156 lines
4.3 KiB
JavaScript
156 lines
4.3 KiB
JavaScript
// META: title=validation tests for WebNN API pad operation
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// META: global=window
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// META: variant=?cpu
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// META: variant=?gpu
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// META: variant=?npu
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// META: script=../resources/utils_validation.js
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'use strict';
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const label = 'pad_xxx';
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const regrexp = new RegExp('\\[' + label + '\\]');
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multi_builder_test(async (t, builder, otherBuilder) => {
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const inputFromOtherBuilder =
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otherBuilder.input('input', {dataType: 'float32', shape: [2, 2]});
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const beginningPadding = [1, 1];
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const endingPadding = [1, 1];
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assert_throws_js(
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TypeError,
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() =>
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builder.pad(inputFromOtherBuilder, beginningPadding, endingPadding));
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}, '[pad] throw if input is from another builder');
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promise_test(async t => {
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const builder = new MLGraphBuilder(context);
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const input = builder.input('input', {
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dataType: 'float32',
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shape: [1, context.opSupportLimits().maxTensorByteLength / 4]});
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const options = {};
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options.value = 0;
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options.mode = 'constant';
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options.label = label;
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const beginningPadding = [1, 2];
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const endingPadding = [1, 2];
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assert_throws_with_label(
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() => builder.pad(input, beginningPadding, endingPadding, options), regrexp);
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}, '[pad] throw if the output tensor byte length exceeds limit');
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const tests = [
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{
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name:
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'[pad] Test with default options, beginningPadding=[1, 2] and endingPadding=[1, 2].',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [1, 2],
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endingPadding: [1, 2],
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options: {
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mode: 'constant',
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value: 0,
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},
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output: {dataType: 'float32', shape: [4, 7]}
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},
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{
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name: '[pad] Throw if building pad for scalar input.',
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input: {dataType: 'float32', shape: []},
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beginningPadding: [],
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endingPadding: [],
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options: {label}
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},
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{
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name:
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'[pad] Throw if the length of beginningPadding is not equal to the input rank.',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [1],
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endingPadding: [1, 2],
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options: {
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mode: 'edge',
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value: 0,
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label: label,
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},
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},
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{
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name:
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'[pad] Throw if the length of endingPadding is not equal to the input rank.',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [1, 0],
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endingPadding: [1, 2, 0],
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options: {
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mode: 'reflection',
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label: label,
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},
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},
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{
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name:
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'[pad] Throw if beginningPadding[index] is equal to inputShape[index] on reflection mode.',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [2, 0],
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endingPadding: [1, 2],
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options: {
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mode: 'reflection',
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label: label,
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},
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},
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{
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name:
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'[pad] Throw if beginningPadding[index] is greater than inputShape[index] on reflection mode.',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [3, 0],
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endingPadding: [1, 2],
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options: {
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mode: 'reflection',
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label: label,
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},
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},
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{
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name:
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'[pad] Throw if endingPadding[index] is equal to inputShape[index] on reflection mode.',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [1, 0],
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endingPadding: [1, 3],
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options: {
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mode: 'reflection',
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label: label,
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},
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},
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{
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name:
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'[pad] Throw if endingPadding[index] is greater than inputShape[index] on reflection mode.',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [1, 0],
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endingPadding: [1, 4],
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options: {
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mode: 'reflection',
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label: label,
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},
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},
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{
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name: '[pad] Throw if the padding of one dimension is too large.',
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input: {dataType: 'float32', shape: [2, 3]},
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beginningPadding: [2294967295, 0],
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endingPadding: [3294967295, 2],
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options: {
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mode: 'reflection',
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label: label,
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},
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},
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];
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tests.forEach(
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test => promise_test(async t => {
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const builder = new MLGraphBuilder(context);
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const input = builder.input('input', test.input);
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if (test.output) {
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const output = builder.pad(
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input, test.beginningPadding, test.endingPadding, test.options);
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assert_equals(output.dataType, test.output.dataType);
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assert_array_equals(output.shape, test.output.shape);
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} else {
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assert_throws_with_label(
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() => builder.pad(
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input, test.beginningPadding, test.endingPadding, test.options),
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regrexp);
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}
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}, test.name));
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