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 --- ..._normalization_float_workload_8cpp_source.xhtml | 142 +++++++++++++++++++++ 1 file changed, 142 insertions(+) create mode 100644 20.02/_cl_batch_normalization_float_workload_8cpp_source.xhtml (limited to '20.02/_cl_batch_normalization_float_workload_8cpp_source.xhtml') diff --git a/20.02/_cl_batch_normalization_float_workload_8cpp_source.xhtml b/20.02/_cl_batch_normalization_float_workload_8cpp_source.xhtml new file mode 100644 index 0000000000..8b77690f29 --- /dev/null +++ b/20.02/_cl_batch_normalization_float_workload_8cpp_source.xhtml @@ -0,0 +1,142 @@ + + + + + + + + + + + + + +ArmNN: src/backends/cl/workloads/ClBatchNormalizationFloatWorkload.cpp Source File + + + + + + + + + + + + + + + + +
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ClBatchNormalizationFloatWorkload.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 "ClBatchNormalizationFloatWorkload.hpp"
7 #include <cl/ClTensorHandle.hpp>
8 #include <backendsCommon/CpuTensorHandle.hpp>
9 #include <aclCommon/ArmComputeTensorUtils.hpp>
10 #include <cl/ClLayerSupport.hpp>
11 
12 #include "ClWorkloadUtils.hpp"
13 
14 namespace armnn
15 {
16 using namespace armcomputetensorutils;
17 
18 arm_compute::Status ClBatchNormalizationValidate(const TensorInfo& input,
19  const TensorInfo& output,
20  const TensorInfo& mean,
21  const TensorInfo& var,
22  const TensorInfo& beta,
23  const TensorInfo& gamma,
24  const BatchNormalizationDescriptor &desc)
25 {
26  const arm_compute::TensorInfo aclInputInfo =
27  armcomputetensorutils::BuildArmComputeTensorInfo(input, desc.m_DataLayout);
28  const arm_compute::TensorInfo aclOutputInfo =
29  armcomputetensorutils::BuildArmComputeTensorInfo(output, desc.m_DataLayout);
30  const arm_compute::TensorInfo aclMeanInfo =
31  armcomputetensorutils::BuildArmComputeTensorInfo(mean, desc.m_DataLayout);
32  const arm_compute::TensorInfo aclVarInfo =
33  armcomputetensorutils::BuildArmComputeTensorInfo(var, desc.m_DataLayout);
34  const arm_compute::TensorInfo aclBetaInfo =
35  armcomputetensorutils::BuildArmComputeTensorInfo(beta, desc.m_DataLayout);
36  const arm_compute::TensorInfo aclGammaInfo =
37  armcomputetensorutils::BuildArmComputeTensorInfo(gamma, desc.m_DataLayout);
38 
39  return arm_compute::CLBatchNormalizationLayer::validate(&aclInputInfo,
40  &aclOutputInfo,
41  &aclMeanInfo,
42  &aclVarInfo,
43  &aclBetaInfo,
44  &aclGammaInfo,
45  desc.m_Eps);
46 }
47 
48 ClBatchNormalizationFloatWorkload::ClBatchNormalizationFloatWorkload(
49  const BatchNormalizationQueueDescriptor& descriptor, const WorkloadInfo& info)
50  : FloatWorkload<BatchNormalizationQueueDescriptor>(descriptor, info)
51 {
52  m_Mean = std::make_unique<arm_compute::CLTensor>();
53  BuildArmComputeTensor(*m_Mean, m_Data.m_Mean->GetTensorInfo());
54 
55  m_Variance = std::make_unique<arm_compute::CLTensor>();
56  BuildArmComputeTensor(*m_Variance, m_Data.m_Variance->GetTensorInfo());
57 
58  m_Gamma = std::make_unique<arm_compute::CLTensor>();
59  BuildArmComputeTensor(*m_Gamma, m_Data.m_Gamma->GetTensorInfo());
60 
61  m_Beta = std::make_unique<arm_compute::CLTensor>();
62  BuildArmComputeTensor(*m_Beta, m_Data.m_Beta->GetTensorInfo());
63 
64  m_Data.ValidateInputsOutputs("ClBatchNormalizationFloatWorkload", 1, 1);
65 
66  arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
