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
|
/*
* 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.
*/
#include "src/gpu/cl/operators/ClMatMul.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "src/common/utils/Log.h"
#include "src/gpu/cl/kernels/ClMatMulNativeKernel.h"
#include "src/runtime/heuristics/matmul_native/ClMatMulNativeDefaultConfigValhall.h"
#include "src/runtime/heuristics/matmul_native/ClMatMulNativeKernelConfig.h"
#include "src/runtime/heuristics/matmul_native/IClMatMulNativeKernelConfig.h"
using namespace arm_compute::cl_matmul;
namespace arm_compute
{
namespace opencl
{
using namespace arm_compute::opencl::kernels;
ClMatMul::ClMatMul()
: _matmul_native_kernel(std::make_unique<ClMatMulNativeKernel>()),
_matmul_lowp_native_kernel(std::make_unique<ClMatMulLowpNativeKernel>())
{
}
Status ClMatMul::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulInfo &matmul_info, const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(rhs, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
const GPUTarget gpu_target = CLScheduler::get().target();
std::unique_ptr<IClMatMulNativeKernelConfig> t = ClMatMulNativeKernelConfigurationFactory::create(gpu_target);
const MatMulKernelInfo kernel_info = t->configure(lhs, rhs, matmul_info);
const bool is_quantized = is_data_type_quantized_asymmetric(lhs->data_type());
return is_quantized ? ClMatMulLowpNativeKernel::validate(lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info) :
ClMatMulNativeKernel::validate(lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info);
}
void ClMatMul::configure(const CLCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulInfo &matmul_info, const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst);
ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst, matmul_info);
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, dst, matmul_info));
_is_quantized = is_data_type_quantized_asymmetric(lhs->data_type());
const GPUTarget gpu_target = CLScheduler::get().target();
std::unique_ptr<IClMatMulNativeKernelConfig> t = ClMatMulNativeKernelConfigurationFactory::create(gpu_target);
MatMulKernelInfo kernel_info = t->configure(lhs, rhs, matmul_info);
if(_is_quantized)
{
_matmul_lowp_native_kernel->set_target(gpu_target);
// Configure the low-precision native matrix multiply kernel
_matmul_lowp_native_kernel->configure(compile_context, lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info);
}
else
{
_matmul_native_kernel->set_target(gpu_target);
// Configure the native matrix multiply kernel
_matmul_native_kernel->configure(compile_context, lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info);
}
}
void ClMatMul::run(ITensorPack &tensors)
{
if(_is_quantized)
{
CLScheduler::get().enqueue_op(*_matmul_lowp_native_kernel, tensors, true);
}
else
{
CLScheduler::get().enqueue_op(*_matmul_native_kernel, tensors, true);
}
}
} // namespace opencl
} // namespace arm_compute
|
