Source code
Revision control
Copy as Markdown
Other Tools
Test Info:
- This WPT test may be referenced by the following Test IDs:
- /webnn/conformance_tests/reduce_sum_square.https.any.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reduce_sum_square.https.any.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reduce_sum_square.https.any.html?npu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reduce_sum_square.https.any.worker.html?cpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reduce_sum_square.https.any.worker.html?gpu - WPT Dashboard Interop Dashboard
- /webnn/conformance_tests/reduce_sum_square.https.any.worker.html?npu - WPT Dashboard Interop Dashboard
// META: title=test WebNN API reduction operations
// META: global=window,dedicatedworker
// META: variant=?cpu
// META: variant=?gpu
// META: variant=?npu
// META: script=../resources/utils.js
// META: timeout=long
'use strict';
// Reduce the input tensor along all dimensions, or along the axes specified in
// the axes array parameter.
//
// dictionary MLReduceOptions {
// sequence<[EnforceRange] unsigned long> axes;
// boolean keepDimensions = false;
// };
//
// MLOperand reduceSumSquare(MLOperand input, optional MLReduceOptions options
// = {});
const getReductionOperatorsPrecisionTolerance = (graphResources) => {
return {
metricType: 'ULP',
value: getReducedElementCount(graphResources) * 2,
};
};
const reduceSumSquareTests = [
{
'name': 'reduceSumSquare float32 0D constant tensor default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [52.5615348815918],
'descriptor': {shape: [], dataType: 'float32'},
'constant': true
}
},
'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': {
'reduceSumSquareInput': {
'data': [52.5615348815918],
'descriptor': {shape: [], dataType: 'float32'},
'constant': true
}
},
'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': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [24], dataType: 'float32'},
'constant': true
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 1D tensor all positive default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [24], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 1D tensor all negative default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
-21.45201301574707, -57.30725860595703, -72.8390121459961,
-0.059761520475149155, -71.73678588867188, -44.61909103393555,
-43.12002182006836, -91.3373794555664, -33.17243957519531,
-48.555931091308594, -95.6286392211914, -20.876630783081055,
-16.690837860107422, -39.52110290527344, -7.5107855796813965,
-90.59027099609375, -42.21683120727539, -76.74274444580078,
-98.22420501708984, -60.272953033447266, -74.73202514648438,
-8.543684005737305, -59.888736724853516, -17.99894142150879
],
'descriptor': {shape: [24], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 80052.015625,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name':
'reduceSumSquare float32 1D tensor all positive integers default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52, 48, 2, 66, 30, 39, 14, 23, 81, 94, 78, 64,
38, 16, 63, 11, 46, 95, 17, 47, 40, 53, 87, 43
],
'descriptor': {shape: [24], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput':
{'data': 71347, 'descriptor': {shape: [], dataType: 'float32'}}
}
}
},
{
'name':
'reduceSumSquare float32 1D tensor all negative integers default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
-10, -60, -69, -88, -35, -84, -74, -42, -93, -26, -40, -55,
-92, -26, -39, -30, -61, -16, -16, -36, -9, -89, -45, -29
],
'descriptor': {shape: [24], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput':
{'data': 73634, 'descriptor': {shape: [], dataType: 'float32'}}
}
}
},
{
'name': 'reduceSumSquare float32 1D tensor with empty axes',
'graph': {
'inputs': {
'reduceSumSquareInput':
{'data': [2, 3], 'descriptor': {shape: [2], dataType: 'float32'}}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments':
[{'input': 'reduceSumSquareInput'}, {'options': {'axes': []}}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput':
{'data': [4, 9], 'descriptor': {shape: [2], dataType: 'float32'}}
}
}
},
{
'name': 'reduceSumSquare float32 2D tensor default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [4, 6], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 3D tensor default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 4D tensor default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 5D tensor default options',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 1, 4, 1, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [{'input': 'reduceSumSquareInput'}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 3D tensor options.axes',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments':
[{'input': 'reduceSumSquareInput'}, {'options': {'axes': [2]}}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': [
9709.013671875, 10817.7685546875, 14548.470703125, 16385.8515625,
9287.357421875, 12527.3974609375
],
'descriptor': {shape: [2, 3], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 4D tensor options.axes',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments':
[{'input': 'reduceSumSquareInput'}, {'options': {'axes': [0, 2]}}],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': [
8585.87109375, 7700.654296875, 19889.1796875, 7113.0439453125,
16775.708984375, 13211.3994140625
],
'descriptor': {shape: [2, 3], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 3D tensor options.keepDimensions=false',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [
{'input': 'reduceSumSquareInput'},
{'options': {'keepDimensions': false}}
],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 3D tensor options.keepDimensions=true',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [
{'input': 'reduceSumSquareInput'},
{'options': {'keepDimensions': true}}
],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': [73275.859375],
'descriptor': {shape: [1, 1, 1], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 4D tensor options.keepDimensions=false',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [
{'input': 'reduceSumSquareInput'},
{'options': {'keepDimensions': false}}
],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': 73275.859375,
'descriptor': {shape: [], dataType: 'float32'}
}
}
}
},
{
'name': 'reduceSumSquare float32 4D tensor options.keepDimensions=true',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [
{'input': 'reduceSumSquareInput'},
{'options': {'keepDimensions': true}}
],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': [73275.859375],
'descriptor': {shape: [1, 1, 1, 1], dataType: 'float32'}
}
}
}
},
{
'name':
'reduceSumSquare float32 4D tensor options.axes with options.keepDimensions=false',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [
{'input': 'reduceSumSquareInput'},
{'options': {'axes': [1, 3], 'keepDimensions': false}}
],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': [
12302.474609375, 22772.77734375, 26919.09765625, 11281.5068359375
],
'descriptor': {shape: [2, 2], dataType: 'float32'}
}
}
}
},
{
'name':
'reduceSumSquare float32 4D tensor options.axes with options.keepDimensions=true',
'graph': {
'inputs': {
'reduceSumSquareInput': {
'data': [
52.5615348815918, 2.6261062622070312, 82.04877471923828,
14.401411056518555, 33.96051788330078, 83.9383773803711,
47.445045471191406, 19.177289962768555, 13.493006706237793,
44.152381896972656, 86.53118133544922, 70.20919799804688,
25.67262840270996, 79.73770141601562, 66.42284393310547,
70.40363311767578, 13.503327369689941, 41.225399017333984,
6.654552936553955, 85.79743957519531, 89.91349029541016,
53.55647277832031, 39.48537063598633, 3.9460408687591553
],
'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'}
}
},
'operators': [{
'name': 'reduceSumSquare',
'arguments': [
{'input': 'reduceSumSquareInput'},
{'options': {'axes': [1, 3], 'keepDimensions': true}}
],
'outputs': 'reduceSumSquareOutput'
}],
'expectedOutputs': {
'reduceSumSquareOutput': {
'data': [
12302.474609375, 22772.77734375, 26919.09765625, 11281.5068359375
],
'descriptor': {shape: [2, 1, 2, 1], dataType: 'float32'}
}
}
}
}
];
if (navigator.ml) {
reduceSumSquareTests.forEach((test) => {
webnn_conformance_test(
buildAndExecuteGraph, getReductionOperatorsPrecisionTolerance, test);
});
} else {
test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
}