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
|
/*
* Copyright (c) 2017-2019 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_CLSOFTMAXLAYERKERNEL_H
#define ARM_COMPUTE_CLSOFTMAXLAYERKERNEL_H
#include "arm_compute/core/CL/ICLSimple3DKernel.h"
#include "arm_compute/core/KernelDescriptors.h"
#include <tuple>
namespace arm_compute
{
class ICLTensor;
/** Interface for the identifying the max value of 1D Logits */
class CLLogits1DMaxKernel : public ICLSimple3DKernel
{
public:
/** Set the input and output tensors.
*
* @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32
* @param[out] output Destination tensor. Data types supported: same as @p input
*/
void configure(const ICLTensor *input, ICLTensor *output);
/** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DMaxKernel
*
* @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32
* @param[in] output Destination tensor. Data types supported: same as @p input
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output);
};
/** Interface for shifting, exponentiating and summing the logits */
class CLLogits1DShiftExpSumKernel : public ICLKernel
{
public:
/** Default constructor */
CLLogits1DShiftExpSumKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLLogits1DShiftExpSumKernel(const CLLogits1DShiftExpSumKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLLogits1DShiftExpSumKernel &operator=(const CLLogits1DShiftExpSumKernel &) = delete;
/** Allow instances of this class to be moved */
CLLogits1DShiftExpSumKernel(CLLogits1DShiftExpSumKernel &&) = default;
/** Allow instances of this class to be moved */
CLLogits1DShiftExpSumKernel &operator=(CLLogits1DShiftExpSumKernel &&) = default;
/** Set the input and output tensors.
*
* @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32
* @param[in] max Max values tensor. Data types supported: same as @p input
* @param[out] output Destination tensor. Data types supported: S32 for QASYMM8 @p input, or same as @p input
* @param[out] sum Sum of 1D logits tensor. Data types supported: S32 for QASYMM8 @p input, or same as @p input
* @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.0
*/
void configure(const ICLTensor *input, const ICLTensor *max, ICLTensor *output, ICLTensor *sum, float beta = 1.0f);
/** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DShiftExpSumKernel
*
* @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32
* @param[in] max Max values tensor. Data types supported: same as @p input
* @param[in] output Destination tensor. Data types supported: S32 for QASYMM8 @p input, or same as @p input
* @param[in] sum Sum of 1D logits tensor. Data types supported: S32 for QASYMM8 @p input, or same as @p input
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const ITensorInfo *sum);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
private:
const ICLTensor *_input;
const ICLTensor *_max;
ICLTensor *_output;
ICLTensor *_sum;
};
/** Interface for max, shifting, exponentiating and summing the logits */
class CLLogits1DMaxShiftExpSumKernel : public ICLKernel
{
public:
/** Info for whether a parallel reduction will be run and the vector size of the execution. */
using ParallelReductionInfo = std::tuple<bool, unsigned int>;
public:
/** Default constructor */
CLLogits1DMaxShiftExpSumKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLLogits1DMaxShiftExpSumKernel(const CLLogits1DMaxShiftExpSumKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLLogits1DMaxShiftExpSumKernel &operator=(const CLLogits1DMaxShiftExpSumKernel &) = delete;
/** Allow instances of this class to be moved */
CLLogits1DMaxShiftExpSumKernel(CLLogits1DMaxShiftExpSumKernel &&) = default;
/** Allow instances of this class to be moved */
CLLogits1DMaxShiftExpSumKernel &operator=(CLLogits1DMaxShiftExpSumKernel &&) = default;
/** Set the input and output tensors.
*
* @param[in] input Source tensor. Data types supported: F16/F32
* @param[in,out] max Max values tensor. Data types supported: same as @p input
* @param[out] output Destination tensor. Data types supported: same as @p input
* @param[out] sum Sum of 1D logits tensor. Data types supported: same as @p input
* @param[in] info Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
*/
void configure(const ICLTensor *input, ICLTensor *max, ICLTensor *output, ICLTensor *sum, const SoftmaxKernelInfo &info);
/** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DMaxShiftExpSumKernel
*
* @param[in] input Source tensor. Data types supported: F16/F32
* @param[in] max Max values tensor. Data types supported: same as @p input
* @param[in] output Destination tensor. Data types supported: same as @p input
* @param[in] sum Sum of 1D logits tensor. Data types supported: same as @p input
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const ITensorInfo *sum);
/** Checks if the given size is eligible for parallel reduction
*
* @note Serial reduction is launched for width < (_grid_size * _serial_vector_size).
* @note Parallel reduction is launched for width >= (_grid_size * _serial_vector_size) and vector_size is forced to 4.
*
* @param[in] size Size to check
*
* @return A two-element tuple where the first element is a boolean specifying if a parallel reduction will be run,
* while the second element is the vector size of the execution.
*/
static ParallelReductionInfo is_parallel_reduction(size_t size);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
private:
const ICLTensor *_input;
ICLTensor *_max;
ICLTensor *_output;
ICLTensor *_sum;
private:
static const unsigned int _grid_size;
static const unsigned int _serial_vector_size;
static const unsigned int _parallel_vector_size;
};
/** Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits. */
class CLLogits1DNormKernel : public ICLKernel
{
public:
/** Default constructor */
CLLogits1DNormKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLLogits1DNormKernel(const CLLogits1DNormKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLLogits1DNormKernel &operator=(const CLLogits1DNormKernel &) = delete;
/** Allow instances of this class to be moved */
CLLogits1DNormKernel(CLLogits1DNormKernel &&) = default;
/** Allow instances of this class to be moved */
CLLogits1DNormKernel &operator=(CLLogits1DNormKernel &&) = default;
/** Set the input and output tensors.
*
* @param[in] input Source tensor. Data types supported: S32/F16/F32
* @param[in] sum Sum tensor. Dimensions should be dim(input)-1. Data types supported: same as @p input
* @param[out] output Destination tensor. Data types supported: QASYMM8 for S32 @p input, or same as @p input
* @param[in] info Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
*/
void configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, const SoftmaxKernelInfo &info);
/** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DNormKernel
*
* @param[in] input Source tensor. Data types supported: S32/F16/F32
* @param[in] sum Sum tensor. Dimensions should be dim(input)-1. Data types supported: same as @p input
* @param[in] output Destination tensor. Data types supported: QASYMM8 for S32 @p input, or same as @p input
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
private:
const ICLTensor *_input;
const ICLTensor *_sum;
ICLTensor *_output;
};
} // namespace arm_compute
#endif /*ARM_COMPUTE_CLSOFTMAXLAYERKERNEL_H */
|
