commit 0affd6b001c609298d117d93f6ce1a5336d104f1
parent eed22c4811b7707549f69e629c1b89951b453c0f
Author: BruceDai <feng.dai@intel.com>
Date: Fri, 7 Nov 2025 09:02:45 +0000
Bug 1998602 [wpt PR 55900] - webnnn: updated and added some conformance tests of non-constant tensors, a=testonly
Automatic update from web-platform-tests
webnnn: updated and added some conformance tests of non-constant tensors
This CL updates some tests of `dequantizeLinear` and `quantizeLinear`
operators to be of non-constant tensors, besides adding more tests of
non-constant tensors for reduction operations and tile operation to
improve test coverage.
Bug: 427523536
Change-Id: Ieb517a706f6da64ac585843ca5f5a3df096c047b
Cq-Include-Trybots: luci.chromium.try:win11-blink-rel, mac14.arm64-blink-rel, mac14-blink-rel, mac15.arm64-blink-rel, mac15-blink-rel, linux-blink-rel
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/7111740
Commit-Queue: Dai, Feng <feng.dai@intel.com>
Reviewed-by: Reilly Grant <reillyg@chromium.org>
Reviewed-by: Hu, Ningxin <ningxin.hu@intel.com>
Auto-Submit: Dai, Feng <feng.dai@intel.com>
Cr-Commit-Position: refs/heads/main@{#1541028}
--
wpt-commits: 0258cbe3201406545134814475f5b89d4794b61c
wpt-pr: 55900
Diffstat:
13 files changed, 1070 insertions(+), 79 deletions(-)
diff --git a/testing/web-platform/tests/webnn/conformance_tests/dequantizeLinear.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/dequantizeLinear.https.any.js
@@ -148,13 +148,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint8 1D constant tensor with negative float32 1D scale',
+ 'dequantizeLinear uint8 1D tensor with negative float32 1D scale',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [12, 24, 35, 123],
'descriptor': {shape: [4], dataType: 'uint8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [
@@ -194,13 +194,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint8 1D constant tensor with float32 1D scale, implicit block_size = 2',
+ 'dequantizeLinear uint8 1D tensor with float32 1D scale, implicit block_size = 2',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [12, 24, 35, 123],
'descriptor': {shape: [4], dataType: 'uint8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [
@@ -238,13 +238,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear int8 4D constant tensor broadcasting float32 4D scale and int8 4D zeroPoint',
+ 'dequantizeLinear int8 4D tensor broadcasting float32 4D scale and int8 4D zeroPoint',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [-124, 0, 23, 122],
'descriptor': {shape: [1, 1, 2, 2], dataType: 'int8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [0.2800687253475189, -4.617084980010986],
@@ -279,7 +279,7 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear int8 2D constant tensor with float32 2D scale, block_size = [3, 2]',
+ 'dequantizeLinear int8 2D tensor with float32 2D scale, block_size = [3, 2]',
'graph': {
'inputs': {
'dequantizeLinearInput': {
@@ -288,7 +288,7 @@ const dequantizeLinearTests = [
-34, -45, -56, -67, 89, 30, 12, 23, 56, 67, 56, -12
],
'descriptor': {shape: [6, 4], dataType: 'int8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [
@@ -354,7 +354,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [15, 0],
'descriptor': {shape: [2], dataType: 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1202747821807861, 1.1202747821807861],
@@ -392,7 +392,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [10, 12, 14],
'descriptor': {shape: [3], dataType: 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1202747821807861],
@@ -424,13 +424,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint4 4D constant tensor with broadcasting float32 4D scale and uint4 4D zeroPoint',
+ 'dequantizeLinear uint4 4D tensor with broadcasting float32 4D scale and uint4 4D zeroPoint',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [0, 1, 10, 15],
'descriptor': {shape: [1, 1, 2, 2], dataType: 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [
@@ -468,13 +468,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint4 3D input with float32 3D scale, block_size = [1, 1, 2]',
+ 'dequantizeLinear uint4 3D tensor with float32 3D scale, block_size = [1, 1, 2]',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [0, 1, 10, 15],
'descriptor': {shape: [1, 1, 4], dataType: 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [
@@ -518,7 +518,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [-8, -3],
'descriptor': {shape: [2], dataType: 'int4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1202747821807861, 1.1202747821807861],
@@ -555,7 +555,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [-1, 7, 0],
'descriptor': {shape: [3], dataType: 'int4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1202747821807861],
@@ -587,13 +587,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'per-tensor dequantizeLinear for int4 4D constant with float32 4D scale',
+ 'per-tensor dequantizeLinear for int4 4D tensor with float32 4D scale',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [0, -1, -6, 1],
'descriptor': {shape: [1, 1, 2, 2], dataType: 'int4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [
@@ -857,13 +857,13 @@ const dequantizeLinearTests = [
}
},
{
- 'name': 'dequantizeLinear uint8 1D constant tensor with float16 1D scale',
+ 'name': 'dequantizeLinear uint8 1D tensor with float16 1D scale',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [12, 24, 35, 123],
'descriptor': {'shape': [4], 'dataType': 'uint8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [9.34375, 0.280029296875, 4.6171875, 1.1201171875],
