@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
44 lines • 1.58 kB
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 { ENGINE } from '../engine';
import { Prelu } from '../kernel_names';
import { convertToTensor } from '../tensor_util_env';
import { op } from './operation';
/**
* Computes leaky rectified linear element-wise with parametric alphas.
*
* `x < 0 ? alpha * x : f(x) = x`
*
* ```js
* const x = tf.tensor1d([-1, 2, -3, 4]);
* const alpha = tf.scalar(0.1);
*
* x.prelu(alpha).print(); // or tf.prelu(x, alpha)
* ```
* @param x The input tensor.
* @param alpha Scaling factor for negative values.
*
* @doc {heading: 'Operations', subheading: 'Basic math'}
*/
function prelu_(x, alpha) {
const $x = convertToTensor(x, 'x', 'prelu');
const $alpha = convertToTensor(alpha, 'alpha', 'prelu');
const inputs = { x: $x, alpha: $alpha };
return ENGINE.runKernel(Prelu, inputs);
}
export const prelu = op({ prelu_ });
//# sourceMappingURL=prelu.js.map