• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
1 /*
2  * Copyright (c) 2018-2020 Arm Limited.
3  *
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  */
24 #ifndef ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
25 #define ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
26 
27 #include "src/core/NEON/INEKernel.h"
28 
29 namespace arm_compute
30 {
31 // Forward declarations
32 class 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  */
42 class NEConvertFullyConnectedWeightsKernel : public INEKernel
43 {
44 public:
name()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      *
63      * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
64      * @param[out] output               The converted weights tensor. Shape and Data Type: Same as @p input.
65      * @param[in]  original_input_shape Shape of the original input tensor (the one entering fully connected layer).
66      * @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      *
71      * @param[in] input                Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
72      * @param[in] output               The converted weights tensor info. Shape and Data Type: Same as @p input.
73      * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
74      * @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 
81 private:
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
95 #endif /*ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H */
96