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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @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. * ============================================================================= */ /// <amd-module name="@tensorflow/tfjs-core/dist/ops/softmax" /> import { Tensor } from '../tensor'; import { TensorLike } from '../types'; /** * Computes the softmax normalized vector given the logits. * * ```js * const a = tf.tensor1d([1, 2, 3]); * * a.softmax().print(); // or tf.softmax(a) * ``` * * ```js * const a = tf.tensor2d([2, 4, 6, 1, 2, 3], [2, 3]); * * a.softmax().print(); // or tf.softmax(a) * ``` * * @param logits The logits array. * @param dim The dimension softmax would be performed on. Defaults to `-1` * which indicates the last dimension. * * @doc {heading: 'Operations', subheading: 'Normalization'} */ declare function softmax_<T extends Tensor>(logits: T | TensorLike, dim?: number): T; export declare const softmax: typeof softmax_; export {};