@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @license
* Copyright 2020 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('expandDims', ALL_ENVS, () => {
it('scalar, default axis is 0', async () => {
const res = tf.scalar(1).expandDims();
expect(res.shape).toEqual([1]);
expectArraysClose(await res.data(), [1]);
});
it('scalar, axis is out of bounds throws error', () => {
const f = () => tf.scalar(1).expandDims(1);
expect(f).toThrowError();
});
it('1d, axis=-3', () => {
expect(() => {
tf.tensor1d([1, 2, 3]).expandDims(-3);
}).toThrowError();
});
it('1d, axis=-2', async () => {
const res = tf.tensor1d([1, 2, 3]).expandDims(-2 /* axis */);
expect(res.shape).toEqual([1, 3]);
expectArraysClose(await res.data(), [1, 2, 3]);
});
it('1d, axis=-1', async () => {
const res = tf.tensor1d([1, 2, 3]).expandDims(-1 /* axis */);
expect(res.shape).toEqual([3, 1]);
expectArraysClose(await res.data(), [1, 2, 3]);
});
it('1d, axis=0', async () => {
const res = tf.tensor1d([1, 2, 3]).expandDims(0 /* axis */);
expect(res.shape).toEqual([1, 3]);
expectArraysClose(await res.data(), [1, 2, 3]);
});
it('1d, axis=1', async () => {
const res = tf.tensor1d([1, 2, 3]).expandDims(1 /* axis */);
expect(res.shape).toEqual([3, 1]);
expectArraysClose(await res.data(), [1, 2, 3]);
});
it('2d, axis=-4', () => {
expect(() => {
tf.tensor2d([[1, 2], [3, 4], [5, 6]]).expandDims(-4 /* axis */);
}).toThrowError();
});
it('2d, axis=-3', async () => {
const res = tf.tensor2d([[1, 2], [3, 4], [5, 6]]).expandDims(-3 /* axis */);
expect(res.shape).toEqual([1, 3, 2]);
expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6]);
});
it('2d, axis=-2', async () => {
const res = tf.tensor2d([[1, 2], [3, 4], [5, 6]]).expandDims(-2 /* axis */);
expect(res.shape).toEqual([3, 1, 2]);
expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6]);
});
it('2d, axis=-1', async () => {
const res = tf.tensor2d([[1, 2], [3, 4], [5, 6]]).expandDims(-1 /* axis */);
expect(res.shape).toEqual([3, 2, 1]);
expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6]);
});
it('2d, axis=0', async () => {
const res = tf.tensor2d([[1, 2], [3, 4], [5, 6]]).expandDims(0 /* axis */);
expect(res.shape).toEqual([1, 3, 2]);
expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6]);
});
it('2d, axis=1', async () => {
const res = tf.tensor2d([[1, 2], [3, 4], [5, 6]]).expandDims(1 /* axis */);
expect(res.shape).toEqual([3, 1, 2]);
expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6]);
});
it('2d, axis=2', async () => {
const res = tf.tensor2d([[1, 2], [3, 4], [5, 6]]).expandDims(2 /* axis */);
expect(res.shape).toEqual([3, 2, 1]);
expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6]);
});
it('4d, axis=0', async () => {
const res = tf.tensor4d([[[[4]]]]).expandDims();
expect(res.shape).toEqual([1, 1, 1, 1, 1]);
expectArraysClose(await res.data(), [4]);
});
it('1d string tensor', async () => {
const t = tf.tensor(['hello', 'world']);
const res = t.expandDims();
expect(res.shape).toEqual([1, 2]);
expectArraysClose(await res.data(), ['hello', 'world']);
});
it('2d string tensor, axis=1', async () => {
const t = tf.tensor([['a', 'b'], ['c', 'd']]);
const res = t.expandDims(1);
expect(res.shape).toEqual([2, 1, 2]);
expectArraysClose(await res.data(), ['a', 'b', 'c', 'd']);
});
it('throws when passed a non-tensor', () => {
expect(() => tf.expandDims({}))
.toThrowError(/Argument 'x' passed to 'expandDims' must be a Tensor/);
});
it('accepts a tensor-like object', async () => {
const res = tf.expandDims(7);
expect(res.shape).toEqual([1]);
expectArraysClose(await res.data(), [7]);
});
it('works with 0 in shape', async () => {
const a = tf.tensor2d([], [0, 3]);
const res = a.expandDims();
expect(res.shape).toEqual([1, 0, 3]);
expectArraysClose(await res.data(), []);
const res2 = a.expandDims(1);
expect(res2.shape).toEqual([0, 1, 3]);
expectArraysClose(await res2.data(), []);
const res3 = a.expandDims(2);
expect(res3.shape).toEqual([0, 3, 1]);
expectArraysClose(await res3.data(), []);
});
it('ensure no memory leak', async () => {
const numTensorsBefore = tf.memory().numTensors;
const numDataIdBefore = tf.engine().backend.numDataIds();
const t = tf.scalar(1);
const res = t.expandDims();
expect(res.shape).toEqual([1]);
expectArraysClose(await res.data(), [1]);
res.dispose();
t.dispose();
const numTensorsAfter = tf.memory().numTensors;
const numDataIdAfter = tf.engine().backend.numDataIds();
expect(numTensorsAfter).toBe(numTensorsBefore);
expect(numDataIdAfter).toBe(numDataIdBefore);
});
});
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