/**

* @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 {Tensor} from '../tensor';

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

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

import {parseAxisParam} from '../util';

import {add} from './add';

import {expandShapeToKeepDim} from './axis_util';

import {exp} from './exp';

import {log} from './log';

import {max} from './max';

import {op} from './operation';

import {reshape} from './reshape';

import {sub} from './sub';

import {sum} from './sum';

/**

* Computes the log(sum(exp(elements across the reduction dimensions))).

*

* Reduces the input along the dimensions given in `axis`. Unless `keepDims`

* is true, the rank of the array is reduced by 1 for each entry in `axis`.

* If `keepDims` is true, the reduced dimensions are retained with length 1.

* If `axis` has no entries, all dimensions are reduced, and an array with a

* single element is returned.

*

* ```js

* const x = tf.tensor1d([1, 2, 3]);

*

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

* ```

*

* ```js

* const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);

*

* const axis = 1;

* x.logSumExp(axis).print(); // or tf.logSumExp(a, axis)

* ```

* @param x The input tensor.

* @param axis The dimension(s) to reduce. If null (the default),

* reduces all dimensions.

* @param keepDims If true, retains reduced dimensions with length

* of 1. Defaults to false.

*

* @doc {heading: 'Operations', subheading: 'Reduction'}

*/

function logSumExp_<T extends Tensor>(

}

export const logSumExp = /* @__PURE__ */ op({logSumExp_});