| // META: title=validation tests for WebNN API scatterND operation |
| // META: global=window |
| // META: variant=?cpu |
| // META: variant=?gpu |
| // META: variant=?npu |
| // META: script=../resources/utils_validation.js |
| |
| 'use strict'; |
| |
| const tests = [ |
| { |
| name: '[scatterND] Test scatterND with valid tensors', |
| input: {dataType: 'float32', shape: [4, 4, 4]}, |
| indices: {dataType: 'int32', shape: [2, 1]}, |
| updates: {dataType: 'float32', shape: [2, 4, 4]}, |
| output: {dataType: 'float32', shape: [4, 4, 4]} |
| }, |
| { |
| name: |
| '[scatterND] Throw if updates tensor data type is not the same as input data type', |
| input: {dataType: 'float32', shape: [4, 4, 4]}, |
| indices: {dataType: 'int32', shape: [2, 1]}, |
| updates: {dataType: 'float16', shape: [2, 4, 4]}, |
| }, |
| { |
| name: '[scatterND] Throw if input is a scalar', |
| input: {dataType: 'float32', shape: []}, |
| indices: {dataType: 'int32', shape: [2, 1]}, |
| updates: {dataType: 'float32', shape: [2, 4, 4]}, |
| }, |
| { |
| name: '[scatterND] Throw if indices is a scalar', |
| input: {dataType: 'float32', shape: [4, 4, 4]}, |
| indices: {dataType: 'int32', shape: []}, |
| updates: {dataType: 'float32', shape: [2, 4, 4]}, |
| }, |
| { |
| name: |
| '[scatterND] Throw if the size of last dimension of indices tensor is greater than input rank', |
| input: {dataType: 'float32', shape: [4, 4, 4]}, |
| indices: {dataType: 'int32', shape: [2, 4]}, |
| updates: {dataType: 'float32', shape: [2, 4, 4]}, |
| }, |
| { |
| name: '[scatterND] Throw if updates tensor shape is invalid.', |
| input: {dataType: 'float32', shape: [4, 4, 4]}, |
| indices: {dataType: 'int32', shape: [2, 1]}, |
| // Updates tensor shape should be [2, 4, 4]. |
| updates: {dataType: 'float32', shape: [2, 3, 4]}, |
| } |
| ]; |
| |
| tests.forEach(test => promise_test(async t => { |
| const builder = new MLGraphBuilder(context); |
| const input = builder.input('input', test.input); |
| const indices = builder.input('indices', test.indices); |
| const updates = builder.input('updates', test.updates); |
| |
| if (test.output) { |
| const output = builder.scatterND(input, indices, updates); |
| assert_equals(output.dataType, test.output.dataType); |
| assert_array_equals(output.shape, test.output.shape); |
| } else { |
| const label = 'a_scatter_nd' |
| const options = {label}; |
| const regexp = new RegExp('\\[' + label + '\\]'); |
| assert_throws_with_label( |
| () => builder.scatterND(input, indices, updates, options), |
| regexp); |
| } |
| }, test.name)); |
| |
| multi_builder_test(async (t, builder, otherBuilder) => { |
| const input = otherBuilder.input('input', {dataType: 'float32', shape: [8]}); |
| const indices = builder.input('indices', {dataType: 'int32', shape: [4, 1]}); |
| const updates = builder.input('indices', {dataType: 'int32', shape: [4]}); |
| |
| assert_throws_js(TypeError, () => builder.scatterND(input, indices, updates)); |
| }, '[scatterND] Throw if input is from another builder'); |
| |
| multi_builder_test(async (t, builder, otherBuilder) => { |
| const input = builder.input('input', {dataType: 'float32', shape: [8]}); |
| const indices = |
| otherBuilder.input('indices', {dataType: 'int32', shape: [4, 1]}); |
| const updates = builder.input('indices', {dataType: 'int32', shape: [4]}); |
| |
| assert_throws_js(TypeError, () => builder.scatterND(input, indices, updates)); |
| }, '[scatterND] Throw if indcies is from another builder'); |
| |
| multi_builder_test(async (t, builder, otherBuilder) => { |
| const input = builder.input('input', {dataType: 'float32', shape: [8]}); |
| const indices = builder.input('indices', {dataType: 'int32', shape: [4, 1]}); |
| const updates = |
| otherBuilder.input('indices', {dataType: 'int32', shape: [4]}); |
| |
| assert_throws_js(TypeError, () => builder.scatterND(input, indices, updates)); |
| }, '[scatterND] Throw if updates is from another builder'); |