TypeError is expected if options.recurrentBias.dimensions[1] is not 3 * hiddenSize',
+ input: { dataType: 'float16', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ recurrentBias: { dataType: 'float16', dimensions: [numDirections, 4 * hiddenSize] }
+ }
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the rank of options.initialHiddenState is not 3',
+ input: { dataType: 'float16', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ initialHiddenState: {
+ dataType: 'float16',
+ dimensions: [numDirections, batchSize]
+ }
+ }
+ },
+ {
+ name:
+ '[gru] TypeError is expected if options.initialHiddenState.dimensions[2] is not inputSize',
+ input: { dataType: 'float16', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ initialHiddenState: {
+ dataType: 'float16',
+ dimensions: [numDirections, batchSize, 3 * hiddenSize]
+ }
+ }
+ },
+ {
+ name:
+ '[gru] TypeError is expected if the dataType of options.initialHiddenState is incorrect',
+ input: { dataType: 'float16', dimensions: [steps, batchSize, inputSize] },
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 3 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ initialHiddenState: {
+ dataType: 'uint64',
+ dimensions: [numDirections, batchSize, hiddenSize]
+ }
+ }
+ }
+];
+
+tests.forEach(
+ test => promise_test(async t => {
+ const input = builder.input(
+ 'input',
+ { dataType: test.input.dataType, dimensions: test.input.dimensions });
+ const weight = builder.input(
+ 'weight',
+ { dataType: test.weight.dataType, dimensions: test.weight.dimensions });
+ const recurrentWeight = builder.input('recurrentWeight', {
+ dataType: test.recurrentWeight.dataType,
+ dimensions: test.recurrentWeight.dimensions
+ });
+
+ const options = {};
+ if (test.options) {
+ if (test.options.bias) {
+ options.bias = builder.input('bias', {
+ dataType: test.options.bias.dataType,
+ dimensions: test.options.bias.dimensions
+ });
+ }
+ if (test.options.recurrentBias) {
+ options.bias = builder.input('recurrentBias', {
+ dataType: test.options.recurrentBias.dataType,
+ dimensions: test.options.recurrentBias.dimensions
+ });
+ }
+ if (test.options.initialHiddenState) {
+ options.initialHiddenState = builder.input('initialHiddenState', {
+ dataType: test.options.initialHiddenState.dataType,
+ dimensions: test.options.initialHiddenState.dimensions
+ });
+ }
+ if (test.options.resetAfter) {
+ options.resetAfter = test.options.resetAfter;
+ }
+ if (test.options.returnSequence) {
+ options.returnSequence = test.options.returnSequence;
+ }
+ if (test.options.direction) {
+ options.direction = test.options.direction;
+ }
+ if (test.options.layout) {
+ options.layout = test.options.layout;
+ }
+ if (test.options.activations) {
+ options.activations = [];
+ test.options.activations.forEach(
+ activation => options.activations.push(builder[activation]()));
+ }
+ }
+
+ if (test.outputs) {
+ const outputs = builder.gru(
+ input, weight, recurrentWeight, test.steps, test.hiddenSize,
+ options);
+ assert_equals(outputs.length, test.outputs.length);
+ for (let i = 0; i < outputs.length; ++i) {
+ assert_equals(outputs[i].dataType(), test.outputs[i].dataType);
+ assert_array_equals(outputs[i].shape(), test.outputs[i].dimensions);
+ }
+ } else {
+ assert_throws_js(
+ TypeError,
+ () => builder.gru(
+ input, weight, recurrentWeight, test.steps, test.hiddenSize,
+ options));
+ }
+ }, test.name)); \ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/validation_tests/layer_normalization.https.any.js b/testing/web-platform/tests/webnn/validation_tests/layer_normalization.https.any.js
new file mode 100644
index 0000000000..7dbcf5c74a
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/layer_normalization.https.any.js
@@ -0,0 +1,8 @@
+// META: title=validation tests for WebNN API
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+validateOptionsAxes('layerNormalization', 4);
diff --git a/testing/web-platform/tests/webnn/validation_tests/lstm.https.any.js b/testing/web-platform/tests/webnn/validation_tests/lstm.https.any.js
new file mode 100644
index 0000000000..efa05090ca
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/lstm.https.any.js
@@ -0,0 +1,386 @@
+// META: title=validation tests for WebNN API lstm operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+const steps = 10, batchSize = 5, inputSize = 3, hiddenSize = 8,
+ numDirections = 1;
+
+const tests = [
+ {
+ name: '[lstm] Test with default options',
+ input: {dataType: 'float16', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ outputs: [
