/**

* @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 {customGrad} from '../gradients';

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

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

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

import {mul} from './mul';

import {neg} from './neg';

import {op} from './operation';

import {sigmoid} from './sigmoid';

import {softplus} from './softplus';

/**

* Computes log sigmoid of the input `tf.Tensor` element-wise:

* `logSigmoid(x)`. For numerical stability, we use `-tf.softplus(-x)`.

*

* ```js

* const x = tf.tensor1d([0, 1, -1, .7]);

*

* x.logSigmoid().print(); // or tf.logSigmoid(x)

* ```

* @param x The input tensor.

*

* @doc {heading: 'Operations', subheading: 'Basic math'}

*/

function logSigmoid_<T extends Tensor>(x: T|TensorLike): T {

}

export const logSigmoid = /* @__PURE__ */ op({logSigmoid_});