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
|
/*
* Copyright (c) 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_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLMATMUL
#define ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLMATMUL
#include "arm_compute/core/Types.h"
#include "arm_compute/function_info/ActivationLayerInfo.h"
#include "arm_compute/runtime/IFunction.h"
#include <memory>
namespace arm_compute
{
// Forward declarations for used types instead of including their header, that could minimize compile time
class CLCompileContext;
class ICLTensor;
class ITensorInfo;
class MatMulInfo;
class Status;
/** Settings for MatMul OpenCL implementation */
class GpuMatMulSettings
{
public:
/* Placeholder for operator parity between CPU/GPU */
};
/** Basic function to execute MatMul (Matrix Multiplication) on OpenCL */
class CLMatMul : public IFunction
{
public:
/** Default constructor.*/
CLMatMul();
/** Default destructor */
~CLMatMul();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLMatMul(const CLMatMul &) = delete;
/** Default move constructor */
CLMatMul(CLMatMul &&);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLMatMul &operator=(const CLMatMul &) = delete;
/** Default move assignment operator */
CLMatMul &operator=(CLMatMul &&);
/** Initialise the kernel's inputs and output
*
* Valid data layouts:
* - All
*
* Valid data type configurations:
* |lhs |rhs |dst |
* |:--------------|:--------------|:--------------|
* |F32 |F32 |F32 |
* |F16 |F16 |F16 |
* |QASYMM8_SIGNED |QASYMM8_SIGNED |QASYMM8_SIGNED |
* |QASYMM8 |QASYMM8 |QASYMM8 |
*
* @note BatchMatMul: Batched Matrix Multiply - [A * B], Multiplies all slices (slice is an element of a batch) of Tensors A and B
* and stores the result in the dst tensor of the same batch size.
* Batch here is number of slices from A and B multiplied at a time, do not confuse with the batch dimension 'N' of NHWC/NCHW
* For NHWC for example: the batch is the higher dimensions H * N, and in general it is H * all higher dimensions.
* @note All tensors must have the same data type.
*
* @param[in] compile_context The compile context to be used.
* @param[in] lhs Left-hand side tensor info containing the input activations as Matrix A. Data types supported: F16/F32/QASYMM8_SIGNED/QASYMM8.
* @param[in] rhs Right-hand side tensor info containing the input weights as Matrix B. Data types supported: same as @p lhs.
* @param[out] dst Output tensor to store the result of the batched matrix multiplication. Data types supported: same as @p lhs.
* @param[in] matmul_info Contains MatMul operation information described in @ref MatMulInfo.
* @param[in] settings Contains flags for function level settings
* @param[in] act_info (Optional) Contains activation function and lower and upper bound values for bounded activation functions.
*/
void configure(const CLCompileContext &compile_context,
ICLTensor *rhs,
ICLTensor *lhs,
ICLTensor *dst,
const MatMulInfo &matmul_info,
const GpuMatMulSettings &settings = GpuMatMulSettings{},
const ActivationLayerInfo &act_info = ActivationLayerInfo{});
/** Initialise the kernel's inputs and output
*
* Similar to @ref CLMatMul::configure()
*/
void configure(ICLTensor *lhs,
ICLTensor *rhs,
ICLTensor *dst,
const MatMulInfo &matmul_info,
const GpuMatMulSettings &settings = GpuMatMulSettings{},
const ActivationLayerInfo &act_info = ActivationLayerInfo{});
/** Static function to check if given info will lead to a valid configuration of @ref CLMatMul.
*
*
* @note All tensors must have the same data type.
*
* @param[in] lhs Left-hand side (Matrix A) tensor info. Data types supported: F16/F32/QASYMM8_SIGNED/QASYMM8.
* @param[in] rhs Right-hand side (Matrix B) tensor info. Data types supported: same as @p lhs.
* @param[out] output Output tensor info to store the result of the batched matrix multiplication. Data types supported: same as @p lhs.
* @param[in] matmul_info Contains MatMul operation information described in @ref MatMulInfo.
* @param[in] act_info (Optional) Contains activation function and lower and upper bound values for bounded activation functions.
*/
static Status validate(const ITensorInfo *lhs,
const ITensorInfo *rhs,
const ITensorInfo *output,
const MatMulInfo &matmul_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo{});
// Inherited methods overridden:
void run() override;
private:
struct Impl;
std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
#endif /* ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLMATMUL */
|
