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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @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 { buffer } from './buffer'; import { op } from './operation'; import { UniformRandom } from './rand_util'; /** * Creates a `tf.Tensor` with values sampled from a uniform distribution. * * The generated values follow a uniform distribution in the range [minval, * maxval). The lower bound minval is included in the range, while the upper * bound maxval is excluded. * * ```js * tf.randomUniform([2, 2]).print(); * ``` * * @param shape An array of integers defining the output tensor shape. * @param minval The lower bound on the range of random values to generate. * Defaults to 0. * @param maxval The upper bound on the range of random values to generate. * Defaults to 1. * @param dtype The data type of the output tensor. Defaults to 'float32'. * * @doc {heading: 'Tensors', subheading: 'Random'} */ function randomUniform_(shape, minval = 0, maxval = 1, dtype = 'float32', seed) { const res = buffer(shape, dtype); const random = new UniformRandom(minval, maxval, null, seed); for (let i = 0; i < res.values.length; i++) { res.values[i] = random.nextValue(); } return res.toTensor(); } export const randomUniform = op({ randomUniform_ }); //# sourceMappingURL=random_uniform.js.map