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Test Info:
- This WPT test may be referenced by the following Test IDs:
- /webnn/conformance_tests/abs.https.any.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/abs.https.any.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/abs.https.any.html?npu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/abs.https.any.worker.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/abs.https.any.worker.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/abs.https.any.worker.html?npu - WPT Dashboard Interop Dashboard
// META: title=test WebNN API element-wise abs operation
// META: global=window,dedicatedworker
// META: variant=?cpu
// META: variant=?gpu
// META: variant=?npu
// META: script=../resources/utils.js
// META: timeout=long
'use strict';
// Compute the absolute value of the input tensor, element-wise.
//
// MLOperand abs(MLOperand input);
const getAbsPrecisionTolerance = (graphResources) => {
const toleranceValueDict = {float32: 0, float16: 0};
const expectedDataType =
getExpectedDataTypeOfSingleOutput(graphResources.expectedOutputs);
return {metricType: 'ULP', value: toleranceValueDict[expectedDataType]};
};
const absTests = [
// abs tests
{
'name': 'abs float32 positive 0D scalar',
'graph': {
'inputs': {
'absInput': {
'data': [49.837242126464844],
'descriptor': {shape: [], dataType: 'float32'}
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [49.837242126464844],
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'abs float32 negative 0D scalar',
'graph': {
'inputs': {
'absInput': {
'data': [-91.03521728515625],
'descriptor': {shape: [], dataType: 'float32'}
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [91.03521728515625],
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'abs float32 1D constant tensor',
'graph': {
'inputs': {
'absInput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, -91.03521728515625,
31.4484920501709, -29.31110954284668, -92.4477310180664,
-15.520709991455078, 80.91279602050781, -38.2097053527832,
53.064762115478516, 99.6537094116211, -21.285049438476562,
90.01982879638672, 18.32451820373535, -33.06915283203125,
30.097660064697266, -74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, -53.206058502197266
],
'descriptor': {shape: [24], dataType: 'float32'},
'constant': true
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, 91.03521728515625,
31.4484920501709, 29.31110954284668, 92.4477310180664,
15.520709991455078, 80.91279602050781, 38.2097053527832,
53.064762115478516, 99.6537094116211, 21.285049438476562,
90.01982879638672, 18.32451820373535, 33.06915283203125,
30.097660064697266, 74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, 53.206058502197266
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'abs float32 1D tensor',
'graph': {
'inputs': {
'absInput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, -91.03521728515625,
31.4484920501709, -29.31110954284668, -92.4477310180664,
-15.520709991455078, 80.91279602050781, -38.2097053527832,
53.064762115478516, 99.6537094116211, -21.285049438476562,
90.01982879638672, 18.32451820373535, -33.06915283203125,
30.097660064697266, -74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, -53.206058502197266
],
'descriptor': {shape: [24], dataType: 'float32'}
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, 91.03521728515625,
31.4484920501709, 29.31110954284668, 92.4477310180664,
15.520709991455078, 80.91279602050781, 38.2097053527832,
53.064762115478516, 99.6537094116211, 21.285049438476562,
90.01982879638672, 18.32451820373535, 33.06915283203125,
30.097660064697266, 74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, 53.206058502197266
],
'descriptor': {shape: [24], dataType: 'float32'}
}
}
}
},
{
'name': 'abs float32 2D tensor',
'graph': {
'inputs': {
'absInput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, -91.03521728515625,
31.4484920501709, -29.31110954284668, -92.4477310180664,
-15.520709991455078, 80.91279602050781, -38.2097053527832,
53.064762115478516, 99.6537094116211, -21.285049438476562,
90.01982879638672, 18.32451820373535, -33.06915283203125,
30.097660064697266, -74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, -53.206058502197266
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, 91.03521728515625,
31.4484920501709, 29.31110954284668, 92.4477310180664,
15.520709991455078, 80.91279602050781, 38.2097053527832,
53.064762115478516, 99.6537094116211, 21.285049438476562,
90.01982879638672, 18.32451820373535, 33.06915283203125,
30.097660064697266, 74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, 53.206058502197266
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
}
}
},
{
'name': 'abs float32 3D tensor',
'graph': {
'inputs': {
'absInput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, -91.03521728515625,
31.4484920501709, -29.31110954284668, -92.4477310180664,
-15.520709991455078, 80.91279602050781, -38.2097053527832,
53.064762115478516, 99.6537094116211, -21.285049438476562,
90.01982879638672, 18.32451820373535, -33.06915283203125,
30.097660064697266, -74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, -53.206058502197266
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, 91.03521728515625,
31.4484920501709, 29.31110954284668, 92.4477310180664,
15.520709991455078, 80.91279602050781, 38.2097053527832,
53.064762115478516, 99.6537094116211, 21.285049438476562,
90.01982879638672, 18.32451820373535, 33.06915283203125,
30.097660064697266, 74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, 53.206058502197266
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
}
}
},
{
'name': 'abs float32 4D tensor',
'graph': {
'inputs': {
'absInput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, -91.03521728515625,
31.4484920501709, -29.31110954284668, -92.4477310180664,
-15.520709991455078, 80.91279602050781, -38.2097053527832,
53.064762115478516, 99.6537094116211, -21.285049438476562,
90.01982879638672, 18.32451820373535, -33.06915283203125,
30.097660064697266, -74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, -53.206058502197266
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, 91.03521728515625,
31.4484920501709, 29.31110954284668, 92.4477310180664,
15.520709991455078, 80.91279602050781, 38.2097053527832,
53.064762115478516, 99.6537094116211, 21.285049438476562,
90.01982879638672, 18.32451820373535, 33.06915283203125,
30.097660064697266, 74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, 53.206058502197266
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
}
}
},
{
'name': 'abs float32 5D tensor',
'graph': {
'inputs': {
'absInput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, -91.03521728515625,
31.4484920501709, -29.31110954284668, -92.4477310180664,
-15.520709991455078, 80.91279602050781, -38.2097053527832,
53.064762115478516, 99.6537094116211, -21.285049438476562,
90.01982879638672, 18.32451820373535, -33.06915283203125,
30.097660064697266, -74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, -53.206058502197266
],
'descriptor': {shape: [2, 1, 4, 1, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'abs',
'arguments': [{'input': 'absInput'}],
'outputs': 'absOutput'
}],
'expectedOutputs': {
'absOutput': {
'data': [
49.837242126464844, 82.09291076660156, 3.1989054679870605,
85.20904541015625, 88.94609069824219, 91.03521728515625,
31.4484920501709, 29.31110954284668, 92.4477310180664,
15.520709991455078, 80.91279602050781, 38.2097053527832,
53.064762115478516, 99.6537094116211, 21.285049438476562,
90.01982879638672, 18.32451820373535, 33.06915283203125,
30.097660064697266, 74.21503448486328, 95.60974884033203,
6.614287376403809, 31.2832088470459, 53.206058502197266
],
'descriptor': {shape: [2, 1, 4, 1, 3], dataType: 'float32'}
}
}
}
}
];
if (navigator.ml) {
absTests.forEach((test) => {
webnn_conformance_test(
buildAndExecuteGraph, getAbsPrecisionTolerance, test);
});
} else {
test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
}