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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @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 {Conv3D, Conv3DAttrs, Conv3DInputs} from '../kernel_names'; import {NamedAttrMap} from '../kernel_registry'; import {Tensor4D, Tensor5D} from '../tensor'; import {NamedTensorMap} from '../tensor_types'; import {convertToTensor} from '../tensor_util_env'; import {TensorLike} from '../types'; import * as util from '../util'; import {eitherStridesOrDilationsAreOne} from './conv_util'; import {op} from './operation'; import {reshape} from './reshape'; /** * Computes a 3D convolution over the input x. * * @param x The input tensor, of rank 5 or rank 4, of shape * `[batch, depth, height, width, channels]`. If rank 4, * batch of 1 is assumed. * @param filter The filter, rank 5, of shape * `[filterDepth, filterHeight, filterWidth, inChannels, outChannels]`. * inChannels must match between input and filter. * @param strides The strides of the convolution: `[strideDepth, 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 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: An optional string from: "NDHWC", "NCDHW". Defaults to * "NDHWC". Specify the data format of the input and output data. With the * default format "NDHWC", the data is stored in the order of: [batch, * depth, height, width, channels]. Only "NDHWC" is currently supported. * @param dilations The dilation rates: `[dilationDepth, dilationHeight, * dilationWidth]` in which we sample input values across the height * and width dimensions in atrous convolution. Defaults to `[1, 1, 1]`. * If `dilations` is a single number, then * `dilationDepth == dilationHeight == dilationWidth`. If it is greater * than 1, then all values of `strides` must be 1. * * @doc {heading: 'Operations', subheading: 'Convolution'} */ function conv3d_<T extends Tensor4D|Tensor5D>( x: T|TensorLike, filter: Tensor5D|TensorLike, strides: [number, number, number]|number, pad: 'valid'|'same', dataFormat: 'NDHWC'|'NCDHW' = 'NDHWC', dilations: [number, number, number]|number = [1, 1, 1]): T { const $x = convertToTensor(x, 'x', 'conv3d'); const $filter = convertToTensor(filter, 'filter', 'conv3d'); let x5D = $x as Tensor5D; let reshapedTo5D = false; if ($x.rank === 4) { reshapedTo5D = true; x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]); } util.assert( x5D.rank === 5, () => `Error in conv3d: input must be rank 5, but got rank ${x5D.rank}.`); util.assert( $filter.rank === 5, () => `Error in conv3d: filter must be rank 5, but got rank ` + `${$filter.rank}.`); util.assert( x5D.shape[4] === $filter.shape[3], () => `Error in conv3d: depth of input (${x5D.shape[4]}) must match ` + `input depth for filter ${$filter.shape[3]}.`); util.assert( eitherStridesOrDilationsAreOne(strides, dilations), () => 'Error in conv3D: Either strides or dilations must be 1. ' + `Got strides ${strides} and dilations '${dilations}'`); util.assert( dataFormat === 'NDHWC', () => `Error in conv3d: got dataFormat of ${ dataFormat} but only NDHWC is currently supported.`); const inputs: Conv3DInputs = {x: x5D, filter: $filter}; const attrs: Conv3DAttrs = {strides, pad, dataFormat, dilations}; // tslint:disable-next-line: no-unnecessary-type-assertion const res = ENGINE.runKernel( Conv3D, inputs as {} as NamedTensorMap, attrs as {} as NamedAttrMap) as T; if (reshapedTo5D) { return reshape( res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]) as T; } return res; } export const conv3d = op({conv3d_});