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Test Info: Warnings
- This test has a WPT meta file that expects 1 subtest issues.
- This WPT test may be referenced by the following Test IDs:
- /webnn/conformance_tests/reshape.https.any.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reshape.https.any.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reshape.https.any.html?npu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reshape.https.any.worker.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reshape.https.any.worker.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reshape.https.any.worker.html?npu - WPT Dashboard Interop Dashboard
// META: title=test WebNN API reshape operation
// META: global=window,dedicatedworker
// META: variant=?cpu
// META: variant=?gpu
// META: variant=?npu
// META: script=../resources/utils.js
// META: timeout=long
'use strict';
// Alter the shape of a tensor to a new shape.
//
// MLOperand reshape(
// MLOperand input, sequence<[EnforceRange] unsigned long> newShape);
const reshapeTests = [
{
'name': 'reshape float32 tensor to a new shape (reorder all dimensions)',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 2, 3], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape float32 tensor to a new shape (reduce dimensions)',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 1, 1, 1, 6], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 1, 1, 6]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 1, 1, 6], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape float32 tensor to a new shape (extend dimensions)',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 2, 2, 3, 1]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 2, 2, 3, 1], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape float32 tensor to a new shape (4D to 4D)',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [3, 2, 2, 2], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3, 1]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 2, 3, 1], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape float32 tensor to 1D tensor',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [3, 2, 2, 2], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (squeeze) float32 2D tensor by eliminating one dimension',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [1, 24], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (squeeze) float32 3D tensor by eliminating one dimension',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 1, 6], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (squeeze) float32 3D tensor by eliminating two dimensions',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [1, 24, 1], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (squeeze) float32 4D tensor by eliminating two dimensions',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [1, 4, 1, 6], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (squeeze) float32 4D tensor by eliminating all dimensions',
'graph': {
'inputs': {
'reshapeInput': {
'data': [-33.82555389404297],
'descriptor': {shape: [1, 1, 1, 1], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': []}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [-33.82555389404297],
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name':
'reshape (squeeze) float32 5D tensor by eliminating four dimensions',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [1, 1, 1, 24, 1], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (squeeze) float32 2D tensor by eliminating 1st dimension',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [1, 24], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
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-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 4, 6, 1]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [1, 4, 6, 1], dataType: 'float32'}
}
}
}
},
{
'name':
'reshape (unsqueeze) float32 3D tensor by adding 2nd and 3rd dimensions',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 12, 1], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments':
[{'input': 'reshapeInput'}, {'newShape': [2, 1, 1, 12, 1]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 1, 1, 12, 1], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (unsqueeze) float32 4D tensor by adding 2nd dimension',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 1, 2, 2, 3]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 1, 2, 2, 3], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (unsqueeze) float32 5D tensor by adding 4th dimension',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 1, 4, 3, 1], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments':
[{'input': 'reshapeInput'}, {'newShape': [2, 1, 4, 1, 3, 1]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 1, 4, 1, 3, 1], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (flatten) float32 3D tensor to 2D',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 12]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 12], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (flatten) float32 4D to 2D',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (flatten) float32 4D to 2D exclusive 1st dimension',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [1, 24], dataType: 'float32'}
}
}
}
},
{
'name': 'reshape (flatten) float32 4D to 2D exclusive 4th dimension',
'graph': {
'inputs': {
'reshapeInput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reshape',
'arguments': [{'input': 'reshapeInput'}, {'newShape': [24, 1]}],
'outputs': 'reshapeOutput'
}],
'expectedOutputs': {
'reshapeOutput': {
'data': [
-30.0561466217041, 99.56941986083984, 88.04620361328125,
-91.87507629394531, -23.7972354888916, -91.28665161132812,
-63.15204620361328, 12.0669527053833, -96.1172866821289,
-44.77365493774414, -80.08650970458984, -64.43756866455078,
27.64195442199707, -96.86306762695312, 83.6834716796875,
50.599483489990234, -20.18765640258789, -1.3904608488082886,
-96.93603515625, 65.34143829345703, 34.835994720458984,
62.01485824584961, -2.8698415756225586, 27.903749465942383
],
'descriptor': {shape: [24, 1], dataType: 'float32'}
}
}
}
}
];
if (navigator.ml) {
reshapeTests.forEach((test) => {
webnn_conformance_test(buildAndExecuteGraph, getPrecisionTolerance, test);
});
} else {
test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
}