+ {dataType: 'float16', dimensions: [numDirections, batchSize, hiddenSize]},
+ {dataType: 'float16', dimensions: [numDirections, batchSize, hiddenSize]}
+ ]
+ },
+ {
+ name: '[lstm] Test with given options',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ bias: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 4 * hiddenSize]
+ },
+ recurrentBias: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 4 * hiddenSize]
+ },
+ peepholeWeight: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, 3 * hiddenSize]
+ },
+ initialHiddenState: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, batchSize, hiddenSize]
+ },
+ initialCellState: {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, batchSize, hiddenSize]
+ },
+ returnSequence: true,
+ direction: 'both',
+ layout: 'ifgo',
+ activations: ['sigmoid', 'relu', 'tanh']
+ },
+ outputs: [
+ {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, batchSize, hiddenSize]
+ },
+ {
+ dataType: 'float32',
+ dimensions: [/*numDirections=*/ 2, batchSize, hiddenSize]
+ },
+ {
+ dataType: 'float32',
+ dimensions: [steps, /*numDirections=*/ 2, batchSize, hiddenSize]
+ }
+ ]
+ },
+ {
+ name: '[lstm] DataError is expected if hiddenSize equals to zero',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: 0
+ },
+ {
+ name: '[lstm] DataError is expected if hiddenSize is too large',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: 4294967295,
+ },
+ {
+ name: '[lstm] DataError is expected if steps equals to zero',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: 0,
+ hiddenSize: hiddenSize,
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the data type is not one of the floating point types',
+ input: {dataType: 'uint32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'uint32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'uint32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the rank of input is not 3',
+ input: {dataType: 'float32', dimensions: [steps, batchSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[lstm] DataError is expected if input.dimensions[0] is not equal to steps',
+ input: {dataType: 'float32', dimensions: [1000, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name: '[lstm] DataError is expected if the shape of weight is incorrect',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, 1000]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the rank of recurrentWeight is not 3',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight:
+ {dataType: 'float32', dimensions: [numDirections, 4 * hiddenSize]},
+ steps: steps,
+ hiddenSize: hiddenSize
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the size of options.activations is not 3',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {activations: ['sigmoid', 'tanh']}
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the rank of options.bias is not 2',
+ input: {dataType: 'float16', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {bias: {dataType: 'float16', dimensions: [numDirections]}}
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the shape of options.recurrentBias.dimensions is incorrect',
+ input: {dataType: 'float16', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ recurrentBias: {dataType: 'float16', dimensions: [numDirections, 1000]}
+ }
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the dataType of options.peepholeWeight is incorrect',
+ input: {dataType: 'float16', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ peepholeWeight:
+ {dataType: 'float32', dimensions: [numDirections, 3 * hiddenSize]}
+ }
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the dataType of options.initialHiddenState is incorrect',
+ input: {dataType: 'float16', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float16',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ initialHiddenState: {
+ dataType: 'uint64',
+ dimensions: [numDirections, batchSize, hiddenSize]
+ }
+ }
+ },
+ {
+ name:
+ '[lstm] DataError is expected if the shape of options.initialCellState is incorrect',
+ input: {dataType: 'float32', dimensions: [steps, batchSize, inputSize]},
+ weight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, inputSize]
+ },
+ recurrentWeight: {
+ dataType: 'float32',
+ dimensions: [numDirections, 4 * hiddenSize, hiddenSize]
+ },
+ steps: steps,
+ hiddenSize: hiddenSize,
+ options: {
+ initialCellState:
+ {dataType: 'float32', dimensions: [numDirections, batchSize, 1000]}
+ }
+ }
+];
+
