/**

* @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, PreluInputs} from '../kernel_names';

import {Tensor} from '../tensor';

import {NamedTensorMap} from '../tensor_types';

import {convertToTensor} from '../tensor_util_env';

import {TensorLike} from '../types';

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_<T extends Tensor>(x: T|TensorLike, alpha: T|TensorLike): T {

}

export const prelu = /* @__PURE__ */ op({prelu_});