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
|
/*
* Copyright (c) 2017-2021 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_NEFULLYCONNECTEDLAYER_H
#define ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h"
#include "arm_compute/runtime/NEON/functions/NEFlattenLayer.h"
#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
#include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h"
#include "arm_compute/runtime/NEON/functions/NETranspose.h"
#include "arm_compute/runtime/Tensor.h"
namespace arm_compute
{
namespace weights_transformations
{
/** Basic function to manage the reshape weights generated from @ref NETranspose */
class NEFullyConnectedLayerReshapeWeightsManaged : public ITransformWeights
{
public:
void run() override
{
_output.allocator()->allocate();
_func.run();
_reshape_run = true;
}
void release() override
{
_output.allocator()->free();
}
ITensor *get_weights() override
{
return &_output;
}
uint32_t uid() override
{
return _uid;
}
void configure(const ITensor *input)
{
_func.configure(input, &_output);
}
private:
static constexpr uint32_t _uid = 0x0;
Tensor _output{};
NETranspose _func{};
};
} // namespace weights_transformations
/** Basic function to compute a Fully Connected layer. This function calls the following kernels:
* -# @ref NEIm2ColKernel (called when the input comes from a convolutional layer)
* -# @ref NETranspose (if @p are_weights_reshaped is set to false and transpose_weights is set to true ) (called once)
* -# @ref NEGEMMMatrixMultiplyKernel or @ref NEGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
* -# @ref cpu::kernels::CpuGemmMatrixAdditionKernel or @ref NEGEMMLowpOutputStage (if quantized asymmetric) (if @p biases is not equal to nullptr)
*
* @note The fully connected layer accepts "weights" tensors only with 2 dimensions.
*/
class NEFullyConnectedLayer : public IFunction
{
public:
/** Constructor */
NEFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEFullyConnectedLayer(const NEFullyConnectedLayer &) = delete;
/** Prevent instances of this class from being moved (As this class contains pointers) */
NEFullyConnectedLayer(NEFullyConnectedLayer &&) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEFullyConnectedLayer &operator=(const NEFullyConnectedLayer &) = delete;
/** Prevent instances of this class from being moved (As this class contains pointers) */
NEFullyConnectedLayer &operator=(NEFullyConnectedLayer &&) = delete;
/** Default destructor */
~NEFullyConnectedLayer();
/** 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_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED |
*
* @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor. The weights must be 2 dimensional.
* If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
* If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
* Data type supported: Same as @p input.
* @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED.
* @param[out] output Destination tensor. Its shape should be equal to the output of a matrix multiplication between:
* - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
* - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
* Data type supported: Same as @p input.
* @param[in] fc_info (Optional) Fully connected layer additional info
*/
void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output,
FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref NEFullyConnectedLayer
*
* @param[in] input Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor info. The weights must be 2 dimensional.
* If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
* If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
* Data type supported: Same as @p input.
* @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED.
* @param[in] output Destination tensor info. Its shape should be equal to the output of a matrix multiplication between:
* - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
* - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
* Data type supported: Same as @p input.
* @param[in] fc_info (Optional) Fully connected layer additional info
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
//Inherited methods override
void run() override;
void prepare() override;
private:
void configure_fc_fc(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act);
void configure_conv_fc(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act);
void configure_mm(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act);
MemoryGroup _memory_group;
IWeightsManager *_weights_manager;
NEFlattenLayer _flatten;
NEConvertFullyConnectedWeights _convert_weights;
weights_transformations::NEConvertFullyConnectedWeightsManaged _convert_weights_managed;
NETranspose _reshape_weights_function;
weights_transformations::NEFullyConnectedLayerReshapeWeightsManaged _reshape_weights_managed_function;
NEGEMM _mm_gemm;
NEGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
Tensor _flatten_output;
Tensor _converted_weights_output;
Tensor _reshape_weights_output;
const ITensor *_original_weights;
bool _are_weights_converted;
bool _are_weights_reshaped;
bool _is_fc_after_conv;
bool _is_quantized_asymmetric;
bool _is_prepared;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_NEFULLYCONNECTEDLAYER_H */
|