@@ -895,13 +895,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint8 1D constant tensor with negative float16 1D scale',
+ 'dequantizeLinear uint8 1D tensor with negative float16 1D scale',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [12, 24, 35, 123],
'descriptor': {'shape': [4], 'dataType': 'uint8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [9.34375, 0.280029296875, -4.6171875, 1.1201171875],
@@ -933,13 +933,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint8 1D constant tensor with float16 1D scale, implicit block_size = 2',
+ 'dequantizeLinear uint8 1D tensor with float16 1D scale, implicit block_size = 2',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [12, 24, 35, 123],
'descriptor': {'shape': [4], 'dataType': 'uint8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [9.34375, -4.6171875],
@@ -971,13 +971,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear int8 4D constant tensor broadcasting float16 4D scale and int8 4D zeroPoint',
+ 'dequantizeLinear int8 4D tensor broadcasting float16 4D scale and int8 4D zeroPoint',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [-124, 0, 23, 122],
'descriptor': {'shape': [1, 1, 2, 2], 'dataType': 'int8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [0.280029296875, -4.6171875],
@@ -1009,7 +1009,7 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear int8 2D constant tensor with float16 2D scale, block_size = [3, 2]',
+ 'dequantizeLinear int8 2D tensor with float16 2D scale, block_size = [3, 2]',
'graph': {
'inputs': {
'dequantizeLinearInput': {
@@ -1018,7 +1018,7 @@ const dequantizeLinearTests = [
-34, -45, -56, -67, 89, 30, 12, 23, 56, 67, 56, -12
],
'descriptor': {'shape': [6, 4], 'dataType': 'int8'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [0.280029296875, -4.6171875, 1.2802734375, -3.6171875],
@@ -1062,7 +1062,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [15, 0],
'descriptor': {'shape': [2], 'dataType': 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1201171875, 1.1201171875],
@@ -1100,7 +1100,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [10, 12, 14],
'descriptor': {'shape': [3], 'dataType': 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1201171875],
@@ -1132,13 +1132,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint4 4D constant tensor with broadcasting float16 4D scale and uint4 4D zeroPoint',
+ 'dequantizeLinear uint4 4D tensor with broadcasting float16 4D scale and uint4 4D zeroPoint',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [0, 1, 10, 15],
'descriptor': {'shape': [1, 1, 2, 2], 'dataType': 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [9.34375, -4.6171875],
@@ -1170,13 +1170,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'dequantizeLinear uint4 3D input with float16 3D scale, block_size = [1, 1, 2]',
+ 'dequantizeLinear uint4 3D tensor with float16 3D scale, block_size = [1, 1, 2]',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [0, 1, 10, 15],
'descriptor': {'shape': [1, 1, 4], 'dataType': 'uint4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [9.34375, -4.6171875],
@@ -1214,7 +1214,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [-8, -3],
'descriptor': {'shape': [2], 'dataType': 'int4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1201171875, 1.1201171875],
@@ -1251,7 +1251,7 @@ const dequantizeLinearTests = [
'dequantizeLinearInput': {
'data': [-1, 7, 0],
'descriptor': {'shape': [3], 'dataType': 'int4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1201171875],
@@ -1283,13 +1283,13 @@ const dequantizeLinearTests = [
},
{
'name':
- 'per-tensor dequantizeLinear for int4 4D constant with float16 4D scale',
+ 'per-tensor dequantizeLinear for int4 4D tensor with float16 4D scale',
'graph': {
'inputs': {
'dequantizeLinearInput': {
'data': [0, -1, -6, 1],
'descriptor': {'shape': [1, 1, 2, 2], 'dataType': 'int4'},
- 'constant': true
+ 'constant': false
},
'dequantizeLinearScale': {
'data': [1.1201171875, -4.6171875, 6.2421875, 3.841796875],
diff --git a/testing/web-platform/tests/webnn/conformance_tests/quantizeLinear.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/quantizeLinear.https.any.js
@@ -28,7 +28,7 @@ const quantizeLinearTests = [
// float32 tests
{
'name':
- 'quantizeLinear float32 0D tensor with int8 0D zeroPoint',
+ 'quantizeLinear float32 0D constant tensor with int8 0D zeroPoint',
'graph': {
'inputs': {
'quantizeLinearInput': {
@@ -62,6 +62,41 @@ const quantizeLinearTests = [
}
},
{
+ 'name':
+ 'quantizeLinear float32 0D tensor with int8 0D zeroPoint',
+ 'graph': {
+ 'inputs': {
+ 'quantizeLinearInput': {
+ 'data': [10.794857501983643],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ },
+ 'quantizeLinearScale': {
+ 'data': [1.1202747821807861],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': true
+ },
+ 'quantizeLinearZeroPoint': {
+ 'data': [1],
+ 'descriptor': {shape: [], dataType: 'int8'},
+ 'constant': true
+ }
+ },
+ 'operators': [{
+ 'name': 'quantizeLinear',
+ 'arguments': [
+ {'input': 'quantizeLinearInput'}, {'scale': 'quantizeLinearScale'},
+ {'zeroPoint': 'quantizeLinearZeroPoint'}
+ ],
+ 'outputs': 'quantizeLinearOutput'
+ }],
+ 'expectedOutputs': {
+ 'quantizeLinearOutput':
+ {'data': [11], 'descriptor': {shape: [], dataType: 'int8'}}
+ }
+ }
+ },
+ {
'name': 'quantizeLinear float32 1D constant tensor with uint8 1D zeroPoint',
'graph': {
'inputs': {
@@ -151,7 +186,7 @@ const quantizeLinearTests = [
},
{