67  arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
68 
69  arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
70  input.info()->set_data_layout(aclDataLayout);
71  output.info()->set_data_layout(aclDataLayout);
72 
73  m_Layer.configure(&input,
74  &output,
75  m_Mean.get(),
76  m_Variance.get(),
77  m_Beta.get(),
78  m_Gamma.get(),
79  m_Data.m_Parameters.m_Eps);
80 
81  InitializeArmComputeClTensorData(*m_Mean, m_Data.m_Mean);
82  InitializeArmComputeClTensorData(*m_Variance, m_Data.m_Variance);
83  InitializeArmComputeClTensorData(*m_Beta, m_Data.m_Beta);
84  InitializeArmComputeClTensorData(*m_Gamma, m_Data.m_Gamma);
85 
86  // Force Compute Library to perform the necessary copying and reshaping, after which
87  // delete all the input tensors that will no longer be needed
88  m_Layer.prepare();
89  FreeUnusedTensors();
90 }
91 
92 void ClBatchNormalizationFloatWorkload::Execute() const
93 {
94  ARMNN_SCOPED_PROFILING_EVENT_CL("ClBatchNormalizationFloatWorkload_Execute");
95  RunClFunction(m_Layer, CHECK_LOCATION());
96 }
97 
98 void ClBatchNormalizationFloatWorkload::FreeUnusedTensors()
99 {
100  FreeTensorIfUnused(m_Mean);
101  FreeTensorIfUnused(m_Variance);
102  FreeTensorIfUnused(m_Gamma);
103  FreeTensorIfUnused(m_Beta);
104 }
105 
106 } //namespace armnn
ClBatchNormalizationFloatWorkload.hpp
+
armnn::ClBatchNormalizationValidate
arm_compute::Status ClBatchNormalizationValidate(const TensorInfo &input, const TensorInfo &output, const TensorInfo &mean, const TensorInfo &var, const TensorInfo &beta, const TensorInfo &gamma, const BatchNormalizationDescriptor &desc)
Definition: ClBatchNormalizationFloatWorkload.cpp:18
+
armnn::DataLayout
DataLayout
Definition: Types.hpp:49
+
armnn::InitializeArmComputeClTensorData
void InitializeArmComputeClTensorData(arm_compute::CLTensor &clTensor, const ConstCpuTensorHandle *handle)
Definition: ClWorkloadUtils.hpp:90
+ +
ARMNN_SCOPED_PROFILING_EVENT_CL
#define ARMNN_SCOPED_PROFILING_EVENT_CL(name)
Definition: ClWorkloadUtils.hpp:20
+
armnn::RunClFunction
void RunClFunction(arm_compute::IFunction &function, const CheckLocation &location)
Definition: ClWorkloadUtils.hpp:131
+
armnn::BaseWorkload::m_Data
const QueueDescriptor m_Data
Definition: Workload.hpp:46
+
armnn::BatchNormalizationDescriptor::m_Eps
float m_Eps
Value to add to the variance. Used to avoid dividing by zero.
Definition: Descriptors.hpp:623
+
armnn::BatchNormalizationDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:625
+
ArmComputeTensorUtils.hpp
+
armnn::QueueDescriptor::ValidateInputsOutputs
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Definition: WorkloadData.cpp:461
+
armnn
Copyright (c) 2020 ARM Limited.
Definition: 00_introduction.dox:25
+
armnn::ClBatchNormalizationFloatWorkload::ClBatchNormalizationFloatWorkload
ClBatchNormalizationFloatWorkload(const BatchNormalizationQueueDescriptor &descriptor, const WorkloadInfo &info)
Definition: ClBatchNormalizationFloatWorkload.cpp:48
+
armnn::Status
Status
enumeration
Definition: Types.hpp:26
+ +
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:192
+
CpuTensorHandle.hpp
+
ClTensorHandle.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
+
ClWorkloadUtils.hpp
+
armnn::BatchNormalizationDescriptor
A BatchNormalizationDescriptor for the BatchNormalizationLayer.
Definition: Descriptors.hpp:610
+
ClLayerSupport.hpp
+
+
+ + + + -- cgit v1.2.1