1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
|
/*
* Copyright (c) 2017-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ARM_COMPUTE_CLDECONVOLUTIONLAYER_H
#define ARM_COMPUTE_CLDECONVOLUTIONLAYER_H
#include "arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h"
#include "arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include <memory>
namespace arm_compute
{
/** Basic function to compute the deconvolution layer. This function calls the following OpenCL kernels/functions:
*
* -# @ref CLGEMMDeconvolutionLayer
* -# @ref CLDirectDeconvolutionLayer
*/
class CLDeconvolutionLayer : public IFunction
{
public:
/** Default constructor */
CLDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
~CLDeconvolutionLayer();
/** Set the input, weights, biases and output tensors.
*
* Valid data layouts:
* - NHWC
* - NCHW
*
* Valid data type configurations:
* |src0 |src1 |src2 |dst |
* |:--------------|:------------------|:------|:--------------|
* |F16 |F16 |F16 |F16 |
* |F32 |F32 |F32 |F32 |
* |QASYMM8 |QASYMM8 |S32 |QASYMM8 |
* |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 |
* |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED |
* |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED |
*
* @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: QASYMM8_SIGNED/QASYMM8/F16/F32.
* @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
* @param[out] output Output tensor. The output has the same number of dimensions as the @p input.
* @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref opencl::kernels::ClWeightsReshapeKernel.
*
*/
void configure(ICLTensor *input,
ICLTensor *weights,
const ICLTensor *bias,
ICLTensor *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info = WeightsInfo());
/** Set the input, weights, biases and output tensors.
*
* @param[in] compile_context The compile context to be used.
* @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: QASYMM8_SIGNED/QASYMM8/F16/F32.
* @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
* @param[out] output Output tensor. The output has the same number of dimensions as the @p input.
* @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref opencl::kernels::ClWeightsReshapeKernel.
*
*/
void configure(const CLCompileContext &compile_context,
ICLTensor *input,
ICLTensor *weights,
const ICLTensor *bias,
ICLTensor *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info = WeightsInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayer
*
* @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: QASYMM8_SIGNED/QASYMM8/F16/F32.
* @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
* @param[in] bias (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
* @param[in] output Output tensor info. The output has the same number of dimensions as the @p input.
* @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
* @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref opencl::kernels::ClWeightsReshapeKernel.
*
* @return a status
*/
static Status validate(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *bias,
ITensorInfo *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info = WeightsInfo());
static DeconvolutionMethod get_deconvolution_method(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *bias,
ITensorInfo *output,
const PadStrideInfo &deconv_info,
const WeightsInfo &weights_info);
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
std::shared_ptr<IMemoryManager> _memory_manager;
std::unique_ptr<IFunction> _function;
struct Impl;
std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_CLDECONVOLUTIONLAYER_H */
|