'name':
- 'quantizeLinear float32 2D constant tensor broadcasting zeroPoint and scale',
+ 'quantizeLinear float32 2D tensor broadcasting zeroPoint and scale',
'graph': {
'inputs': {
'quantizeLinearInput': {
@@ -160,7 +195,7 @@ const quantizeLinearTests = [
6.108623504638672
],
'descriptor': {shape: [2, 2], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [9.343092918395996],
@@ -191,7 +226,7 @@ const quantizeLinearTests = [
},
{
'name':
- 'quantizeLinear float32 4D constant tensor broadcasting scale and zeroPoint',
+ 'quantizeLinear float32 4D tensor broadcasting scale and zeroPoint',
'graph': {
'inputs': {
'quantizeLinearInput': {
@@ -200,7 +235,7 @@ const quantizeLinearTests = [
6.108623504638672
],
'descriptor': {shape: [1, 1, 2, 2], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [0.2800687253475189, 4.617084980010986],
@@ -230,7 +265,7 @@ const quantizeLinearTests = [
}
},
{
- 'name': 'per-tensor quantizeLinear for float32 4D constant',
+ 'name': 'per-tensor quantizeLinear for float32 4D tensor',
'graph': {
'inputs': {
'quantizeLinearInput': {
@@ -239,7 +274,7 @@ const quantizeLinearTests = [
6.108623504638672
],
'descriptor': {shape: [1, 1, 2, 2], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [
@@ -273,7 +308,7 @@ const quantizeLinearTests = [
},
{
'name':
- 'quantizeLinear float32 3D input with implicit block_size = [1, 2, 1].',
+ 'quantizeLinear float32 3D tensor with implicit block_size = [1, 2, 1].',
'graph': {
'inputs': {
'quantizeLinearInput': {
@@ -282,7 +317,7 @@ const quantizeLinearTests = [
6.108623504638672
],
'descriptor': {shape: [1, 4, 1], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [0.2800687253475189, -4.617084980010986],
@@ -319,7 +354,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.794857501983643],
'descriptor': {shape: [], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1202747821807861],
@@ -354,7 +389,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.794857501983643, 3.23434354545],
'descriptor': {shape: [2], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1202747821807861, 1.1202747821807861],
@@ -392,7 +427,7 @@ const quantizeLinearTests = [
5.794857501983643, 0, 7.23434354545
],
'descriptor': {shape: [3, 2], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1202747821807861, 2.1202747821807861],
@@ -434,7 +469,7 @@ const quantizeLinearTests = [
7.23434354545
],
'descriptor': {shape: [3, 4], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1202747821807861, 2.1202747821807861],
@@ -474,7 +509,7 @@ const quantizeLinearTests = [
3.794857501983643
],
'descriptor': {shape: [5], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1202747821807861],
@@ -511,7 +546,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.794857501983643, 3.23434354545],
'descriptor': {shape: [2], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1202747821807861, 1.1202747821807861],
@@ -549,7 +584,7 @@ const quantizeLinearTests = [
4.794857501983643, 3.23434354545
],
'descriptor': {shape: [6], dataType: 'float32'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1202747821807861, 1.1202747821807861],
@@ -619,7 +654,7 @@ const quantizeLinearTests = [
// float16 tests
{
'name':
- 'quantizeLinear float16 0D tensor with int8 0D zeroPoint',
+ 'quantizeLinear float16 0D constant tensor with int8 0D zeroPoint',
'graph': {
'inputs': {
'quantizeLinearInput': {
@@ -653,13 +688,48 @@ const quantizeLinearTests = [
}
},
{
- 'name': 'quantizeLinear float16 1D constant tensor with uint8 1D zeroPoint',
+ 'name':
+ 'quantizeLinear float16 0D tensor with int8 0D zeroPoint',
+ 'graph': {
+ 'inputs': {
+ 'quantizeLinearInput': {
+ 'data': [10.796875],
+ 'descriptor': {'shape': [], 'dataType': 'float16'},
+ 'constant': false
+ },
+ 'quantizeLinearScale': {
+ 'data': [1.1201171875],
+ 'descriptor': {'shape': [], 'dataType': 'float16'},
+ 'constant': true
+ },
+ 'quantizeLinearZeroPoint': {
+ 'data': [1],
+ 'descriptor': {'shape': [], 'dataType': 'int8'},
+ 'constant': true
+ }
+ },
+ 'operators': [{
+ 'name': 'quantizeLinear',
+ 'arguments': [
+ {'input': 'quantizeLinearInput'}, {'scale': 'quantizeLinearScale'},
+ {'zeroPoint': 'quantizeLinearZeroPoint'}
+ ],
+ 'outputs': 'quantizeLinearOutput'
+ }],
+ 'expectedOutputs': {
+ 'quantizeLinearOutput':
+ {'data': [11], 'descriptor': {'shape': [], 'dataType': 'int8'}}
+ }
+ }
+ },
+ {
+ 'name': 'quantizeLinear float16 1D tensor with uint8 1D zeroPoint',
'graph': {
'inputs': {
'quantizeLinearInput': {
'data': [-2.548828125, -4.79296875, 8.4140625, 6.109375],
'descriptor': {'shape': [4], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [9.34375, 0.280029296875, 4.6171875, 1.1201171875],
@@ -689,13 +759,13 @@ const quantizeLinearTests = [
}
},
{
- 'name': 'quantizeLinear float16 1D constant tensor with negative scale',
+ 'name': 'quantizeLinear float16 1D tensor with negative scale',
'graph': {
'inputs': {
'quantizeLinearInput': {
'data': [-2.548828125, -4.79296875, 8.4140625, 6.109375],
'descriptor': {'shape': [4], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [9.34375, 0.280029296875, -4.6171875, 1.1201171875],
@@ -726,13 +796,13 @@ const quantizeLinearTests = [
},
{
'name':
- 'quantizeLinear float16 2D constant tensor broadcasting zeroPoint and scale',
+ 'quantizeLinear float16 2D tensor broadcasting zeroPoint and scale',
'graph': {
'inputs': {
'quantizeLinearInput': {
'data': [-2.548828125, -4.79296875, 8.4140625, 6.109375],
'descriptor': {'shape': [2, 2], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [9.34375],
