/**
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* @license
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* Copyright 2018 Google LLC. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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/// <amd-module name="@tensorflow/tfjs-core/dist/ops/softmax" />
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import { Tensor } from '../tensor';
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import { TensorLike } from '../types';
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/**
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* Computes the softmax normalized vector given the logits.
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*
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* ```js
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* const a = tf.tensor1d([1, 2, 3]);
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*
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* a.softmax().print(); // or tf.softmax(a)
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* ```
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*
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* ```js
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* const a = tf.tensor2d([2, 4, 6, 1, 2, 3], [2, 3]);
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*
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* a.softmax().print(); // or tf.softmax(a)
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* ```
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*
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* @param logits The logits array.
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* @param dim The dimension softmax would be performed on. Defaults to `-1`
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* which indicates the last dimension.
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*
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* @doc {heading: 'Operations', subheading: 'Normalization'}
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*/
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declare function softmax_<T extends Tensor>(logits: T | TensorLike, dim?: number): T;
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export declare const softmax: typeof softmax_;
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export {};
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