| 1 | /// <amd-module name="@tensorflow/tfjs-core/dist/ops/separable_conv2d" />
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| 2 | /**
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| 3 | * @license
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| 4 | * Copyright 2020 Google LLC. All Rights Reserved.
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| 5 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 6 | * you may not use this file except in compliance with the License.
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| 7 | * You may obtain a copy of the License at
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| 8 | *
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| 9 | * http://www.apache.org/licenses/LICENSE-2.0
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| 10 | *
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| 11 | * Unless required by applicable law or agreed to in writing, software
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| 12 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 14 | * See the License for the specific language governing permissions and
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| 15 | * limitations under the License.
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| 16 | * =============================================================================
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| 17 | */
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| 18 | import { Tensor3D, Tensor4D } from '../tensor';
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| 19 | import { TensorLike } from '../types';
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| 20 | /**
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| 21 | * 2-D convolution with separable filters.
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| 22 | *
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| 23 | * Performs a depthwise convolution that acts separately on channels followed
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| 24 | * by a pointwise convolution that mixes channels. Note that this is
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| 25 | * separability between dimensions [1, 2] and 3, not spatial separability
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| 26 | * between dimensions 1 and 2.
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| 27 | *
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| 28 | * See
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| 29 | * [https://www.tensorflow.org/api_docs/python/tf/nn/separable_conv2d](
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| 30 | * https://www.tensorflow.org/api_docs/python/tf/nn/separable_conv2d)
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| 31 | * for more details.
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| 32 | *
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| 33 | * @param x The input tensor, of rank 4 or rank 3, of shape
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| 34 | * `[batch, height, width, inChannels]`. If rank 3, batch of 1 is
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| 35 | * assumed.
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| 36 | * @param depthwiseFilter The depthwise filter tensor, rank 4, of shape
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| 37 | * `[filterHeight, filterWidth, inChannels, channelMultiplier]`. This is
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| 38 | * the filter used in the first step.
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| 39 | * @param pointwiseFilter The pointwise filter tensor, rank 4, of shape
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| 40 | * `[1, 1, inChannels * channelMultiplier, outChannels]`. This is
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| 41 | * the filter used in the second step.
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| 42 | * @param strides The strides of the convolution: `[strideHeight,
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| 43 | * strideWidth]`. If strides is a single number, then `strideHeight ==
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| 44 | * strideWidth`.
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| 45 | * @param pad The type of padding algorithm.
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| 46 | * - `same` and stride 1: output will be of same size as input,
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| 47 | * regardless of filter size.
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| 48 | * - `valid`: output will be smaller than input if filter is larger
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| 49 | * than 1x1.
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| 50 | * - For more info, see this guide:
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| 51 | * [https://www.tensorflow.org/api_docs/python/tf/nn/convolution](
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| 52 | * https://www.tensorflow.org/api_docs/python/tf/nn/convolution)
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| 53 | * @param dilations The dilation rates: `[dilationHeight, dilationWidth]`
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| 54 | * in which we sample input values across the height and width dimensions
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| 55 | * in atrous convolution. Defaults to `[1, 1]`. If `rate` is a single
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| 56 | * number, then `dilationHeight == dilationWidth`. If it is greater than
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| 57 | * 1, then all values of `strides` must be 1.
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| 58 | * @param dataFormat: An optional string from: "NHWC", "NCHW". Defaults to
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| 59 | * "NHWC". Specify the data format of the input and output data. With the
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| 60 | * default format "NHWC", the data is stored in the order of: [batch,
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| 61 | * height, width, channels]. Only "NHWC" is currently supported.
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| 62 | *
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| 63 | * @doc {heading: 'Operations', subheading: 'Convolution'}
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| 64 | */
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| 65 | declare function separableConv2d_<T extends Tensor3D | Tensor4D>(x: T | TensorLike, depthwiseFilter: Tensor4D | TensorLike, pointwiseFilter: Tensor4D | TensorLike, strides: [number, number] | number, pad: 'valid' | 'same', dilation?: [number, number] | number, dataFormat?: 'NHWC' | 'NCHW'): T;
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| 66 | export declare const separableConv2d: typeof separableConv2d_;
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| 67 | export {};
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