@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 { util } from '..';
import * as tf from '../index';
import { ALL_ENVS, describeWithFlags } from '../jasmine_util';
import { expectValuesInRange } from '../test_util';
import { MPRandGauss, RandGamma, UniformRandom } from './rand_util';
import { expectArrayInMeanStdRange, jarqueBeraNormalityTest } from './rand_util';
describeWithFlags('rand', ALL_ENVS, () => {
it('should return a random 1D float32 array', async () => {
const shape = [10];
// Enusre defaults to float32 w/o type:
let result = tf.rand(shape, () => util.randUniform(0, 2));
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 2);
result = tf.rand(shape, () => util.randUniform(0, 1.5));
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 1.5);
});
it('should return a random 1D int32 array', async () => {
const shape = [10];
const result = tf.rand(shape, () => util.randUniform(0, 2), 'int32');
expect(result.dtype).toBe('int32');
expectValuesInRange(await result.data(), 0, 2);
});
it('should return a random 1D bool array', async () => {
const shape = [10];
const result = tf.rand(shape, () => util.randUniform(0, 1), 'bool');
expect(result.dtype).toBe('bool');
expectValuesInRange(await result.data(), 0, 1);
});
it('should return a random 2D float32 array', async () => {
const shape = [3, 4];
// Enusre defaults to float32 w/o type:
let result = tf.rand(shape, () => util.randUniform(0, 2.5));
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 2.5);
result = tf.rand(shape, () => util.randUniform(0, 1.5), 'float32');
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 1.5);
});
it('should return a random 2D int32 array', async () => {
const shape = [3, 4];
const result = tf.rand(shape, () => util.randUniform(0, 2), 'int32');
expect(result.dtype).toBe('int32');
expectValuesInRange(await result.data(), 0, 2);
});
it('should return a random 2D bool array', async () => {
const shape = [3, 4];
const result = tf.rand(shape, () => util.randUniform(0, 1), 'bool');
expect(result.dtype).toBe('bool');
expectValuesInRange(await result.data(), 0, 1);
});
it('should return a random 3D float32 array', async () => {
const shape = [3, 4, 5];
// Enusre defaults to float32 w/o type:
let result = tf.rand(shape, () => util.randUniform(0, 2.5));
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 2.5);
result = tf.rand(shape, () => util.randUniform(0, 1.5), 'float32');
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 1.5);
});
it('should return a random 3D int32 array', async () => {
const shape = [3, 4, 5];
const result = tf.rand(shape, () => util.randUniform(0, 2), 'int32');
expect(result.dtype).toBe('int32');
expectValuesInRange(await result.data(), 0, 2);
});
it('should return a random 3D bool array', async () => {
const shape = [3, 4, 5];
const result = tf.rand(shape, () => util.randUniform(0, 1), 'bool');
expect(result.dtype).toBe('bool');
expectValuesInRange(await result.data(), 0, 1);
});
it('should return a random 4D float32 array', async () => {
const shape = [3, 4, 5, 6];
// Enusre defaults to float32 w/o type:
let result = tf.rand(shape, () => util.randUniform(0, 2.5));
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 2.5);
result = tf.rand(shape, () => util.randUniform(0, 1.5));
expect(result.dtype).toBe('float32');
expectValuesInRange(await result.data(), 0, 1.5);
});
it('should return a random 4D int32 array', async () => {
const shape = [3, 4, 5, 6];
const result = tf.rand(shape, () => util.randUniform(0, 2), 'int32');
expect(result.dtype).toBe('int32');
expectValuesInRange(await result.data(), 0, 2);
});
it('should return a random 4D bool array', async () => {
const shape = [3, 4, 5, 6];
const result = tf.rand(shape, () => util.randUniform(0, 1), 'bool');
expect(result.dtype).toBe('bool');
expectValuesInRange(await result.data(), 0, 1);
});
});
function isFloat(n) {