+tests.forEach(
+ test => promise_test(async t => {
+ const input = builder.input(
+ 'input',
+ {dataType: test.input.dataType, dimensions: test.input.dimensions});
+ const weight = builder.input(
+ 'weight',
+ {dataType: test.weight.dataType, dimensions: test.weight.dimensions});
+ const recurrentWeight = builder.input('recurrentWeight', {
+ dataType: test.recurrentWeight.dataType,
+ dimensions: test.recurrentWeight.dimensions
+ });
+
+ const options = {};
+ if (test.options) {
+ if (test.options.bias) {
+ options.bias = builder.input('bias', {
+ dataType: test.options.bias.dataType,
+ dimensions: test.options.bias.dimensions
+ });
+ }
+ if (test.options.recurrentBias) {
+ options.bias = builder.input('recurrentBias', {
+ dataType: test.options.recurrentBias.dataType,
+ dimensions: test.options.recurrentBias.dimensions
+ });
+ }
+ if (test.options.peepholeWeight) {
+ options.peepholeWeight = builder.input('peepholeWeight', {
+ dataType: test.options.peepholeWeight.dataType,
+ dimensions: test.options.peepholeWeight.dimensions
+ });
+ }
+ if (test.options.initialHiddenState) {
+ options.initialHiddenState = builder.input('initialHiddenState', {
+ dataType: test.options.initialHiddenState.dataType,
+ dimensions: test.options.initialHiddenState.dimensions
+ });
+ }
+ if (test.options.initialCellState) {
+ options.initialCellState = builder.input('initialCellState', {
+ dataType: test.options.initialCellState.dataType,
+ dimensions: test.options.initialCellState.dimensions
+ });
+ }
+ if (test.options.returnSequence) {
+ options.returnSequence = test.options.returnSequence;
+ }
+ if (test.options.direction) {
+ options.direction = test.options.direction;
+ }
+ if (test.options.layout) {
+ options.layout = test.options.layout;
+ }
+ if (test.options.activations) {
+ options.activations = [];
+ test.options.activations.forEach(
+ activation => options.activations.push(builder[activation]()));
+ }
+ }
+
+ if (test.outputs) {
+ const outputs = builder.lstm(
+ input, weight, recurrentWeight, test.steps, test.hiddenSize,
+ options);
+ assert_equals(outputs.length, test.outputs.length);
+ for (let i = 0; i < outputs.length; ++i) {
+ assert_equals(outputs[i].dataType(), test.outputs[i].dataType);
+ assert_array_equals(outputs[i].shape(), test.outputs[i].dimensions);
+ }
+ } else {
+ assert_throws_dom(
+ 'DataError',
+ () => builder.lstm(
+ input, weight, recurrentWeight, test.steps, test.hiddenSize,
+ options));
+ }
+ }, test.name));
diff --git a/testing/web-platform/tests/webnn/validation_tests/reduction.https.any.js b/testing/web-platform/tests/webnn/validation_tests/reduction.https.any.js
new file mode 100644
index 0000000000..65b71239b9
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/reduction.https.any.js
@@ -0,0 +1,21 @@
+// META: title=validation tests for WebNN API reduction operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+[
+ 'reduceL1',
+ 'reduceL2',
+ 'reduceLogSum',
+ 'reduceLogSumExp',
+ 'reduceMax',
+ 'reduceMean',
+ 'reduceMin',
+ 'reduceProduct',
+ 'reduceSum',
+ 'reduceSumSquare',
+].forEach((operationName) => {
+ validateOptionsAxes(operationName);
+});
diff --git a/testing/web-platform/tests/webnn/validation_tests/resample2d.https.any.js b/testing/web-platform/tests/webnn/validation_tests/resample2d.https.any.js
new file mode 100644
index 0000000000..2e00cf297c
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/resample2d.https.any.js
@@ -0,0 +1,8 @@
+// META: title=validation tests for WebNN API resample2d operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+validateOptionsAxes('resample2d', 4);
diff --git a/testing/web-platform/tests/webnn/validation_tests/triangular.https.any.js b/testing/web-platform/tests/webnn/validation_tests/triangular.https.any.js
new file mode 100644
index 0000000000..4e4c368f82
--- /dev/null
+++ b/testing/web-platform/tests/webnn/validation_tests/triangular.https.any.js
@@ -0,0 +1,16 @@
+// META: title=validation tests for WebNN API triangular operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+// META: timeout=long
+
+'use strict';
+
+promise_test(async t => {
+ // The input tensor which is at least 2-D.
+ for (let dimensions of allWebNNDimensionsArray.slice(0, 2)) {
+ for (let dataType of allWebNNOperandDataTypes) {
+ const input = builder.input(`input${++inputIndex}`, {dataType, dimensions});
+ assert_throws_js(TypeError, () => builder.triangular(input));
+ }
+ }
+}, "[triangular] DataError is expected if input's rank is less than 2");