@@ -763,13 +833,13 @@ const quantizeLinearTests = [
},
{
'name':
- 'quantizeLinear float16 4D constant tensor broadcasting scale and zeroPoint',
+ 'quantizeLinear float16 4D tensor broadcasting scale and zeroPoint',
'graph': {
'inputs': {
'quantizeLinearInput': {
'data': [-2.548828125, -4.79296875, 8.4140625, 6.109375],
'descriptor': {'shape': [1, 1, 2, 2], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [0.280029296875, 4.6171875],
@@ -799,13 +869,13 @@ const quantizeLinearTests = [
}
},
{
- 'name': 'per-tensor quantizeLinear for float16 4D constant',
+ 'name': 'per-tensor quantizeLinear for float16 4D tensor',
'graph': {
'inputs': {
'quantizeLinearInput': {
'data': [-2.548828125, -4.79296875, 8.4140625, 6.109375],
'descriptor': {'shape': [1, 1, 2, 2], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [0.280029296875, -4.6171875, 0.280029296875, -4.6171875],
@@ -836,13 +906,13 @@ const quantizeLinearTests = [
},
{
'name':
- 'quantizeLinear float16 3D input with implicit block_size = [1, 2, 1].',
+ 'quantizeLinear float16 3D tensor with implicit block_size = [1, 2, 1].',
'graph': {
'inputs': {
'quantizeLinearInput': {
'data': [-2.548828125, -4.79296875, 8.4140625, 6.109375],
'descriptor': {'shape': [1, 4, 1], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [0.280029296875, -4.6171875],
@@ -879,7 +949,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.79296875],
'descriptor': {'shape': [], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1201171875],
@@ -914,7 +984,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.79296875, 3.234375],
'descriptor': {'shape': [2], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1201171875, 1.1201171875],
@@ -949,7 +1019,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.79296875, 3.234375, 2.794921875, 5.79296875, 0, 7.234375],
'descriptor': {'shape': [3, 2], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1201171875, 2.12109375],
@@ -989,7 +1059,7 @@ const quantizeLinearTests = [
4.79296875, 3.234375, 2.794921875, 5.79296875, 0, 7.234375
],
'descriptor': {'shape': [3, 4], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1201171875, 2.12109375],
@@ -1026,7 +1096,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.79296875, 2.794921875, 1.794921875, 0, 3.794921875],
'descriptor': {'shape': [5], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1201171875],
@@ -1063,7 +1133,7 @@ const quantizeLinearTests = [
'quantizeLinearInput': {
'data': [4.79296875, 3.234375],
'descriptor': {'shape': [2], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1201171875, 1.1201171875],
@@ -1101,7 +1171,7 @@ const quantizeLinearTests = [
4.794857501983643, 3.23434354545
],
'descriptor': {'shape': [6], 'dataType': 'float16'},
- 'constant': true
+ 'constant': false
},
'quantizeLinearScale': {
'data': [1.1201171875, 1.1201171875],
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_l1.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_l1.https.any.js
@@ -44,6 +44,29 @@ const reduceL1Tests = [
}
},
{
+ 'name': 'reduceL1 float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceL1Input': {
+ 'data': [5.50882625579834],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL1',
+ 'arguments': [{'input': 'reduceL1Input'}],
+ 'outputs': 'reduceL1Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL1Output': {
+ 'data': 5.50882625579834,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceL1 float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -67,6 +90,29 @@ const reduceL1Tests = [
}
},
{
+ 'name': 'reduceL1 float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceL1Input': {
+ 'data': [5.50882625579834],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL1',
+ 'arguments': [{'input': 'reduceL1Input'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceL1Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL1Output': {
+ 'data': 5.50882625579834,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceL1 float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -654,6 +700,29 @@ const reduceL1Tests = [
}
},
{
+ 'name': 'reduceL1 float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceL1Input': {
+ 'data': [5.5078125],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL1',
+ 'arguments': [{'input': 'reduceL1Input'}],
+ 'outputs': 'reduceL1Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL1Output': {
+ 'data': [5.5078125],
+ 'descriptor': {shape: [], dataType: 'float16'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceL1 float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -677,6 +746,29 @@ const reduceL1Tests = [
}
},
{
+ 'name': 'reduceL1 float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceL1Input': {
+ 'data': [5.5078125],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL1',
+ 'arguments': [{'input': 'reduceL1Input'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceL1Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL1Output': {
+ 'data': [5.5078125],
+ 'descriptor': {shape: [], dataType: 'float16'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceL1 float16 1D constant tensor all positive default options',
'graph': {
'inputs': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_l2.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_l2.https.any.js
@@ -45,6 +45,29 @@ const reduceL2Tests = [
}
},
{
+ 'name': 'reduceL2 float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceL2Input': {
+ 'data': [4.860228061676025],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL2',
