// META: title=validation tests for WebNN API pooling operation
// META: global=window,dedicatedworker
// META: variant=?cpu
// META: variant=?gpu
// META: variant=?npu
// META: script=../resources/utils_validation.js
'use strict';
const kPoolingOperators = ['averagePool2d', 'l2Pool2d', 'maxPool2d'];
kPoolingOperators.forEach((operatorName) => {
validateInputFromAnotherBuilder(
operatorName, {dataType: 'float32', dimensions: [2, 2, 2, 2]});
});
const label = 'pool_2d_xxx';
const tests = [
{
name: 'Test pool2d with default options.',
input: {dataType: 'float32', dimensions: [1, 3, 4, 4]},
output: {dataType: 'float32', dimensions: [1, 3, 1, 1]}
},
{
name: 'Test pool2d with windowDimensions',
input: {dataType: 'float16', dimensions: [1, 3, 4, 4]},
options: {
windowDimensions: [3, 3],
},
output: {dataType: 'float16', dimensions: [1, 3, 2, 2]}
},
{
name: 'Test pool2d with padding.',
input: {dataType: 'float32', dimensions: [1, 3, 5, 5]},
options: {
windowDimensions: [5, 5],
padding: [2, 2, 2, 2],
},
output: {dataType: 'float32', dimensions: [1, 3, 5, 5]}
},
{
name: 'Test pool2d with strides.',
input: {dataType: 'float16', dimensions: [1, 3, 5, 5]},
options: {
windowDimensions: [2, 2],
strides: [2, 2],
},
output: {dataType: 'float16', dimensions: [1, 3, 2, 2]}
},
{
name: 'Test pool2d with strides and padding.',
input: {dataType: 'float32', dimensions: [1, 3, 5, 5]},
options: {
windowDimensions: [3, 3],
padding: [1, 1, 1, 1],
strides: [2, 2],
},
output: {dataType: 'float32', dimensions: [1, 3, 3, 3]}
},
{
name: 'Test pool2d with strides and asymmetric padding.',
input: {dataType: 'float32', dimensions: [1, 3, 7, 7]},
options: {
windowDimensions: [4, 4],
padding: [2, 1, 2, 1],
strides: [2, 2],
},
output: {dataType: 'float32', dimensions: [1, 3, 4, 4]}
},
{
name: 'Test pool2d with strides, padding and roundingType="floor".',
input: {dataType: 'float32', dimensions: [1, 3, 7, 7]},
options: {
windowDimensions: [4, 4],
padding: [1, 1, 1, 1],
strides: [2, 2],
roundingType: 'floor',
},
output: {dataType: 'float32', dimensions: [1, 3, 3, 3]}
},
{
name: 'Test pool2d with strides, padding and roundingType="ceil".',
input: {dataType: 'float16', dimensions: [1, 3, 7, 7]},
options: {
windowDimensions: [4, 4],
padding: [1, 1, 1, 1],
strides: [2, 2],
roundingType: 'ceil',
},
output: {dataType: 'float16', dimensions: [1, 3, 4, 4]}
},
{
name: 'Test pool2d with explicit outputSizes ignored roundingType',
input: {dataType: 'float32', dimensions: [1, 3, 7, 7]},
options: {
windowDimensions: [4, 4],
padding: [1, 1, 1, 1],
strides: [2, 2],
roundingType: 'ceil',
outputSizes: [3, 3],
},
output: {dataType: 'float32', dimensions: [1, 3, 3, 3]}
},
{
name: 'Test pool2d with strides, padding and outputSizes=[3, 3].',
input: {dataType: 'float32', dimensions: [1, 3, 7, 7]},
options: {
windowDimensions: [4, 4],
padding: [1, 1, 1, 1],
strides: [2, 2],
outputSizes: [3, 3],
},
output: {dataType: 'float32', dimensions: [1, 3, 3, 3]}
},
{
name: 'Test pool2d with strides, padding and outputSizes=[4, 4].',
input: {dataType: 'float32', dimensions: [1, 3, 7, 7]},
options: {
windowDimensions: [4, 4],
padding: [1, 1, 1, 1],
strides: [2, 2],
outputSizes: [4, 4],
},
output: {dataType: 'float32', dimensions: [1, 3, 4, 4]}
},
{
name: 'Test pool2d with layout="nchw".',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [3, 3],
layout: 'nchw',
},
output: {dataType: 'float32', dimensions: [1, 2, 3, 3]}
},
{
name: 'Test pool2d with layout="nhwc".',
input: {dataType: 'float16', dimensions: [1, 5, 5, 2]},
options: {
windowDimensions: [3, 3],
layout: 'nhwc',
},
output: {dataType: 'float16', dimensions: [1, 3, 3, 2]}
},
{
name: 'Throw if the input is not a 4-D tensor.',
input: {dataType: 'float32', dimensions: [1, 5, 5]},
options: {label},
},
{
name: 'Throw if the output sizes is incorrect.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [2, 2],
padding: [2, 2, 2, 2],
strides: [2, 2],
outputSizes: [3, 3],
label: label,
},
},
{
name: 'Throw if the length of output sizes is not 2.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [2, 2],
padding: [2, 2, 2, 2],
strides: [2, 2],
outputSizes: [1, 2, 4, 4],
