@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @license
* Copyright 2017 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 { Variable } from './tensor';
import { expectArraysClose } from './test_util';
describeWithFlags('variable', ALL_ENVS, () => {
it('simple assign', async () => {
const v = tf.variable(tf.tensor1d([1, 2, 3]));
expectArraysClose(await v.data(), [1, 2, 3]);
v.assign(tf.tensor1d([4, 5, 6]));
expectArraysClose(await v.data(), [4, 5, 6]);
});
it('simple chain assign', async () => {
const v = tf.tensor1d([1, 2, 3]).variable();
expectArraysClose(await v.data(), [1, 2, 3]);
v.assign(tf.tensor1d([4, 5, 6]));
expectArraysClose(await v.data(), [4, 5, 6]);
});
it('default names are unique', () => {
const v = tf.variable(tf.tensor1d([1, 2, 3]));
expect(v.name).not.toBeNull();
const v2 = tf.variable(tf.tensor1d([1, 2, 3]));
expect(v2.name).not.toBeNull();
expect(v.name).not.toBe(v2.name);
});
it('user provided name', () => {
const v = tf.variable(tf.tensor1d([1, 2, 3]), true, 'myName');
expect(v.name).toBe('myName');
});
it('if name already used, throw error', () => {
tf.variable(tf.tensor1d([1, 2, 3]), true, 'myName');
expect(() => tf.variable(tf.tensor1d([1, 2, 3]), true, 'myName'))
.toThrowError();
});
it('ops can take variables', async () => {
const value = tf.tensor1d([1, 2, 3]);
const v = tf.variable(value);
const res = tf.sum(v);
expectArraysClose(await res.data(), [6]);
});
it('chained variables works', async () => {
const v = tf.tensor1d([1, 2, 3]).variable();
const res = tf.sum(v);
expectArraysClose(await res.data(), [6]);
});
it('variables are not affected by tidy', async () => {
let v;
expect(tf.memory().numTensors).toBe(0);
tf.tidy(() => {
const value = tf.tensor1d([1, 2, 3], 'float32');
expect(tf.memory().numTensors).toBe(1);
v = tf.variable(value);
expect(tf.memory().numTensors).toBe(2);
});
expect(tf.memory().numTensors).toBe(1);
expectArraysClose(await v.data(), [1, 2, 3]);
v.dispose();
expect(tf.memory().numTensors).toBe(0);
});
it('disposing a named variable allows creating new named variable', () => {
const numTensors = tf.memory().numTensors;
const t = tf.scalar(1);
const varName = 'var';
const v = tf.variable(t, true, varName);
expect(tf.memory().numTensors).toBe(numTensors + 2);
v.dispose();
t.dispose();
expect(tf.memory().numTensors).toBe(numTensors);
// Create another variable with the same name.
const t2 = tf.scalar(1);
const v2 = tf.variable(t2, true, varName);
expect(tf.memory().numTensors).toBe(numTensors + 2);
t2.dispose();
v2.dispose();
expect(tf.memory().numTensors).toBe(numTensors);
});
it('double disposing a variable works', () => {
const numTensors = tf.memory().numTensors;
const t = tf.scalar(1);
const v = tf.variable(t);
expect(tf.memory().numTensors).toBe(numTensors + 2);
t.dispose();
v.dispose();
expect(tf.memory().numTensors).toBe(numTensors);
// Double dispose the variable.
v.dispose();
expect(tf.memory().numTensors).toBe(numTensors);
});
it('constructor does not dispose', async () => {
const a = tf.scalar(2);
const v = tf.variable(a);
expect(tf.memory().numTensors).toBe(2);
expect(tf.memory().numDataBuffers).toBe(1);
expectArraysClose(await v.data(), [2]);
expectArraysClose(await a.data(), [2]);
});
it('variables are assignable to tensors', () => {
// This test asserts compilation, not doing any run-time assertion.
const x0 = null;
const y0 = x0;
expect(y0).toBeNull();
const x1 = null;
const y1 = x1;
expect(y1).toBeNull();
const x2 = null;
const y2 = x2;
expect(y2).toBeNull();
const x3 = null;
const y3 = x3;
expect(y3).toBeNull();
const x4 = null;
const y4 = x4;
expect(y4).toBeNull();
const xh = null;
const yh = xh;
expect(yh).toBeNull();
});
it('assign does not dispose old data', async () => {
let v;
v = tf.variable(tf.tensor1d([1, 2, 3]));
expect(tf.memory().numTensors).toBe(2);
expect(tf.memory().numDataBuffers).toBe(1);
expectArraysClose(await v.data(), [1, 2, 3]);
const secondArray = tf.tensor1d([4, 5, 6]);
expect(tf.memory().numTensors).toBe(3);
expect(tf.memory().numDataBuffers).toBe(2);
v.assign(secondArray);
expectArraysClose(await v.data(), [4, 5, 6]);
// Assign doesn't dispose the 1st array.
expect(tf.memory().numTensors).toBe(3);
expect(tf.memory().numDataBuffers).toBe(2);
v.dispose();
// Disposing the variable disposes itself. The input to variable and
// secondArray are the only remaining tensors.
expect(tf.memory().numTensors).toBe(2);
expect(tf.memory().numDataBuffers).toBe(2);
});
it('shape must match', () => {
const v = tf.variable(tf.tensor1d([1, 2, 3]));
expect(() => v.assign(tf.tensor1d([1, 2]))).toThrowError();
// tslint:disable-next-line:no-any
expect(() => v.assign(tf.tensor2d([3, 4], [1, 2]))).toThrowError();
});
it('dtype must match', () => {
const v = tf.variable(tf.tensor1d([1, 2, 3]));
// tslint:disable-next-line:no-any
expect(() => v.assign(tf.tensor1d([1, 1, 1], 'int32')))
.toThrowError();
// tslint:disable-next-line:no-any
expect(() => v.assign(tf.tensor1d([true, false, true], 'bool')))
.toThrowError();
});
});
describeWithFlags('x instanceof Variable', ALL_ENVS, () => {
it('x: Variable', () => {
const t = tf.variable(tf.scalar(1));
expect(t instanceof Variable).toBe(true);
});
it('x: other object, fails', () => {
const t = { something: 'else' };
expect(t instanceof Variable).toBe(false);
});
it('x: Tensor, fails', () => {
const t = tf.scalar(1);
expect(t instanceof Variable).toBe(false);
});
});
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