return Number(n) === n && n % 1 !== 0;
}
describe('MPRandGauss', () => {
const EPSILON = 0.05;
const SEED = 2002;
it('should default to float32 numbers', () => {
const rand = new MPRandGauss(0, 1.5);
expect(isFloat(rand.nextValue())).toBe(true);
});
it('should handle a mean/stdv of float32 numbers', () => {
const rand = new MPRandGauss(0, 1.5, 'float32', false /* truncated */, SEED);
const values = [];
const size = 10000;
for (let i = 0; i < size; i++) {
values.push(rand.nextValue());
}
expectArrayInMeanStdRange(values, 0, 1.5, EPSILON);
jarqueBeraNormalityTest(values);
});
it('should handle int32 numbers', () => {
const rand = new MPRandGauss(0, 1, 'int32');
expect(isFloat(rand.nextValue())).toBe(false);
});
it('should handle a mean/stdv of int32 numbers', () => {
const rand = new MPRandGauss(0, 2, 'int32', false /* truncated */, SEED);
const values = [];
const size = 10000;
for (let i = 0; i < size; i++) {
values.push(rand.nextValue());
}
expectArrayInMeanStdRange(values, 0, 2, EPSILON);
jarqueBeraNormalityTest(values);
});
it('Should not have a more than 2x std-d from mean for truncated values', () => {
const stdv = 1.5;
const rand = new MPRandGauss(0, stdv, 'float32', true /* truncated */);
for (let i = 0; i < 1000; i++) {
expect(Math.abs(rand.nextValue())).toBeLessThan(stdv * 2);
}
});
});
describe('RandGamma', () => {
const SEED = 2002;
it('should default to float32 numbers', () => {
const rand = new RandGamma(2, 2, 'float32');
expect(isFloat(rand.nextValue())).toBe(true);
});
it('should handle an alpha/beta of float32 numbers', () => {
const rand = new RandGamma(2, 2, 'float32', SEED);
const values = [];
const size = 10000;
for (let i = 0; i < size; i++) {
values.push(rand.nextValue());
}
expectValuesInRange(values, 0, 30);
});
it('should handle int32 numbers', () => {
const rand = new RandGamma(2, 2, 'int32');
expect(isFloat(rand.nextValue())).toBe(false);
});
it('should handle an alpha/beta of int32 numbers', () => {
const rand = new RandGamma(2, 2, 'int32', SEED);
const values = [];
const size = 10000;
for (let i = 0; i < size; i++) {
values.push(rand.nextValue());
}
expectValuesInRange(values, 0, 30);
});
});
describe('UniformRandom', () => {
it('float32, no seed', () => {
const min = 0.2;
const max = 0.24;
const dtype = 'float32';
const xs = [];
for (let i = 0; i < 10; ++i) {
const rand = new UniformRandom(min, max, dtype);
const x = rand.nextValue();
xs.push(x);
}
expect(Math.min(...xs)).toBeGreaterThanOrEqual(min);
expect(Math.max(...xs)).toBeLessThan(max);
});
it('int32, no seed', () => {
const min = 13;
const max = 37;
const dtype = 'int32';
const xs = [];
for (let i = 0; i < 10; ++i) {
const rand = new UniformRandom(min, max, dtype);
const x = rand.nextValue();
expect(Number.isInteger(x)).toEqual(true);
xs.push(x);
}
expect(Math.min(...xs)).toBeGreaterThanOrEqual(min);
expect(Math.max(...xs)).toBeLessThanOrEqual(max);
});
it('seed is number', () => {
const min = -1.2;
const max = -0.4;
const dtype = 'float32';
const seed = 1337;
const xs = [];
for (let i = 0; i < 10; ++i) {
const rand = new UniformRandom(min, max, dtype, seed);
const x = rand.nextValue();
expect(x).toBeGreaterThanOrEqual(min);
expect(x).toBeLessThan(max);
xs.push(x);
}
// Assert deterministic results.
expect(Math.min(...xs)).toEqual(Math.max(...xs));
});
it('seed === null', () => {
const min = 0;
const max = 1;
const dtype = 'float32';
const seed = null;
const rand = new UniformRandom(min, max, dtype, seed);
const x = rand.nextValue();
expect(x).toBeGreaterThanOrEqual(0);
expect(x).toBeLessThan(1);
});
it('seed === undefined', () => {
const min = 0;
const max = 1;
const dtype = 'float32';
const seed = undefined;
const rand = new UniformRandom(min, max, dtype, seed);
const x = rand.nextValue();
expect(x).toBeGreaterThanOrEqual(0);
expect(x).toBeLessThan(1);
});
});
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