@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
103 lines • 4.51 kB
JavaScript
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import * as tf from '../index';
import { ALL_ENVS, describeWithFlags } from '../jasmine_util';
import { expectArraysClose } from '../test_util';
describeWithFlags('booleanMaskAsync', ALL_ENVS, () => {
it('1d array, 1d mask, default axis', async () => {
const array = tf.tensor1d([1, 2, 3]);
const mask = tf.tensor1d([1, 0, 1], 'bool');
const result = await tf.booleanMaskAsync(array, mask);
expect(result.shape).toEqual([2]);
expect(result.dtype).toBe('float32');
expectArraysClose(await result.data(), [1, 3]);
});
it('2d array, 1d mask, default axis', async () => {
const array = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
const mask = tf.tensor1d([1, 0, 1], 'bool');
const result = await tf.booleanMaskAsync(array, mask);
expect(result.shape).toEqual([2, 2]);
expect(result.dtype).toBe('float32');
expectArraysClose(await result.data(), [1, 2, 5, 6]);
});
it('2d array, 2d mask, default axis', async () => {
const array = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
const mask = tf.tensor2d([1, 0, 1, 0, 1, 0], [3, 2], 'bool');
const result = await tf.booleanMaskAsync(array, mask);
expect(result.shape).toEqual([3]);
expect(result.dtype).toBe('float32');
expectArraysClose(await result.data(), [1, 3, 5]);
});
it('2d array, 1d mask, axis=1', async () => {
const array = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
const mask = tf.tensor1d([0, 1], 'bool');
const axis = 1;
const result = await tf.booleanMaskAsync(array, mask, axis);
expect(result.shape).toEqual([3, 1]);
expect(result.dtype).toBe('float32');
expectArraysClose(await result.data(), [2, 4, 6]);
});
it('accepts tensor-like object as array or mask', async () => {
const array = [[1, 2], [3, 4], [5, 6]];
const mask = [1, 0, 1];
const result = await tf.booleanMaskAsync(array, mask);
expect(result.shape).toEqual([2, 2]);
expect(result.dtype).toBe('float32');
expectArraysClose(await result.data(), [1, 2, 5, 6]);
});
it('ensure no memory leak', async () => {
const numTensorsBefore = tf.memory().numTensors;
const array = tf.tensor1d([1, 2, 3]);
const mask = tf.tensor1d([1, 0, 1], 'bool');
const result = await tf.booleanMaskAsync(array, mask);
expect(result.shape).toEqual([2]);
expect(result.dtype).toBe('float32');
expectArraysClose(await result.data(), [1, 3]);
array.dispose();
mask.dispose();
result.dispose();
const numTensorsAfter = tf.memory().numTensors;
expect(numTensorsAfter).toBe(numTensorsBefore);
});
it('should throw if mask is scalar', async () => {
const array = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
const mask = tf.scalar(1, 'bool');
let errorMessage = 'No error thrown.';
try {
await tf.booleanMaskAsync(array, mask);
}
catch (error) {
errorMessage = error.message;
}
expect(errorMessage).toBe('mask cannot be scalar');
});
it('should throw if array and mask shape miss match', async () => {
const array = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
const mask = tf.tensor2d([1, 0], [1, 2], 'bool');
let errorMessage = 'No error thrown.';
try {
await tf.booleanMaskAsync(array, mask);
}
catch (error) {
errorMessage = error.message;
}
expect(errorMessage)
.toBe(`mask's shape must match the first K ` +
`dimensions of tensor's shape, Shapes 3,2 and 1,2 must match`);
});
});
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