| 1 | /**
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| 2 | * @license
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| 3 | * Copyright 2020 Google LLC. All Rights Reserved.
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 5 | * you may not use this file except in compliance with the License.
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| 6 | * You may obtain a copy of the License at
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| 7 | *
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0
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| 9 | *
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| 10 | * Unless required by applicable law or agreed to in writing, software
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 13 | * See the License for the specific language governing permissions and
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| 14 | * limitations under the License.
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| 15 | * =============================================================================
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| 16 | */
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| 17 | import { ENGINE } from '../engine';
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| 18 | import { MaxPool } from '../kernel_names';
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| 19 | import { convertToTensor } from '../tensor_util_env';
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| 20 | import * as util from '../util';
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| 21 | import * as conv_util from './conv_util';
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| 22 | import { op } from './operation';
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| 23 | import { reshape } from './reshape';
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| 24 | /**
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| 25 | * Computes the 2D max pooling of an image.
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| 26 | *
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| 27 | * @param x The input tensor, of rank 4 or rank 3 of shape
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| 28 | * `[batch, height, width, inChannels]`. If rank 3, batch of 1 is assumed.
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| 29 | * @param filterSize The filter size: `[filterHeight, filterWidth]`. If
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| 30 | * `filterSize` is a single number, then `filterHeight == filterWidth`.
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| 31 | * @param strides The strides of the pooling: `[strideHeight, strideWidth]`. If
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| 32 | * `strides` is a single number, then `strideHeight == strideWidth`.
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| 33 | * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
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| 34 | * in which we sample input values across the height and width dimensions
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| 35 | * in dilated pooling. Defaults to `[1, 1]`. If `dilations` is a single
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| 36 | * number, then `dilationHeight == dilationWidth`. If it is greater than
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| 37 | * 1, then all values of `strides` must be 1.
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| 38 | * @param pad The type of padding algorithm.
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| 39 | * - `same` and stride 1: output will be of same size as input,
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| 40 | * regardless of filter size.
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| 41 | * - `valid`: output will be smaller than input if filter is larger
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| 42 | * than 1x1.
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| 43 | * - For more info, see this guide:
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| 44 | * [https://www.tensorflow.org/api_guides/python/nn#Convolution](
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| 45 | * https://www.tensorflow.org/api_guides/python/nn#Convolution)
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| 46 | * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. If none is
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| 47 | * provided, it will default to truncate.
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| 48 | */
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| 49 | function maxPool_(x, filterSize, strides, pad, dimRoundingMode) {
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| 50 | const $x = convertToTensor(x, 'x', 'maxPool');
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| 51 | const dilations = 1;
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| 52 | let x4D = $x;
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| 53 | let reshapedTo4D = false;
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| 54 | if ($x.rank === 3) {
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| 55 | reshapedTo4D = true;
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| 56 | x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);
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| 57 | }
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| 58 | util.assert(x4D.rank === 4, () => `Error in maxPool: input must be rank 4 but got rank ${x4D.rank}.`);
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| 59 | util.assert(conv_util.eitherStridesOrDilationsAreOne(strides, dilations), () => 'Error in maxPool: Either strides or dilations must be 1. ' +
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| 60 | `Got strides ${strides} and dilations '${dilations}'`);
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| 61 | if (dimRoundingMode != null) {
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| 62 | util.assert(util.isInt(pad), () => `Error in maxPool: pad must be an integer when using, ` +
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| 63 | `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
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| 64 | }
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| 65 | const inputs = { x: x4D };
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| 66 | const attrs = { filterSize, strides, pad, dimRoundingMode };
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| 67 | // tslint:disable-next-line: no-unnecessary-type-assertion
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| 68 | const res = ENGINE.runKernel(MaxPool, inputs, attrs);
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| 69 | if (reshapedTo4D) {
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| 70 | return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);
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| 71 | }
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| 72 | return res;
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| 73 | }
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| 74 | export const maxPool = op({ maxPool_ });
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| 75 | //# sourceMappingURL=max_pool.js.map |
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