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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @license * Copyright 2018 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 { ENGINE } from '../engine'; import { Erf } from '../kernel_names'; import { convertToTensor } from '../tensor_util_env'; import * as util from '../util'; import { cast } from './cast'; import { op } from './operation'; /** * Computes gause error function of the input `tf.Tensor` element-wise: * `erf(x)` * * ```js * const x = tf.tensor1d([0, .1, -.1, .7]); * * x.erf().print(); // or tf.erf(x); * ``` * @param x The input tensor. * * @doc {heading: 'Operations', subheading: 'Basic math'} */ function erf_(x) { let $x = convertToTensor(x, 'x', 'erf'); util.assert($x.dtype === 'int32' || $x.dtype === 'float32', () => 'Input dtype must be `int32` or `float32`.'); if ($x.dtype === 'int32') { $x = cast($x, 'float32'); } const inputs = { x: $x }; return ENGINE.runKernel(Erf, inputs); } export const erf = op({ erf_ }); //# sourceMappingURL=erf.js.map