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Test Info:
- This WPT test may be referenced by the following Test IDs:
- /webnn/conformance_tests/identity.https.any.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/identity.https.any.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/identity.https.any.html?npu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/identity.https.any.worker.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/identity.https.any.worker.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/identity.https.any.worker.html?npu - WPT Dashboard Interop Dashboard
// META: title=test WebNN API element-wise identity operation
// META: global=window,dedicatedworker
// META: variant=?cpu
// META: variant=?gpu
// META: variant=?npu
// META: script=../resources/utils.js
// META: timeout=long
'use strict';
// Copy the value of the input tensor to the output tensor, element-wise.
//
// MLOperand identity(MLOperand input);
const getIdentityPrecisionTolerance = (graphResources) => {
const toleranceValueDict = {float32: 0, float16: 0};
const expectedDataType =
getExpectedDataTypeOfSingleOutput(graphResources.expectedOutputs);
return {metricType: 'ULP', value: toleranceValueDict[expectedDataType]};
};
const identityTests = [
{
'name': 'identity float32 0D scalar',
'graph': {
'inputs': {
'identityInput': {
'data': [-4.273642539978027],
'descriptor': {shape: [], dataType: 'float32'}
}
},
'operators': [{
'name': 'identity',
'arguments': [{'input': 'identityInput'}],
'outputs': 'identityOutput'
}],
'expectedOutputs': {
'identityOutput': {
'data': [-4.273642539978027],
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'identity float32 1D constant tensor',
'graph': {
'inputs': {
'identityInput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [24], dataType: 'float32'},
'constant': true
}
},
'operators': [{
'name': 'identity',
'arguments': [{'input': 'identityInput'}],
'outputs': 'identityOutput'
}],
'expectedOutputs': {
'identityOutput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'identity float32 1D tensor',
'graph': {
'inputs': {
'identityInput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [24], dataType: 'float32'}
}
},
'operators': [{
'name': 'identity',
'arguments': [{'input': 'identityInput'}],
'outputs': 'identityOutput'
}],
'expectedOutputs': {
'identityOutput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'identity float32 2D tensor',
'graph': {
'inputs': {
'identityInput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
},
'operators': [{
'name': 'identity',
'arguments': [{'input': 'identityInput'}],
'outputs': 'identityOutput'
}],
'expectedOutputs': {
'identityOutput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
}
}
},
{
'name': 'identity float32 3D tensor',
'graph': {
'inputs': {
'identityInput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'identity',
'arguments': [{'input': 'identityInput'}],
'outputs': 'identityOutput'
}],
'expectedOutputs': {
'identityOutput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
}
}
},
{
'name': 'identity float32 4D tensor',
'graph': {
'inputs': {
'identityInput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'identity',
'arguments': [{'input': 'identityInput'}],
'outputs': 'identityOutput'
}],
'expectedOutputs': {
'identityOutput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
}
}
},
{
'name': 'identity float32 5D tensor',
'graph': {
'inputs': {
'identityInput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [2, 1, 4, 1, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'identity',
'arguments': [{'input': 'identityInput'}],
'outputs': 'identityOutput'
}],
'expectedOutputs': {
'identityOutput': {
'data': [
0.377551406621933, -0.8890897631645203, 9.965806007385254,
7.964576244354248, -4.207889080047607, -3.7487030029296875,
-2.5114004611968994, 5.777673244476318, -4.472823619842529,
-8.405767440795898, -3.8579723834991455, 6.036187648773193,
9.076417922973633, 7.101912021636963, 1.4166420698165894,
-5.644308567047119, -2.5986480712890625, -7.264847278594971,
-9.782458305358887, 5.496699810028076, -9.967339515686035,
-6.901016712188721, -2.8501904010772705, 3.279616355895996
],
'descriptor': {shape: [2, 1, 4, 1, 3], dataType: 'float32'}
}
}
}
}
];
if (navigator.ml) {
identityTests.forEach((test) => {
webnn_conformance_test(
buildAndExecuteGraph, getIdentityPrecisionTolerance, test);
});
} else {
test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
}