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avg_pool_3d.ts
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avg_pool_3d.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 {AvgPool3D, AvgPool3DAttrs, AvgPool3DInputs} 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 {cast} from './cast';
import {checkPadOnDimRoundingMode} from './conv_util';
import {op} from './operation';
import {reshape} from './reshape';
/**
* Computes the 3D average pooling.
*
* ```js
* const x = tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]);
* const result = tf.avgPool3d(x, 2, 1, 'valid');
* result.print();
* ```
*
* @param x The input tensor, of rank 5 or rank 4 of shape
* `[batch, depth, height, width, inChannels]`.
* @param filterSize The filter size:
* `[filterDepth, filterHeight, filterWidth]`.
* If `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 `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 1*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.
* @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.
*
* @doc {heading: 'Operations', subheading: 'Convolution'}
*/
function avgPool3d_<T extends Tensor4D|Tensor5D>(
x: T|TensorLike, filterSize: [number, number, number]|number,
strides: [number, number, number]|number, pad: 'valid'|'same'|number,
dimRoundingMode?: 'floor'|'round'|'ceil',
dataFormat: 'NDHWC'|'NCDHW' = 'NDHWC'): T {
const $x = convertToTensor(x, 'x', 'avgPool3d', 'float32');
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 avgPool3d: x must be rank 5 but got rank ${x5D.rank}.`);
util.assert(
dataFormat === 'NDHWC',
() => `Error in avgPool3d: Only NDHWC is currently supported, ` +
`but got dataFormat of ${dataFormat}`);
util.assert(
(typeof strides === 'number' && strides > 0) ||
(typeof strides === 'object' && strides[0] > 0 && strides[1] > 0 &&
strides[2] > 0),
() => `Error in avgPool3d: Stride must be > 0, but got '${strides}'`);
checkPadOnDimRoundingMode('avgPool3d', pad, dimRoundingMode);
const inputs: AvgPool3DInputs = {x: x5D};
const attrs:
AvgPool3DAttrs = {filterSize, strides, pad, dimRoundingMode, dataFormat};
// tslint:disable-next-line: no-unnecessary-type-assertion
let res = ENGINE.runKernel(
AvgPool3D, inputs as unknown as NamedTensorMap,
attrs as unknown as NamedAttrMap) as T;
res = cast(res, x5D.dtype);
if (reshapedTo5D) {
return reshape(
res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]) as
T;
}
return res;
}
export const avgPool3d = op({avgPool3d_});