From 6940dd720ebb6b3d1df8ca203ab696daefe58189 Mon Sep 17 00:00:00 2001 From: Jim Flynn Date: Fri, 20 Mar 2020 12:25:56 +0000 Subject: renamed Documentation folder 20.02 and added .nojekyll file Signed-off-by: Jim Flynn --- ..._batch_normalization_workload_8cpp_source.xhtml | 132 +++++++++++++++++++++ 1 file changed, 132 insertions(+) create mode 100644 20.02/_ref_batch_normalization_workload_8cpp_source.xhtml (limited to '20.02/_ref_batch_normalization_workload_8cpp_source.xhtml') diff --git a/20.02/_ref_batch_normalization_workload_8cpp_source.xhtml b/20.02/_ref_batch_normalization_workload_8cpp_source.xhtml new file mode 100644 index 0000000000..84f5dcc30d --- /dev/null +++ b/20.02/_ref_batch_normalization_workload_8cpp_source.xhtml @@ -0,0 +1,132 @@ + + + + + + + + + + + + + +ArmNN: src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp Source File + + + + + + + + + + + + + + + + +
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RefBatchNormalizationWorkload.cpp
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+Go to the documentation of this file.
1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "RefBatchNormalizationWorkload.hpp"
7 
8 #include "BatchNormImpl.hpp"
9 #include "RefWorkloadUtils.hpp"
10 
11 #include "Profiling.hpp"
12 
13 namespace armnn
14 {
15 
16 RefBatchNormalizationWorkload::RefBatchNormalizationWorkload(const BatchNormalizationQueueDescriptor& descriptor,
17  const WorkloadInfo& info)
18  : BaseWorkload(descriptor, info)
19  , m_Mean (std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Mean)))
20  , m_Variance(std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Variance)))
21  , m_Beta (std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Beta)))
22  , m_Gamma (std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Gamma)))
23 {}
24 
25 void RefBatchNormalizationWorkload::Execute() const
26 {
27  ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefBatchNormalizationWorkload_Execute");
28 
29  std::unique_ptr<Decoder<float>> meanDecoder = MakeDecoder<float>(m_Mean->GetTensorInfo(),
30  m_Mean->Map(true));
31  std::unique_ptr<Decoder<float>> varianceDecoder = MakeDecoder<float>(m_Variance->GetTensorInfo(),
32  m_Variance->Map(true));
33  std::unique_ptr<Decoder<float>> gammaDecoder = MakeDecoder<float>(m_Gamma->GetTensorInfo(),
34  m_Gamma->Map(true));
35  std::unique_ptr<Decoder<float>> betaDecoder = MakeDecoder<float>(m_Beta->GetTensorInfo(),
36  m_Beta->Map(true));
37  std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(m_Data.m_Inputs[0]),
38  m_Data.m_Inputs[0]->Map());
39  std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(m_Data.m_Outputs[0]),
40  m_Data.m_Outputs[0]->Map());
41 
42  BatchNormImpl(m_Data, *meanDecoder, *varianceDecoder, *betaDecoder, *gammaDecoder, *inputDecoder, *outputEncoder);
43 }
44 
45 } // namespace armnn
armnn::RefBatchNormalizationWorkload::RefBatchNormalizationWorkload
RefBatchNormalizationWorkload(const BatchNormalizationQueueDescriptor &descriptor, const WorkloadInfo &info)
Definition: RefBatchNormalizationWorkload.cpp:16
+
armnn::Compute::CpuRef
CPU Execution: Reference C++ kernels.
+
RefWorkloadUtils.hpp
+
armnn::BaseWorkload< BatchNormalizationQueueDescriptor >::m_Data
const BatchNormalizationQueueDescriptor m_Data
Definition: Workload.hpp:46
+
armnn::BatchNormImpl
void BatchNormImpl(const BatchNormalizationQueueDescriptor &data, Decoder< float > &meanDecoder, Decoder< float > &varianceDecoder, Decoder< float > &betaDecoder, Decoder< float > &gammaDecoder, Decoder< float > &inputDecoder, Encoder< float > &outputEncoder)
Definition: BatchNormImpl.cpp:18
+
armnn::GetTensorInfo
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
Definition: RefWorkloadUtils.hpp:25
+
RefBatchNormalizationWorkload.hpp
+
armnn
Copyright (c) 2020 ARM Limited.
Definition: 00_introduction.dox:25
+
ARMNN_SCOPED_PROFILING_EVENT
#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)
Definition: Profiling.hpp:169
+ + + +
BatchNormImpl.hpp
+ +
armnn::QueueDescriptor::m_Outputs
std::vector< ITensorHandle * > m_Outputs
Definition: WorkloadData.hpp:31
+ +
armnn::WorkloadInfo
Contains information about inputs and outputs to a layer.
Definition: WorkloadInfo.hpp:16
+
armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:30
+
Profiling.hpp
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+
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