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Giorgio Arena657bdb32018-04-26 18:52:01 +01001/*
Michalis Spyrouebcebf12020-10-21 00:04:14 +01002 * Copyright (c) 2018-2020 Arm Limited.
Giorgio Arena657bdb32018-04-26 18:52:01 +01003 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
Michalis Spyrouf4643372019-11-29 16:17:13 +000024#ifndef ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
25#define ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
Giorgio Arena657bdb32018-04-26 18:52:01 +010026
Michalis Spyrouebcebf12020-10-21 00:04:14 +010027#include "src/core/NEON/INEKernel.h"
Giorgio Arena657bdb32018-04-26 18:52:01 +010028
29namespace arm_compute
30{
Georgios Pinitas33843562019-12-10 13:33:18 +000031// Forward declarations
Giorgio Arena657bdb32018-04-26 18:52:01 +010032class ITensor;
33
34/** Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa.
35 *
36 * @note This function can be applied to the 2D weights used by a Fully Connected layer if:
37 * - It follows a Convolution layer
38 * - The data layout used by the network does not match the one the model has been trained in.
39 *
40 * @note This function assumes the weights are already reshaped (transposed)
41 */
42class NEConvertFullyConnectedWeightsKernel : public INEKernel
43{
44public:
45 const char *name() const override
46 {
47 return "NEConvertFullyConnectedWeightsKernel";
48 }
49 /** Default constructor */
50 NEConvertFullyConnectedWeightsKernel();
51 /** Prevent instances of this class from being copied (As this class contains pointers) */
52 NEConvertFullyConnectedWeightsKernel(const NEConvertFullyConnectedWeightsKernel &) = delete;
53 /** Prevent instances of this class from being copied (As this class contains pointers) */
54 NEConvertFullyConnectedWeightsKernel &operator=(const NEConvertFullyConnectedWeightsKernel &) = delete;
55 /** Allow instances of this class to be moved */
56 NEConvertFullyConnectedWeightsKernel(NEConvertFullyConnectedWeightsKernel &&) = default;
57 /** Allow instances of this class to be moved */
58 NEConvertFullyConnectedWeightsKernel &operator=(NEConvertFullyConnectedWeightsKernel &&) = default;
59 /** Default destructor */
60 ~NEConvertFullyConnectedWeightsKernel() = default;
61 /** Set the input and output tensor.
62 *
Georgios Pinitas33843562019-12-10 13:33:18 +000063 * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
Giorgio Arena657bdb32018-04-26 18:52:01 +010064 * @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input.
Georgios Pinitas7d66a8e2018-07-17 12:28:42 +010065 * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
Giorgio Arena657bdb32018-04-26 18:52:01 +010066 * @param[in] data_layout The data layout the weights have been trained in.
67 */
68 void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
69 /** Static function to check if given info will lead to a valid configuration of @ref NEConvertFullyConnectedWeightsKernel
70 *
Georgios Pinitas33843562019-12-10 13:33:18 +000071 * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
Giorgio Arena657bdb32018-04-26 18:52:01 +010072 * @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input.
Georgios Pinitas7d66a8e2018-07-17 12:28:42 +010073 * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
Giorgio Arena657bdb32018-04-26 18:52:01 +010074 * @param[in] data_layout The data layout the weights have been trained in.
75 */
76 static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout);
77
78 // Inherited methods overridden:
79 void run(const Window &window, const ThreadInfo &info) override;
80
81private:
82 /** Template function to run the permute
83 *
84 * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
85 */
86 template <typename T>
87 void run_convert_fc_weights(const Window &window);
88
89 const ITensor *_input;
90 ITensor *_output;
91 unsigned int _factor1; /* equals to the number of elements per original input plane if @p data_layout == NCHW; its number of channels otherwise */
92 unsigned int _factor2; /* equals to the number of elements per original input plane if @p data_layout == NHWC; its number of channels otherwise */
93};
94} // namespace arm_compute
Michalis Spyrouf4643372019-11-29 16:17:13 +000095#endif /*ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H */