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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 {AvgPool3DGrad, AvgPool3DGradAttrs, AvgPool3DGradInputs} 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 {op} from './operation'; import {reshape} from './reshape'; /** * Computes the backprop of a 3d avg pool. * * @param dy The dy error, of rank 5 of shape * [batchSize, depth, height, width, channels]. * assumed. * @param input The original input image, of rank 5 or rank4 of shape * [batchSize, depth, height, width, channels]. * @param filterSize The filter size: * `[filterDepth, filterHeight, filterWidth]`. * `filterSize` is a single number, * then `filterDepth == filterHeight == filterWidth`. * @param strides The strides of the pooling: * `[strideDepth, strideHeight, strideWidth]`. If * `strides` is a single number, then `strideHeight == strideWidth`. * @param pad A string from: 'same', 'valid'. The type of padding algorithm * used in the forward prop of the op. * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. If none is * provided, it will default to truncate. */ function avgPool3dGrad_<T extends Tensor4D|Tensor5D>( dy: T|TensorLike, input: T|TensorLike, filterSize: [number, number, number]|number, strides: [number, number, number]|number, pad: 'valid'|'same'|number, dimRoundingMode?: 'floor'|'round'|'ceil'): T { const $dy = convertToTensor(dy, 'dy', 'avgPool3dGrad'); const $input = convertToTensor(input, 'input', 'avgPool3dGrad'); let dy5D = $dy as Tensor5D; let input5D = $input as Tensor5D; let reshapedTo5D = false; if ($input.rank === 4) { reshapedTo5D = true; dy5D = reshape( $dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]); input5D = reshape($input, [ 1, $input.shape[0], $input.shape[1], $input.shape[2], $input.shape[3] ]); } util.assert( dy5D.rank === 5, () => `Error in avgPool3dGrad: dy must be rank 5 but got rank ` + `${dy5D.rank}.`); util.assert( input5D.rank === 5, () => `Error in avgPool3dGrad: input must be rank 5 but got rank ` + `${input5D.rank}.`); if (dimRoundingMode != null) { util.assert( util.isInt(pad as number), () => `Error in avgPool3dGrad: pad must be an integer when ` + `using, dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`); } const inputs: AvgPool3DGradInputs = {dy: dy5D, input: input5D}; const attrs: AvgPool3DGradAttrs = {filterSize, strides, pad, dimRoundingMode}; // tslint:disable-next-line: no-unnecessary-type-assertion const res = ENGINE.runKernel( AvgPool3DGrad, 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 avgPool3dGrad = op({avgPool3dGrad_});