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avg_pool_3d_grad.ts
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avg_pool_3d_grad.ts
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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 {checkPadOnDimRoundingMode} from './conv_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}.`);
checkPadOnDimRoundingMode('avgPool3dGrad', pad, dimRoundingMode);
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 unknown as NamedTensorMap,
attrs as unknown 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 = /* @__PURE__ */ op({avgPool3dGrad_});