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1 /*
2  * Copyright (c) 2017-2020 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_NEDECONVOLUTIONLAYER_H
25 #define ARM_COMPUTE_NEDECONVOLUTIONLAYER_H
26 
27 #include "arm_compute/runtime/CPP/functions/CPPUpsample.h"
28 #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
29 #include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h"
30 #include "arm_compute/runtime/NEON/functions/NEReverse.h"
31 
32 #include "arm_compute/core/Types.h"
33 #include "arm_compute/runtime/IFunction.h"
34 #include "arm_compute/runtime/IMemoryManager.h"
35 #include "arm_compute/runtime/MemoryGroup.h"
36 #include "arm_compute/runtime/Tensor.h"
37 
38 #include <memory>
39 
40 namespace arm_compute
41 {
42 /** Function to run the deconvolution layer.
43  *
44  * Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perfrom a 1x1
45  * convolution pass. Input stride defines how many zeroes we should put between each element of the input, pad is the amount of padding and finaly a is a user
46  * specified value where a < stride - 1 that increases the padding top and right of the input image.
47  *
48  *  The relation between input to output is as follows:
49  *  \f[
50  *       width\_output = (width\_input - 1) \cdot stride\_x - 2 \cdot padding\_x + kernel\_x
51  *  \f]
52  *  \f[
53  *       height\_output = (height\_input - 1) \cdot stride\_y - 2 \cdot padding\_y + kernel\_y
54  *  \f]
55  *
56  *  where
57  *      width is the size of the first input dimension.
58  *      height is the size of the second input dimension.
59  *      width_output is the size of the first output dimension.
60  *      height_output is the size of the second output dimension.
61  *      kernel_x and kernel_y are the convolution sizes in x and y.
62  *      stride_x and stride_y is the input stride of the first and second dimension.
63  *
64  * The weights used by Deconvolution are supposed to be the same as the ones used for Convolution. Therefore, it will be necessary to use the weights in the
65  * reverse order to perform an actual convolution. This is achieved by using @ref NEReverse.
66  *
67  * This function calls the following NEON kernels/functions:
68  *
69  * -# @ref CPPUpsample
70  * -# @ref NEConvolutionLayer
71  * -# @ref NEPermute
72  * -# @ref NEReverse
73  *
74  */
75 class NEDeconvolutionLayer : public IFunction
76 {
77 public:
78     /** Constructor */
79     NEDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
80 
81     /** Prevent instances of this class from being copied (As this class contains pointers) */
82     NEDeconvolutionLayer(const NEDeconvolutionLayer &) = delete;
83     /** Prevent instances of this class from being copied (As this class contains pointers) */
84     NEDeconvolutionLayer &operator=(const NEDeconvolutionLayer &) = delete;
85     /** Prevent instances of this class from being moved (As this class contains pointers) */
86     NEDeconvolutionLayer(NEDeconvolutionLayer &&) = delete;
87     /** Prevent instances of this class from being moved (As this class contains pointers) */
88     NEDeconvolutionLayer &operator=(NEDeconvolutionLayer &&) = delete;
89     /** Default destructor */
90     virtual ~NEDeconvolutionLayer() = default;
91 
92     /** Set the input, weights, biases and output tensors.
93      *
94      * @param[in,out] input   Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32/F16/QASYMM8/QASYMM8_SIGNED.
95      * @param[in]     weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
96      * @param[in]     bias    Optional, ignored if NULL. The biases have one dimension. Data type supported: Data types supported: S32 for QASYMM8 and QASYMM8_SIGNED input, F32 for F32 input, F16 for F16 input.
97      * @param[out]    output  Output tensor. The output has the same number of dimensions as the @p input.
98      * @param[in]     info    Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
99      *
100      */
101     void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info);
102     /** Static function to check if given info will lead to a valid configuration of @ref NEDeconvolutionLayer
103      *
104      * @param[in] input   Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32/F16/QASYMM8/QASYMM8_SIGNED.
105      * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
106      * @param[in] bias    (Optional) The biases have one dimension. Data type supported: Data types supported: S32 for QASYMM8 and QASYMM8_SIGNED input, F32 for F32 input, F16 for F16 input.
107      * @param[in] output  Output tensor info. The output has the same number of dimensions as the @p input.
108      * @param[in] info    Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
109      *
110      * @return a status
111      */
112     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &info);
113 
114     // Inherited methods overridden:
115     void run() override;
116     void prepare() override;
117 
118 private:
119     MemoryGroup        _memory_group;
120     NEConvolutionLayer _conv_f;
121     CPPUpsample        _upsample_f;
122     NEReverse          _flip_weights;
123     Tensor             _scaled_output;
124     Tensor             _weights_flipped;
125     Tensor             _flip_axis;
126     const ITensor     *_original_weights;
127     ITensor           *_input;
128     PadStrideInfo      _info;
129     bool               _is_prepared;
130 };
131 } // arm_compute
132 #endif /* ARM_COMPUTE_NEDECONVOLUTIONLAYER_H */
133