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
|
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClConvolution2dWorkload.hpp"
#include "ClWorkloadUtils.hpp"
#include <backends/cl/ClLayerSupport.hpp>
#include <backends/cl/ClTensorHandle.hpp>
#include <backends/cl/ClLayerSupport.hpp>
#include <backends/aclCommon/ArmComputeUtils.hpp>
#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
#include <backends/CpuTensorHandle.hpp>
#include <arm_compute/runtime/CL/functions/CLConvolutionLayer.h>
namespace armnn
{
using namespace armcomputetensorutils;
arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const Convolution2dDescriptor& descriptor,
const TensorInfo& weights,
const Optional<TensorInfo>& biases)
{
const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
arm_compute::TensorInfo aclBiasesInfo;
arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
if (descriptor.m_BiasEnabled)
{
BOOST_ASSERT(biases.has_value());
aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
optionalAclBiasesInfo = &aclBiasesInfo;
}
arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
return arm_compute::CLConvolutionLayer::validate(&aclInputInfo,
&aclWeightsInfo,
optionalAclBiasesInfo,
&aclOutputInfo,
layerInfo);
}
ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescriptor& descriptor,
const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
: BaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
, m_ConvolutionLayer(memoryManager)
{
// todo: check tensor shapes match.
const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);
arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
m_Data.m_Parameters.m_StrideY,
m_Data.m_Parameters.m_PadLeft,
m_Data.m_Parameters.m_PadRight,
m_Data.m_Parameters.m_PadTop,
m_Data.m_Parameters.m_PadBottom,
arm_compute::DimensionRoundingType::FLOOR);
if (m_Data.m_Parameters.m_BiasEnabled)
{
m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
}
m_Data.ValidateInputsOutputs("ClConvolution2dWorkload", 1, 1);
arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
input.info()->set_data_layout(aclDataLayout);
output.info()->set_data_layout(aclDataLayout);
m_ConvolutionLayer.configure(&input,
m_KernelTensor.get(),
m_BiasTensor.get(),
&output,
padStrideInfo);
InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
if (m_BiasTensor)
{
InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
}
// Force Compute Library to perform the necessary copying and reshaping, after which
// delete all the input tensors that will no longer be needed
m_ConvolutionLayer.prepare();
FreeUnusedTensors();
}
void ClConvolution2dWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvolution2dWorkload_Execute");
m_ConvolutionLayer.run();
}
void ClConvolution2dWorkload::FreeUnusedTensors()
{
FreeTensorIfUnused(m_KernelTensor);
FreeTensorIfUnused(m_BiasTensor);
}
} //namespace armnn
|
