@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 { expectArrayInMeanStdRange, jarqueBeraNormalityTest } from './rand_util';
describeWithFlags('randomNormal', ALL_ENVS, () => {
const SEED = 2002;
const EPSILON = 0.05;
it('should return a float32 1D of random normal values', async () => {
const SAMPLES = 10000;
// Ensure defaults to float32.
let result = tf.randomNormal([SAMPLES], 0, 0.5, null, SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual([SAMPLES]);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 0.5, EPSILON);
result = tf.randomNormal([SAMPLES], 0, 1.5, 'float32', SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual([SAMPLES]);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 1.5, EPSILON);
});
it('should return a int32 1D of random normal values', async () => {
const SAMPLES = 10000;
const result = tf.randomNormal([SAMPLES], 0, 2, 'int32', SEED);
expect(result.dtype).toBe('int32');
expect(result.shape).toEqual([SAMPLES]);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 2, EPSILON);
});
it('should return a float32 2D of random normal values', async () => {
const SAMPLES = 100;
// Ensure defaults to float32.
let result = tf.randomNormal([SAMPLES, SAMPLES], 0, 2.5, null, SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual([SAMPLES, SAMPLES]);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 2.5, EPSILON);
result = tf.randomNormal([SAMPLES, SAMPLES], 0, 3.5, 'float32', SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual([SAMPLES, SAMPLES]);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 3.5, EPSILON);
});
it('should return a int32 2D of random normal values', async () => {
const SAMPLES = 100;
const result = tf.randomNormal([SAMPLES, SAMPLES], 0, 2, 'int32', SEED);
expect(result.dtype).toBe('int32');
expect(result.shape).toEqual([SAMPLES, SAMPLES]);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 2, EPSILON);
});
it('should return a float32 3D of random normal values', async () => {
const SAMPLES_SHAPE = [20, 20, 20];
// Ensure defaults to float32.
let result = tf.randomNormal(SAMPLES_SHAPE, 0, 0.5, null, SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual(SAMPLES_SHAPE);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 0.5, EPSILON);
result = tf.randomNormal(SAMPLES_SHAPE, 0, 1.5, 'float32', SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual(SAMPLES_SHAPE);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 1.5, EPSILON);
});
it('should return a int32 3D of random normal values', async () => {
const SAMPLES_SHAPE = [20, 20, 20];
const result = tf.randomNormal(SAMPLES_SHAPE, 0, 2, 'int32', SEED);
expect(result.dtype).toBe('int32');
expect(result.shape).toEqual(SAMPLES_SHAPE);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 2, EPSILON);
});
it('should return a float32 4D of random normal values', async () => {
const SAMPLES_SHAPE = [10, 10, 10, 10];
// Ensure defaults to float32.
let result = tf.randomNormal(SAMPLES_SHAPE, 0, 0.5, null, SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual(SAMPLES_SHAPE);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 0.5, EPSILON);
result = tf.randomNormal(SAMPLES_SHAPE, 0, 1.5, 'float32', SEED);
expect(result.dtype).toBe('float32');
expect(result.shape).toEqual(SAMPLES_SHAPE);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 1.5, EPSILON);
});
it('should return a int32 4D of random normal values', async () => {
const SAMPLES_SHAPE = [10, 10, 10, 10];
const result = tf.randomNormal(SAMPLES_SHAPE, 0, 2, 'int32', SEED);
expect(result.dtype).toBe('int32');
expect(result.shape).toEqual(SAMPLES_SHAPE);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 2, EPSILON);
});
it('should return a int32 5D of random normal values', async () => {
const SAMPLES_SHAPE = [10, 10, 10, 10, 10];
const result = tf.randomNormal(SAMPLES_SHAPE, 0, 2, 'int32', SEED);
expect(result.dtype).toBe('int32');
expect(result.shape).toEqual(SAMPLES_SHAPE);
jarqueBeraNormalityTest(await result.data());
expectArrayInMeanStdRange(await result.data(), 0, 2, EPSILON);
});
});
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