/** * @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 { Tensor3D, Tensor4D } from '../tensor'; import { TensorLike } from '../types'; import * as conv_util from './conv_util'; /** * Computes the 2D max pooling of an image. * * @param x The input tensor, of rank 4 or rank 3 of shape * `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed. * @param filterSize The filter size: `[filterHeight, filterWidth]`. If * `filterSize` is a single number, then `filterHeight == filterWidth`. * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If * `strides` is a single number, then `strideHeight == strideWidth`. * @param dilations The dilation rates: `[dilationHeight, dilationWidth]` * in which we sample input values across the height and width dimensions * in dilated pooling. Defaults to `[1, 1]`. If `dilations` is a single * number, then `dilationHeight == dilationWidth`. If it is greater than * 1, then all values of `strides` must be 1. * @param pad The type of padding algorithm. * - `same` and stride 1: output will be of same size as input, * regardless of filter size. * - `valid`: output will be smaller than input if filter is larger * than 1x1. * - For more info, see this guide: * [https://www.tensorflow.org/api_docs/python/tf/nn/convolution]( * https://www.tensorflow.org/api_docs/python/tf/nn/convolution) * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. If none is * provided, it will default to truncate. */ declare function maxPool_(x: T | TensorLike, filterSize: [number, number] | number, strides: [number, number] | number, pad: 'valid' | 'same' | number | conv_util.ExplicitPadding, dimRoundingMode?: 'floor' | 'round' | 'ceil'): T; export declare const maxPool: typeof maxPool_; export {};