@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @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_ });
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