UNPKG

@tensorflow/tfjs-core

Version:

Hardware-accelerated JavaScript library for machine intelligence

79 lines 3.81 kB
/** * @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 { ENGINE } from '../engine'; import { Dilation2D } from '../kernel_names'; import { convertToTensor } from '../tensor_util_env'; import * as util from '../util'; import { op } from './operation'; import { reshape } from './reshape'; /** * Computes the grayscale dilation over the input `x`. * * @param x The input tensor, rank 3 or rank 4 of shape * `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed. * @param filter The filter tensor, rank 3, of shape * `[filterHeight, filterWidth, depth]`. * @param strides The strides of the sliding window for each dimension of the * input tensor: `[strideHeight, strideWidth]`. * If `strides` is a single number, * then `strideHeight == strideWidth`. * @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 1*1x1. * - For more info, see this guide: * [https://www.tensorflow.org/api_guides/python/nn#Convolution]( * https://www.tensorflow.org/api_guides/python/nn#Convolution) * @param dataFormat Specify the data format of the input and output data. * Defaults to 'NHWC'. Only 'NHWC' is currently supported. With the * default format "NHWC", the data is stored in the order of: [batch, * height, width, channels]. * @param dilations The dilation rates: `[dilationHeight, dilationWidth]` * in which we sample input values across the height and width dimensions * for atrous morphological dilation. 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. * * @doc {heading: 'Operations', subheading: 'Convolution'} */ function dilation2d_(x, filter, strides, pad, dilations = [1, 1], dataFormat = 'NHWC') { const $x = convertToTensor(x, 'x', 'dilation2d'); const $filter = convertToTensor(filter, 'filter', 'dilation2d'); util.assert($x.rank === 3 || $x.rank === 4, () => `Error in dilation2d: input must be rank 3 or 4, but got rank ` + `${$x.rank}.`); util.assert($filter.rank === 3, () => `Error in dilation2d: filter must be rank 3, but got rank ` + `${$filter.rank}.`); util.assert(dataFormat === 'NHWC', () => `Error in dilation2d: Only NHWC is currently supported, ` + `but got dataFormat of ${dataFormat}`); let x4D = $x; let reshapedTo4D = false; if ($x.rank === 3) { x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]); reshapedTo4D = true; } const inputs = { x: x4D, filter: $filter }; const attrs = { strides, pad, dilations }; // tslint:disable-next-line: no-unnecessary-type-assertion const res = ENGINE.runKernel(Dilation2D, inputs, attrs); if (reshapedTo4D) { return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]); } return res; } export const dilation2d = op({ dilation2d_ }); //# sourceMappingURL=dilation2d.js.map