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max_pool.ts
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max_pool.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 {MaxPool, MaxPoolAttrs, MaxPoolInputs} from '../kernel_names';
import {NamedAttrMap} from '../kernel_registry';
import {Tensor3D, Tensor4D} from '../tensor';
import {NamedTensorMap} from '../tensor_types';
import {convertToTensor} from '../tensor_util_env';
import {TensorLike} from '../types';
import * as util from '../util';
import * as conv_util from './conv_util';
import {op} from './operation';
import {reshape} from './reshape';
/**
* Computes the 2D max pooling of an image.
*
* @param x The input tensor, of rank 4 or rank 3 of shape
* `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
* @param filterSize The filter size: `[filterHeight, filterWidth]`. If
* `filterSize` is a single number, then `filterHeight == filterWidth`.
* @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
* `strides` is a single number, then `strideHeight == strideWidth`.
* @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
* in which we sample input values across the height and width dimensions
* in dilated pooling. 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.
* @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_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.
*/
function maxPool_<T extends Tensor3D|Tensor4D>(
x: T|TensorLike, filterSize: [number, number]|number,
strides: [number, number]|number,
pad: 'valid'|'same'|number|conv_util.ExplicitPadding,
dimRoundingMode?: 'floor'|'round'|'ceil'): T {
const $x = convertToTensor(x, 'x', 'maxPool');
const dilations = 1;
let x4D = $x as Tensor4D;
let reshapedTo4D = false;
if ($x.rank === 3) {
reshapedTo4D = true;
x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
}
util.assert(
x4D.rank === 4,
() => `Error in maxPool: input must be rank 4 but got rank ${x4D.rank}.`);
util.assert(
conv_util.eitherStridesOrDilationsAreOne(strides, dilations),
() => 'Error in maxPool: Either strides or dilations must be 1. ' +
`Got strides ${strides} and dilations '${dilations}'`);
conv_util.checkPadOnDimRoundingMode('maxPool', pad, dimRoundingMode);
const inputs: MaxPoolInputs = {x: x4D};
const attrs: MaxPoolAttrs = {filterSize, strides, pad, dimRoundingMode};
// tslint:disable-next-line: no-unnecessary-type-assertion
const res = ENGINE.runKernel(
MaxPool, inputs as unknown as NamedTensorMap,
attrs as unknown as NamedAttrMap) as T;
if (reshapedTo4D) {
return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]) as T;
}
return res;
}
export const maxPool = /* @__PURE__ */ op({maxPool_});