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 --- ...on_space_to_batch_nd_workload_8cpp_source.xhtml | 138 +++++++++++++++++++++ 1 file changed, 138 insertions(+) create mode 100644 20.02/_neon_space_to_batch_nd_workload_8cpp_source.xhtml (limited to '20.02/_neon_space_to_batch_nd_workload_8cpp_source.xhtml') diff --git a/20.02/_neon_space_to_batch_nd_workload_8cpp_source.xhtml b/20.02/_neon_space_to_batch_nd_workload_8cpp_source.xhtml new file mode 100644 index 0000000000..579a53fcd6 --- /dev/null +++ b/20.02/_neon_space_to_batch_nd_workload_8cpp_source.xhtml @@ -0,0 +1,138 @@ + + + + + + + + + + + + + +ArmNN: src/backends/neon/workloads/NeonSpaceToBatchNdWorkload.cpp Source File + + + + + + + + + + + + + + + + +
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NeonSpaceToBatchNdWorkload.cpp
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+Go to the documentation of this file.
1 //
2 // Copyright © 2020 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "NeonSpaceToBatchNdWorkload.hpp"
7 
8 #include "NeonWorkloadUtils.hpp"
9 #include <ResolveType.hpp>
10 
11 namespace armnn
12 {
13 
14 using namespace armcomputetensorutils;
15 
16 arm_compute::Status NeonSpaceToBatchNdWorkloadValidate(const TensorInfo& input,
17  const TensorInfo& output,
18  const SpaceToBatchNdDescriptor& descriptor)
19 {
20  const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
21  const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
22 
23  // ArmNN blockShape is [H, W] Cl asks for W, H
24  int32_t blockHeight = boost::numeric_cast<int32_t>(descriptor.m_BlockShape[0]);
25  int32_t blockWidth = boost::numeric_cast<int32_t>(descriptor.m_BlockShape[1]);
26 
27  arm_compute::Size2D paddingLeftTop = BuildArmComputeSize2D(
28  descriptor.m_PadList[1].first, descriptor.m_PadList[0].first);
29  arm_compute::Size2D paddingRightBottom = BuildArmComputeSize2D(
30  descriptor.m_PadList[1].second, descriptor.m_PadList[0].second);
31 
32  return arm_compute::NESpaceToBatchLayer::validate(&aclInputInfo,
33  blockWidth,
34  blockHeight,
35  paddingLeftTop,
36  paddingRightBottom,
37  &aclOutputInfo);
38 }
39 
40 NeonSpaceToBatchNdWorkload::NeonSpaceToBatchNdWorkload(const SpaceToBatchNdQueueDescriptor& desc,
41  const WorkloadInfo& info)
42  : BaseWorkload<SpaceToBatchNdQueueDescriptor>(desc, info)
43 {
44  m_Data.ValidateInputsOutputs("NESpaceToBatchNdWorkload", 1, 1);
45 
46  arm_compute::ITensor& input =
47  boost::polymorphic_pointer_downcast<IAclTensorHandle>(m_Data.m_Inputs[0])->GetTensor();
48  arm_compute::ITensor& output =
49  boost::polymorphic_pointer_downcast<IAclTensorHandle>(m_Data.m_Outputs[0])->GetTensor();
50 
51  // ArmNN blockShape is [H, W] Cl asks for W, H
52  int32_t blockHeight = boost::numeric_cast<int32_t>(m_Data.m_Parameters.m_BlockShape[0]);
53  int32_t blockWidth = boost::numeric_cast<int32_t>(m_Data.m_Parameters.m_BlockShape[1]);
54 
55  arm_compute::Size2D paddingLeftTop = BuildArmComputeSize2D(
56  m_Data.m_Parameters.m_PadList[1].first, m_Data.m_Parameters.m_PadList[0].first);
57  arm_compute::Size2D paddingRightBottom = BuildArmComputeSize2D(
58  m_Data.m_Parameters.m_PadList[1].second, m_Data.m_Parameters.m_PadList[0].second);
59 
60  arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
61  input.info()->set_data_layout(aclDataLayout);
62  output.info()->set_data_layout(aclDataLayout);
63 
64  m_Layer.reset(new arm_compute::NESpaceToBatchLayer());
65  m_Layer->configure(&input,
66  blockWidth,
67  blockHeight,
68  paddingLeftTop,
69  paddingRightBottom,
70  &output);
71  m_Layer->prepare();
72 }
73 
74 void NeonSpaceToBatchNdWorkload::Execute() const
75 {
76  if (m_Layer)
77  {
78  ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSpaceToBatchNdWorkload_Execute");
79  m_Layer->run();
80  }
81 }
82 
83 } //namespace armnn
armnn::DataLayout
DataLayout
Definition: Types.hpp:49
+ +
armnn::BaseWorkload< SpaceToBatchNdQueueDescriptor >::m_Data
const SpaceToBatchNdQueueDescriptor m_Data
Definition: Workload.hpp:46
+
ARMNN_SCOPED_PROFILING_EVENT_NEON
#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name)
Definition: NeonWorkloadUtils.hpp:17
+
ResolveType.hpp
+
NeonSpaceToBatchNdWorkload.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::SpaceToBatchNdDescriptor::m_PadList
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}.
Definition: Descriptors.hpp:804
+ +
armnn::SpaceToBatchNdDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:806
+
armnn::NeonSpaceToBatchNdWorkloadValidate
arm_compute::Status NeonSpaceToBatchNdWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const SpaceToBatchNdDescriptor &descriptor)
Definition: NeonSpaceToBatchNdWorkload.cpp:16
+ + +
armnn::NeonSpaceToBatchNdWorkload::NeonSpaceToBatchNdWorkload
NeonSpaceToBatchNdWorkload(const SpaceToBatchNdQueueDescriptor &descriptor, const WorkloadInfo &info)
Definition: NeonSpaceToBatchNdWorkload.cpp:40
+
armnn::Status
Status
enumeration
Definition: Types.hpp:26
+
NeonWorkloadUtils.hpp
+
armnn::numeric_cast
std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)
Definition: NumericCast.hpp:33
+
armnn::SpaceToBatchNdDescriptor::m_BlockShape
std::vector< unsigned int > m_BlockShape
Block shape value.
Definition: Descriptors.hpp:801
+
armnn::SpaceToBatchNdDescriptor
A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer.
Definition: Descriptors.hpp:778
+
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
+
+
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