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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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"use strict"; /** * @license * Copyright 2020 Google Inc. 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. * ============================================================================= */ Object.defineProperty(exports, "__esModule", { value: true }); var engine_1 = require("../engine"); var util_1 = require("../util"); var operation_1 = require("./operation"); /** * Creates a `tf.Tensor` with values sampled from a random number generator * function defined by the user. * * @param shape An array of integers defining the output tensor shape. * @param randFunction A random number generator function which is called * for each element in the output tensor. * @param dtype The data type of the output tensor. Defaults to 'float32'. */ function rand_(shape, randFunction, dtype) { var size = util_1.sizeFromShape(shape); var values = null; if (dtype == null || dtype === 'float32') { values = new Float32Array(size); } else if (dtype === 'int32') { values = new Int32Array(size); } else if (dtype === 'bool') { values = new Uint8Array(size); } else { throw new Error("Unknown data type " + dtype); } for (var i = 0; i < size; i++) { values[i] = randFunction(); } return engine_1.ENGINE.makeTensor(values, shape, dtype); } exports.rand = operation_1.op({ rand_: rand_ }); //# sourceMappingURL=rand.js.map