+ 'arguments': [{'input': 'reduceL2Input'}],
+ 'outputs': 'reduceL2Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL2Output': {
+ 'data': 4.860228061676025,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceL2 float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -68,6 +91,29 @@ const reduceL2Tests = [
}
},
{
+ 'name': 'reduceL2 float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceL2Input': {
+ 'data': [4.860228061676025],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL2',
+ 'arguments': [{'input': 'reduceL2Input'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceL2Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL2Output': {
+ 'data': 4.860228061676025,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceL2 float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -655,6 +701,27 @@ const reduceL2Tests = [
}
},
{
+ 'name': 'reduceL2 float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceL2Input': {
+ 'data': [4.859375],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL2',
+ 'arguments': [{'input': 'reduceL2Input'}],
+ 'outputs': 'reduceL2Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL2Output':
+ {'data': [4.859375], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceL2 float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -676,6 +743,27 @@ const reduceL2Tests = [
}
},
{
+ 'name': 'reduceL2 float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceL2Input': {
+ 'data': [4.859375],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceL2',
+ 'arguments': [{'input': 'reduceL2Input'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceL2Output'
+ }],
+ 'expectedOutputs': {
+ 'reduceL2Output':
+ {'data': [4.859375], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceL2 float16 1D constant tensor all positive default options',
'graph': {
'inputs': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_log_sum.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_log_sum.https.any.js
@@ -45,6 +45,29 @@ const reduceLogSumTests = [
}
},
{
+ 'name': 'reduceLogSum float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumInput': {
+ 'data': [64.54827117919922],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSum',
+ 'arguments': [{'input': 'reduceLogSumInput'}],
+ 'outputs': 'reduceLogSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumOutput': {
+ 'data': 4.167413234710693,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceLogSum float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -69,6 +92,30 @@ const reduceLogSumTests = [
}
},
{
+ 'name': 'reduceLogSum float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumInput': {
+ 'data': [64.54827117919922],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSum',
+ 'arguments':
+ [{'input': 'reduceLogSumInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceLogSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumOutput': {
+ 'data': 4.167413234710693,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceLogSum float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -610,6 +657,29 @@ const reduceLogSumTests = [
}
},
{
+ 'name': 'reduceLogSum float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumInput': {
+ 'data': [64.5625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSum',
+ 'arguments': [{'input': 'reduceLogSumInput'}],
+ 'outputs': 'reduceLogSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumOutput': {
+ 'data': [4.16796875],
+ 'descriptor': {shape: [], dataType: 'float16'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceLogSum float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -634,6 +704,30 @@ const reduceLogSumTests = [
}
},
{
+ 'name': 'reduceLogSum float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumInput': {
+ 'data': [64.5625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSum',
+ 'arguments':
+ [{'input': 'reduceLogSumInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceLogSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumOutput': {
+ 'data': [4.16796875],
+ 'descriptor': {shape: [], dataType: 'float16'}
+ }
+ }
+ }
+ },
+ {
'name':
'reduceLogSum float16 1D constant tensor all non-negative default options',
'graph': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_log_sum_exp.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_log_sum_exp.https.any.js
@@ -45,6 +45,29 @@ const reduceLogSumExpTests = [
}
},
{
+ 'name': 'reduceLogSumExp float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumExpInput': {
+ 'data': [0.7974132895469666],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSumExp',
+ 'arguments': [{'input': 'reduceLogSumExpInput'}],
+ 'outputs': 'reduceLogSumExpOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumExpOutput': {
+ 'data': 0.7974132895469666,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceLogSumExp float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -69,6 +92,30 @@ const reduceLogSumExpTests = [
}
},
{
+ 'name': 'reduceLogSumExp float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumExpInput': {
+ 'data': [0.7974132895469666],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSumExp',
+ 'arguments':
+ [{'input': 'reduceLogSumExpInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceLogSumExpOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumExpOutput': {
+ 'data': 0.7974132895469666,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceLogSumExp float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -671,6 +718,28 @@ const reduceLogSumExpTests = [
}
},
{
