1 | /// <amd-module name="@tensorflow/tfjs-core/dist/ops/conv2d" />
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2 | import { Tensor3D, Tensor4D } from '../tensor';
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3 | import { TensorLike } from '../types';
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4 | import * as conv_util from './conv_util';
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5 | /**
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6 | * Computes a 2D convolution over the input x.
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7 | *
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8 | * @param x The input tensor, of rank 4 or rank 3, of shape
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9 | * `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
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10 | * assumed.
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11 | * @param filter The filter, rank 4, of shape
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12 | * `[filterHeight, filterWidth, inDepth, outDepth]`.
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13 | * @param strides The strides of the convolution: `[strideHeight,
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14 | * strideWidth]`.
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15 | * @param pad The type of padding algorithm.
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16 | * - `same` and stride 1: output will be of same size as input,
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17 | * regardless of filter size.
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18 | * - `valid`: output will be smaller than input if filter is larger
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19 | * than 1x1.
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20 | * - For more info, see this guide:
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21 | * [https://www.tensorflow.org/api_docs/python/tf/nn/convolution](
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22 | * https://www.tensorflow.org/api_docs/python/tf/nn/convolution)
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23 | * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
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24 | * "NHWC". Specify the data format of the input and output data. With the
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25 | * default format "NHWC", the data is stored in the order of: [batch,
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26 | * height, width, channels].
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27 | * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
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28 | * in which we sample input values across the height and width dimensions
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29 | * in atrous convolution. Defaults to `[1, 1]`. If `dilations` is a single
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30 | * number, then `dilationHeight == dilationWidth`. If it is greater than
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31 | * 1, then all values of `strides` must be 1.
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32 | * @param dimRoundingMode A string from: 'ceil', 'round', 'floor'. If none is
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33 | * provided, it will default to truncate.
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34 | *
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35 | * @doc {heading: 'Operations', subheading: 'Convolution'}
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36 | */
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37 | declare function conv2d_<T extends Tensor3D | Tensor4D>(x: T | TensorLike, filter: Tensor4D | TensorLike, strides: [number, number] | number, pad: 'valid' | 'same' | number | conv_util.ExplicitPadding, dataFormat?: 'NHWC' | 'NCHW', dilations?: [number, number] | number, dimRoundingMode?: 'floor' | 'round' | 'ceil'): T;
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38 | export declare const conv2d: typeof conv2d_;
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39 | export {};
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