@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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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 { convertToTensor } from '../tensor_util_env';
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_(x, axis = null, keepDims = false) {
const $x = convertToTensor(x, 'x', 'logSumExp');
const axes = parseAxisParam(axis, $x.shape);
const xMax = max($x, axes, true /* keepDims */);
const a = sub($x, xMax);
const b = exp(a);
const c = sum(b, axes);
const d = log(c);
const res = add(reshape(xMax, d.shape), d);
if (keepDims) {
const newShape = expandShapeToKeepDim(res.shape, axes);
return reshape(res, newShape);
}
return res;
}
export const logSumExp = op({ logSumExp_ });
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