+ 'name': 'reduceLogSumExp float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumExpInput': {
+ 'data': [0.79736328125],
+ 'descriptor': {shape: [], dataType: 'float16'}
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSumExp',
+ 'arguments': [{'input': 'reduceLogSumExpInput'}],
+ 'outputs': 'reduceLogSumExpOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumExpOutput': {
+ 'data': [0.79736328125],
+ 'descriptor': {shape: [], dataType: 'float16'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceLogSumExp float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -695,6 +764,29 @@ const reduceLogSumExpTests = [
}
},
{
+ 'name': 'reduceLogSumExp float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceLogSumExpInput': {
+ 'data': [0.79736328125],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceLogSumExp',
+ 'arguments':
+ [{'input': 'reduceLogSumExpInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceLogSumExpOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceLogSumExpOutput': {
+ 'data': [0.79736328125],
+ 'descriptor': {shape: [], dataType: 'float16'}
+ }
+ }
+ }
+ },
+ {
'name':
'reduceLogSumExp float16 1D constant tensor all positive default options',
'graph': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_max.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_max.https.any.js
@@ -44,6 +44,29 @@ const reduceMaxTests = [
}
},
{
+ 'name': 'reduceMax float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceMaxInput': {
+ 'data': [32.16658401489258],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMax',
+ 'arguments': [{'input': 'reduceMaxInput'}],
+ 'outputs': 'reduceMaxOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMaxOutput': {
+ 'data': 32.16658401489258,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceMax float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -67,6 +90,29 @@ const reduceMaxTests = [
}
},
{
+ 'name': 'reduceMax float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceMaxInput': {
+ 'data': [32.16658401489258],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMax',
+ 'arguments': [{'input': 'reduceMaxInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceMaxOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMaxOutput': {
+ 'data': 32.16658401489258,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceMax float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -577,6 +623,27 @@ const reduceMaxTests = [
}
},
{
+ 'name': 'reduceMax float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceMaxInput': {
+ 'data': [32.15625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMax',
+ 'arguments': [{'input': 'reduceMaxInput'}],
+ 'outputs': 'reduceMaxOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMaxOutput':
+ {'data': [32.15625], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceMax float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -598,6 +665,27 @@ const reduceMaxTests = [
}
},
{
+ 'name': 'reduceMax float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceMaxInput': {
+ 'data': [32.15625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMax',
+ 'arguments': [{'input': 'reduceMaxInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceMaxOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMaxOutput':
+ {'data': [32.15625], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceMax float16 1D constant tensor default options',
'graph': {
'inputs': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_mean.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_mean.https.any.js
@@ -44,6 +44,29 @@ const reduceMeanTests = [
}
},
{
+ 'name': 'reduceMean float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceMeanInput': {
+ 'data': [95.84498596191406],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMean',
+ 'arguments': [{'input': 'reduceMeanInput'}],
+ 'outputs': 'reduceMeanOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMeanOutput': {
+ 'data': 95.84498596191406,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceMean float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -67,6 +90,29 @@ const reduceMeanTests = [
}
},
{
+ 'name': 'reduceMean float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceMeanInput': {
+ 'data': [95.84498596191406],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMean',
+ 'arguments': [{'input': 'reduceMeanInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceMeanOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMeanOutput': {
+ 'data': 95.84498596191406,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceMean float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -661,6 +707,27 @@ const reduceMeanTests = [
}
},
{
+ 'name': 'reduceMean float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceMeanInput': {
+ 'data': [95.875],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMean',
+ 'arguments': [{'input': 'reduceMeanInput'}],
+ 'outputs': 'reduceMeanOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMeanOutput':
+ {'data': [95.875], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceMean float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -682,6 +749,27 @@ const reduceMeanTests = [
}
},
{
+ 'name': 'reduceMean float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceMeanInput': {
+ 'data': [95.875],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMean',
+ 'arguments': [{'input': 'reduceMeanInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceMeanOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMeanOutput':
