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
|
//
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonL2NormalizationFloatWorkload.hpp"
#include "NeonWorkloadUtils.hpp"
#include <aclCommon/ArmComputeUtils.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <arm_compute/runtime/NEON/functions/NEL2NormalizeLayer.h>
namespace armnn
{
using namespace armcomputetensorutils;
arm_compute::Status NeonL2NormalizationWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const L2NormalizationDescriptor& descriptor)
{
const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
int axis = (descriptor.m_DataLayout == DataLayout::NCHW) ? 2 : 0;
return arm_compute::NEL2NormalizeLayer::validate(&aclInput, &aclOutput, axis, descriptor.m_Eps);
}
NeonL2NormalizationFloatWorkload::NeonL2NormalizationFloatWorkload(const L2NormalizationQueueDescriptor& descriptor,
const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
: FloatWorkload<L2NormalizationQueueDescriptor>(descriptor, info)
{
// Report Profiling Details
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonL2NormalizationFloatWorkload_Construct",
descriptor.m_Parameters,
info,
this->GetGuid());
m_Data.ValidateInputsOutputs("NeonL2NormalizationFloatWorkload", 1, 1);
arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(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);
int axis = (m_Data.m_Parameters.m_DataLayout == DataLayout::NCHW) ? 2 : 0;
auto layer = std::make_unique<arm_compute::NEL2NormalizeLayer>(memoryManager);
layer->configure(&input, &output, axis, m_Data.m_Parameters.m_Eps);
m_Layer.reset(layer.release());
}
void NeonL2NormalizationFloatWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonL2NormalizationFloatWorkload_Execute", this->GetGuid());
m_Layer->run();
}
} //namespace armnn
|
