120 lines
4 KiB
JavaScript
120 lines
4 KiB
JavaScript
// META: title=validation tests for WebNN API gather 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 = 'gather_'
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const regrexp = new RegExp('\\[' + label + '\\]');
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const tests = [
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{
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name: '[gather] Test gather with default options and 0-D indices',
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input: {dataType: 'int32', shape: [3]},
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indices: {dataType: 'int64', shape: []},
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output: {dataType: 'int32', shape: []}
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},
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{
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name: '[gather] Test gather with axis = 2',
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input: {dataType: 'float32', shape: [1, 2, 3, 4]},
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indices: {dataType: 'int64', shape: [5, 6]},
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axis: 2,
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output: {dataType: 'float32', shape: [1, 2, 5, 6, 4]}
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},
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{
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name: '[gather] Test gather with indices\'s dataType = uint32',
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input: {dataType: 'float32', shape: [1, 2, 3, 4]},
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indices: {dataType: 'uint32', shape: [5, 6]},
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axis: 2,
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output: {dataType: 'float32', shape: [1, 2, 5, 6, 4]}
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},
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{
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name: '[gather] Test gather with indices\'s dataType = int32',
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input: {dataType: 'float32', shape: [1, 2, 3, 4]},
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indices: {dataType: 'int32', shape: [5, 6]},
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axis: 2,
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output: {dataType: 'float32', shape: [1, 2, 5, 6, 4]}
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},
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{
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name: '[gather] TypeError is expected if the input is a scalar',
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input: {dataType: 'float16', shape: []},
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indices: {dataType: 'int64', shape: [1]},
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},
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{
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name:
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'[gather] TypeError is expected if the axis is greater than the rank of input',
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input: {dataType: 'float16', shape: [1, 2, 3]},
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indices: {dataType: 'int32', shape: [5, 6]},
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axis: 4,
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},
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{
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name:
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'[gather] TypeError is expected if the data type of indices is float32 which is invalid',
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input: {dataType: 'float16', shape: [1, 2, 3, 4]},
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indices: {dataType: 'float32', shape: [5, 6]},
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},
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{
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name:
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'[gather] TypeError is expected if the data type of indices is uint64 which is invalid',
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input: {dataType: 'float16', shape: [1, 2, 3, 4]},
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indices: {dataType: 'uint64', shape: [5, 6]},
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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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const indices = builder.input('indices', test.indices);
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const options = {};
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if (test.axis) {
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options.axis = test.axis;
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}
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if (test.output) {
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const output = builder.gather(input, indices, 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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options.label = label;
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assert_throws_with_label(
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() => builder.gather(input, indices, options), regrexp);
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}
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}, test.name));
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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 indices = builder.input('indices', {dataType: 'int64', shape: [2, 2]});
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assert_throws_js(
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TypeError, () => builder.gather(inputFromOtherBuilder, indices));
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}, '[gather] throw if input is from another builder');
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multi_builder_test(async (t, builder, otherBuilder) => {
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const indicesFromOtherBuilder =
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otherBuilder.input('indices', {dataType: 'int64', shape: [2, 2]});
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const input = builder.input('input', {dataType: 'float32', shape: [2, 2]});
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assert_throws_js(
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TypeError, () => builder.gather(input, indicesFromOtherBuilder));
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}, '[gather] throw if indices 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', shape: [1, 3, 3, 4]});
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const indices = builder.input('indices', {
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dataType: 'int32',
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shape: [context.opSupportLimits().maxTensorByteLength / 4] });
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const options = {};
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options.label = label;
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options.axis = 2;
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assert_throws_with_label(
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() => builder.gather(input, indices, options), regrexp);
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}, '[gather] throw if the output tensor byte length exceeds limit');
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