@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @license
* Copyright 2018 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 { MaxPoolWithArgmax } from '../kernel_names';
import { convertToTensor } from '../tensor_util_env';
import { op } from './operation';
/**
* Computes the 2D max pooling of an image with Argmax index.
* The indices in argmax are flattened, so that a maximum value at position `[b,
* y, x, c]` becomes flattened index: `(y * width + x) * channels + c` if
* include_batch_in_index is False; `((b * height + y) * width + x) * channels
* +c` if include_batch_in_index is True.
*
* The indices returned are always in `[0, height) x [0, width)` before
* flattening.
*
* @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 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.
* @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_guides/python/nn#Convolution](
* https://www.tensorflow.org/api_guides/python/nn#Convolution)
* @param includeBatchIndex Defaults to False. Whether to include batch
* dimension in flattened index of argmax.
*
* @doc {heading: 'Operations', subheading: 'Convolution'}
*/
function maxPoolWithArgmax_(x, filterSize, strides, pad, includeBatchInIndex = false) {
const $x = convertToTensor(x, 'x', 'maxPoolWithArgmax');
const inputs = { x: $x };
const attrs = { filterSize, strides, pad, includeBatchInIndex };
// tslint:disable-next-line: no-unnecessary-type-assertion
const result = ENGINE.runKernel(MaxPoolWithArgmax, inputs, attrs);
return { result: result[0], indexes: result[1] };
}
export const maxPoolWithArgmax = op({ maxPoolWithArgmax_ });
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