label: label,
},
},
{
name: 'Throw if outputSizes[0] is not greater than 0.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [2, 2],
padding: [2, 2, 2, 2],
strides: [2, 2],
outputSizes: [0, 4],
label: label,
},
},
{
name: 'Throw if outputSizes[1] is not greater than 0.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [2, 2],
padding: [2, 2, 2, 2],
strides: [2, 2],
outputSizes: [4, 0],
label: label,
},
},
{
name: 'Throw if the length of window dimensions is not 2.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [1, 1, 1, 1],
label: label,
},
},
{
name: 'Throw if any window dimension is lesser than 1.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [0, 2],
label: label,
},
},
{
name:
'Throw if the input height is too small to fill the pool window height.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [8, 2],
label: label,
},
},
{
name:
'Throw if the input width is too small to fill the pool window width.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [2, 8],
label: label,
},
},
{
name: 'Throw if the calculated output height is equal to 0.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [6, 3],
label: label,
},
},
{
name: 'Throw if the calculated output width is equal to 0.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
windowDimensions: [3, 6],
label: label,
},
},
{
name: 'Throw if the length of padding is not 4.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
padding: [2, 2],
label: label,
},
},
{
name: 'Throw if the length of strides is not 2.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
strides: [2],
label: label,
},
},
{
name: 'Throw if one stride value is smaller than 1.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
strides: [0, 2],
label: label,
},
},
{
name: 'Throw if the length of dilations is not 2.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
dilations: [1, 1, 2],
label: label,
},
},
{
name: 'Throw if one dilation value is smaller than 1.',
input: {dataType: 'float32', dimensions: [1, 2, 5, 5]},
options: {
dilations: [1, 0],
label: label,
},
},
{
name: 'Throw if the padding height value is too large',
input: {dataType: 'float32', dimensions: [1, 3, 5, 5]},
options: {
padding: [kMaxUnsignedLong, kMaxUnsignedLong, 0, 0],
label: label,
},
},
{
name: 'Throw if the padding width value is too large',
input: {dataType: 'float32', dimensions: [1, 3, 5, 5]},
options: {
padding: [0, 0, kMaxUnsignedLong, kMaxUnsignedLong],
label: label,
},
},
];
tests.forEach(
test => promise_test(async t => {
const builder = new MLGraphBuilder(context);
const input = builder.input(
'input',
{dataType: test.input.dataType, dimensions: test.input.dimensions});
kPoolingOperators.forEach((operatorName) => {
if (test.output) {
const output = builder[operatorName](input, test.options);
assert_equals(output.dataType(), test.output.dataType);
assert_array_equals(output.shape(), test.output.dimensions);
} else {
const regrexp = new RegExp('\\[' + label + '\\]');
assert_throws_with_label(
() => builder[operatorName](input, test.options), regrexp);
}
});
}, test.name));
['int32', 'uint32', 'int8', 'uint8'].forEach(
dataType => promise_test(async t => {
const builder = new MLGraphBuilder(context);
const input = builder.input(
'input', {dataType: dataType, dimensions: [1, 3, 4, 4]});
const output = builder.maxPool2d(input);
assert_equals(output.dataType(), dataType);
assert_array_equals(output.shape(), [1, 3, 1, 1]);
}, `[maxPool2d] Test maxPool2d with data type ${dataType}`));
promise_test(async t => {
const builder = new MLGraphBuilder(context);
const input =
builder.input('input', {dataType: 'int64', dimensions: [1, 2, 3, 3]});
assert_throws_js(TypeError, () => builder.averagePool2d(input));
}, '[averagePool2d] Throw if the input data type is not floating point');
promise_test(async t => {
const builder = new MLGraphBuilder(context);
const input =
builder.input('input', {dataType: 'uint8', dimensions: [1, 2, 4, 4]});
assert_throws_js(TypeError, () => builder.l2Pool2d(input));
}, '[l2Pool2d] Throw if the input data type is not floating point');
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