+ {'data': [95.875], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name':
'reduceMean float16 1D constant tensor all positive default options',
'graph': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_min.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_min.https.any.js
@@ -44,6 +44,29 @@ const reduceMinTests = [
}
},
{
+ 'name': 'reduceMin float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceMinInput': {
+ 'data': [-58.76195526123047],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMin',
+ 'arguments': [{'input': 'reduceMinInput'}],
+ 'outputs': 'reduceMinOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMinOutput': {
+ 'data': -58.76195526123047,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceMin float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -67,6 +90,29 @@ const reduceMinTests = [
}
},
{
+ 'name': 'reduceMin float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceMinInput': {
+ 'data': [-58.76195526123047],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMin',
+ 'arguments': [{'input': 'reduceMinInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceMinOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMinOutput': {
+ 'data': -58.76195526123047,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceMin float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -577,6 +623,27 @@ const reduceMinTests = [
}
},
{
+ 'name': 'reduceMin float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceMinInput': {
+ 'data': [-58.75],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMin',
+ 'arguments': [{'input': 'reduceMinInput'}],
+ 'outputs': 'reduceMinOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMinOutput':
+ {'data': [-58.75], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceMin float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -598,6 +665,27 @@ const reduceMinTests = [
}
},
{
+ 'name': 'reduceMin float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceMinInput': {
+ 'data': [-58.75],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceMin',
+ 'arguments': [{'input': 'reduceMinInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceMinOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceMinOutput':
+ {'data': [-58.75], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceMin float16 1D constant tensor default options',
'graph': {
'inputs': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_product.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_product.https.any.js
@@ -45,6 +45,29 @@ const reduceProductTests = [
}
},
{
+ 'name': 'reduceProduct float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceProductInput': {
+ 'data': [-68.75911712646484],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceProduct',
+ 'arguments': [{'input': 'reduceProductInput'}],
+ 'outputs': 'reduceProductOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceProductOutput': {
+ 'data': -68.75911712646484,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceProduct float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -69,6 +92,30 @@ const reduceProductTests = [
}
},
{
+ 'name': 'reduceProduct float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceProductInput': {
+ 'data': [-68.75911712646484],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceProduct',
+ 'arguments':
+ [{'input': 'reduceProductInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceProductOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceProductOutput': {
+ 'data': -68.75911712646484,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceProduct float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -577,6 +624,27 @@ const reduceProductTests = [
}
},
{
+ 'name': 'reduceProduct float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceProductInput': {
+ 'data': [-68.75],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceProduct',
+ 'arguments': [{'input': 'reduceProductInput'}],
+ 'outputs': 'reduceProductOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceProductOutput':
+ {'data': [-68.75], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceProduct float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -599,6 +667,28 @@ const reduceProductTests = [
}
},
{
+ 'name': 'reduceProduct float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceProductInput': {
+ 'data': [-68.75],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceProduct',
+ 'arguments':
+ [{'input': 'reduceProductInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceProductOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceProductOutput':
+ {'data': [-68.75], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceProduct float16 1D constant tensor default options',
'graph': {
'inputs': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_sum.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_sum.https.any.js
@@ -44,6 +44,29 @@ const reduceSumTests = [
}
},
{
+ 'name': 'reduceSum float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumInput': {
+ 'data': [69.6038589477539],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSum',
+ 'arguments': [{'input': 'reduceSumInput'}],
+ 'outputs': 'reduceSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumOutput': {
+ 'data': 69.6038589477539,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceSum float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -67,6 +90,29 @@ const reduceSumTests = [
}
},
{
+ 'name': 'reduceSum float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumInput': {
