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
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
|
/*
* Copyright (c) 2021, 2023 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 ACL_SRC_GPU_CL_OPERATORS_CLGEMMCONV2D_H
#define ACL_SRC_GPU_CL_OPERATORS_CLGEMMCONV2D_H
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/FunctionDescriptors.h"
#include "src/gpu/cl/ClCompileContext.h"
#include "src/gpu/cl/IClOperator.h"
#include <memory>
namespace arm_compute
{
namespace opencl
{
class ClGemm;
class ClGemmLowpMatrixMultiplyCore;
namespace kernels
{
class ClIm2ColKernel;
class ClCol2ImKernel;
class ClWeightsReshapeKernel;
class ClActivationKernel;
} // namespace kernels
/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
*
* -# @ref opencl::kernels::ClIm2ColKernel
* -# @ref ClGemm (if the data type is FP32 or FP16)
* -# @ref CLGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8/QASYMM8_SIGNED)
* -# @ref ClGemmLowpOutputStage with QUANTIZE_DOWN_FIXEDPOINT type of quantization (if the data type is QASYMM8/QASYMM8_SIGNED)
* -# @ref opencl::kernels::ClCol2ImKernel (if NCHW data layout)
* -# @ref opencl::kernels::ClActivationKernel
*/
class ClGemmConv2d : public IClOperator
{
public:
/** Constructor */
ClGemmConv2d();
/** Prevent instances of this class from being copied (As this class contains pointers) */
ClGemmConv2d(const ClGemmConv2d &) = delete;
/** Default move constructor */
ClGemmConv2d(ClGemmConv2d &&) = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
ClGemmConv2d &operator=(const ClGemmConv2d &) = delete;
/** Default move assignment operator */
ClGemmConv2d &operator=(ClGemmConv2d &&) = default;
/**Default destructor */
~ClGemmConv2d();
/** Set the input 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] compile_context The compile context to be used.
* @param[in] src Source tensor info. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
* Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
* @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
* @param[out] dst Destination tensor info. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv2d_info Contains convolution 2d info described in @ref Conv2dInfo.
* @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
* tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
*/
void configure(const ClCompileContext &compile_context,
ITensorInfo *src,
ITensorInfo *weights,
ITensorInfo *biases,
ITensorInfo *dst,
const Conv2dInfo &conv2d_info,
const WeightsInfo &weights_info = WeightsInfo());
/** Static function to check if given info will lead to a valid configuration
*
* Similar to ClGemmConvolution::configure()
*
* @return a status
*/
static Status validate(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *biases,
const ITensorInfo *output,
const Conv2dInfo &conv2d_info,
const WeightsInfo &weights_info = WeightsInfo());
// Inherited methods overridden:
void run(ITensorPack &tensors) override;
void prepare(ITensorPack &constants) override;
experimental::MemoryRequirements workspace() const override;
private:
/** Configures the appropriate matrix multiply routine
*
* @param[in] compile_context The compile context to be used.
* @param[in] src Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor info. Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or
* QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
* @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
* @param[in, out] dst Output tensor info. Data types supported: same as @p input.
* @param[in] gemmlowp_output_stage GEMMLowp output stage info
* @param[in] gemm_3d_depth Depth of GEMM 3D
* @param[in] act_info Activation to apply after the matrix multiplication
*/
void configure_mm(const CLCompileContext &compile_context,
const ITensorInfo *src,
ITensorInfo *weights,
ITensorInfo *biases,
ITensorInfo *dst,
const GEMMLowpOutputStageInfo &gemmlowp_output_stage,
int gemm_3d_depth,
const ActivationLayerInfo &act_info);
/** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer matrix multiply routines
*
* @param[in] src Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor info. Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or
* QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
* @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
* @param[in] dst Output tensor info. Data types supported: same as @p input.
* @param[in] gemmlowp_output_stage GEMMLowp output stage info
* @param[in] gemm_3d_depth Depth of GEMM 3D
* @param[in] skip_im2col Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout.
* @param[in] act_info Activation to apply after the matrix multiplication
*
* @return a status
*/
static Status validate_mm(const ITensorInfo *src,
const ITensorInfo *weights,
const ITensorInfo *biases,
const ITensorInfo *dst,
const GEMMLowpOutputStageInfo &gemmlowp_output_stage,
int gemm_3d_depth,
bool skip_im2col,
const ActivationLayerInfo &act_info);
enum AuxTensorIdx
{
// ClGemmLowpMatrixMultiplyCore has up to 7 internal tensors
Im2ColOutput = 8,
WeightsReshaped,
GemmOutput,
Count
};
std::unique_ptr<kernels::ClWeightsReshapeKernel> _weights_reshape_kernel;
std::unique_ptr<kernels::ClIm2ColKernel> _im2col_kernel;
std::unique_ptr<ClGemm> _mm_gemm;
std::unique_ptr<ClGemmLowpMatrixMultiplyCore> _mm_gemmlowp;
std::unique_ptr<opencl::kernels::ClCol2ImKernel> _col2im_kernel;
std::unique_ptr<kernels::ClActivationKernel> _activation_kernel;
TensorInfo _im2col_output;
TensorInfo _weights_reshaped;
TensorInfo _gemm_output;
bool _skip_im2col;
bool _skip_col2im;
bool _is_quantized;
bool _fuse_activation;
bool _append_bias;
bool _is_prepared;
experimental::MemoryRequirements _aux_mem;
};
} // namespace opencl
} // namespace arm_compute
#endif // ACL_SRC_GPU_CL_OPERATORS_CLGEMMCONV2D_H
|