+ 'data': [69.6038589477539],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSum',
+ 'arguments': [{'input': 'reduceSumInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumOutput': {
+ 'data': 69.6038589477539,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceSum float32 1D constant tensor empty axes',
'graph': {
'inputs': {
@@ -654,6 +700,27 @@ const reduceSumTests = [
}
},
{
+ 'name': 'reduceSum float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumInput': {
+ 'data': [69.625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSum',
+ 'arguments': [{'input': 'reduceSumInput'}],
+ 'outputs': 'reduceSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumOutput':
+ {'data': [69.625], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceSum float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -675,6 +742,27 @@ const reduceSumTests = [
}
},
{
+ 'name': 'reduceSum float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumInput': {
+ 'data': [69.625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSum',
+ 'arguments': [{'input': 'reduceSumInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceSumOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumOutput':
+ {'data': [69.625], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceSum float16 1D constant tensor all positive default options',
'graph': {
'inputs': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/reduce_sum_square.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/reduce_sum_square.https.any.js
@@ -45,6 +45,29 @@ const reduceSumSquareTests = [
}
},
{
+ 'name': 'reduceSumSquare float32 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumSquareInput': {
+ 'data': [52.5615348815918],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSumSquare',
+ 'arguments': [{'input': 'reduceSumSquareInput'}],
+ 'outputs': 'reduceSumSquareOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumSquareOutput': {
+ 'data': 2762.71484375,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name': 'reduceSumSquare float32 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -69,6 +92,30 @@ const reduceSumSquareTests = [
}
},
{
+ 'name': 'reduceSumSquare float32 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumSquareInput': {
+ 'data': [52.5615348815918],
+ 'descriptor': {shape: [], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSumSquare',
+ 'arguments':
+ [{'input': 'reduceSumSquareInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceSumSquareOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumSquareOutput': {
+ 'data': 2762.71484375,
+ 'descriptor': {shape: [], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
'name':
'reduceSumSquare float32 1D constant tensor all positive default options',
'graph': {
@@ -658,6 +705,27 @@ const reduceSumSquareTests = [
}
},
{
+ 'name': 'reduceSumSquare float16 0D tensor default options',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumSquareInput': {
+ 'data': [52.5625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSumSquare',
+ 'arguments': [{'input': 'reduceSumSquareInput'}],
+ 'outputs': 'reduceSumSquareOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumSquareOutput':
+ {'data': [2762], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name': 'reduceSumSquare float16 0D constant tensor empty axes',
'graph': {
'inputs': {
@@ -680,6 +748,28 @@ const reduceSumSquareTests = [
}
},
{
+ 'name': 'reduceSumSquare float16 0D tensor empty axes',
+ 'graph': {
+ 'inputs': {
+ 'reduceSumSquareInput': {
+ 'data': [52.5625],
+ 'descriptor': {shape: [], dataType: 'float16'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'reduceSumSquare',
+ 'arguments':
+ [{'input': 'reduceSumSquareInput'}, {'options': {'axes': []}}],
+ 'outputs': 'reduceSumSquareOutput'
+ }],
+ 'expectedOutputs': {
+ 'reduceSumSquareOutput':
+ {'data': [2762], 'descriptor': {shape: [], dataType: 'float16'}}
+ }
+ }
+ },
+ {
'name':
'reduceSumSquare float16 1D constant tensor all positive default options',
'graph': {
diff --git a/testing/web-platform/tests/webnn/conformance_tests/tile.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/tile.https.any.js
@@ -63,13 +63,36 @@ const tileTests = [
}
},
{
- 'name': 'tile float16 1D constant tensor',
+ 'name': 'tile float32 1D tensor',
+ 'graph': {
+ 'inputs': {
+ 'tileInput': {
+ 'data': [1, 2, 3, 4],
+ 'descriptor': {shape: [4], dataType: 'float32'},
+ 'constant': false
+ }
+ },
+ 'operators': [{
+ 'name': 'tile',
+ 'arguments': [{'input': 'tileInput'}, {'repetitions': [2]}],
+ 'outputs': 'tileOutput'
+ }],
+ 'expectedOutputs': {
+ 'tileOutput': {
+ 'data': [1, 2, 3, 4, 1, 2, 3, 4],
+ 'descriptor': {shape: [8], dataType: 'float32'}
+ }
+ }
+ }
+ },
+ {
+ 'name': 'tile float16 1D tensor',
'graph': {
'inputs': {
'tileInput': {
'data': [1, 2, 3, 4],
'descriptor': {shape: [4], dataType: 'float16'},
- 'constant': true
+ 'constant': false
}
},
'operators': [{
@@ -92,7 +115,7 @@ const tileTests = [
'tileInput': {
'data': [1, 2, 3, 4],
'descriptor': {shape: [2, 2], dataType: 'float16'},
- 'constant': true
+ 'constant': false
}
},
'operators': [{
@@ -118,7 +141,7 @@ const tileTests = [
'tileInput': {
'data': [1, 2, 3, 4],
'descriptor': {shape: [2, 2], dataType: 'uint32'},
- 'constant': true
+ 'constant': false
}
},
'operators': [{
@@ -144,7 +167,7 @@ const tileTests = [
'tileInput': {
'data': [1, 2, 3, 4],
'descriptor': {shape: [1, 1, 2, 2], dataType: 'int32'},
- 'constant': true
+ 'constant': false
}
},
'operators': [{
