patch/23.02/_neon_strided_slice_workload_8cpp_source.xhtml

 //
 // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //

 #include "NeonStridedSliceWorkload.hpp"

 #include "NeonWorkloadUtils.hpp"
 #include <neon/NeonTensorHandle.hpp>
 #include <aclCommon/ArmComputeUtils.hpp>
 #include <aclCommon/ArmComputeTensorUtils.hpp>
 #include <armnn/utility/NumericCast.hpp>
 #include <armnn/utility/PolymorphicDowncast.hpp>
 #include <backendsCommon/WorkloadUtils.hpp>

 namespace armnn
 {

 arm_compute::Status NeonStridedSliceWorkloadValidate(const TensorInfo& input,
                                                      const TensorInfo& output,
                                                      const StridedSliceDescriptor& descriptor)
 {
     const arm_compute::TensorInfo aclInput = armcomputetensorutils::BuildArmComputeTensorInfo(input);
     const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);

     arm_compute::Coordinates starts;
     arm_compute::Coordinates ends;
     arm_compute::Coordinates strides;

     std::tie(starts, ends, strides) = SetNeonStridedSliceData(descriptor.m_Begin,
                                                               descriptor.m_End,
                                                               descriptor.m_Stride);

     auto numDimensions       = armnn::numeric_cast<int>(input.GetNumDimensions());
     int32_t begin_mask       = ConvertMaskToACLFormat(descriptor.m_BeginMask, numDimensions);
     int32_t end_mask         = ConvertMaskToACLFormat(descriptor.m_EndMask, numDimensions);
     int32_t shrink_axis_mask = ConvertMaskToACLFormat(descriptor.m_ShrinkAxisMask, numDimensions);

     return arm_compute::NEStridedSlice::validate(&aclInput,
                                                  &aclOutput,
                                                  starts,
                                                  ends,
                                                  strides,
                                                  begin_mask,
                                                  end_mask,
                                                  shrink_axis_mask);
 }

 NeonStridedSliceWorkload::NeonStridedSliceWorkload(const StridedSliceQueueDescriptor& descriptor,
                                                    const WorkloadInfo& info)
         : NeonBaseWorkload<StridedSliceQueueDescriptor>(descriptor, info)
 {
     // Report Profiling Details
     ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonStridedSliceWorkload_Construct",
                                          descriptor.m_Parameters,
                                          info,
                                          this->GetGuid());

     m_Data.ValidateInputsOutputs("NeonStridedSliceWorkload", 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::Coordinates starts;
     arm_compute::Coordinates ends;
     arm_compute::Coordinates strides;

     std::tie(starts, ends, strides) = SetNeonStridedSliceData(m_Data.m_Parameters.m_Begin,
                                                               m_Data.m_Parameters.m_End,
                                                               m_Data.m_Parameters.m_Stride);

     auto numDimensions       = armnn::numeric_cast<int>(info.m_InputTensorInfos[0].GetNumDimensions());
     int32_t begin_mask       = ConvertMaskToACLFormat(m_Data.m_Parameters.m_BeginMask, numDimensions);
     int32_t end_mask         = ConvertMaskToACLFormat(m_Data.m_Parameters.m_EndMask, numDimensions);
     int32_t shrink_axis_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_ShrinkAxisMask, numDimensions);

     arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
     input.info()->set_data_layout(aclDataLayout);
     output.info()->set_data_layout(aclDataLayout);

     auto layer = std::make_unique<arm_compute::NEStridedSlice>();

     layer->configure(&input,
                      &output,
                      starts,
                      ends,
                      strides,
                      begin_mask,
                      end_mask,
                      shrink_axis_mask);
     m_Layer.reset(layer.release());
 }

 void NeonStridedSliceWorkload::Execute() const
 {
     ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonStridedSliceWorkload_Execute", this->GetGuid());
     m_Layer->run();
 }

 } //namespace armnn
armnn::DataLayout
DataLayout
Definition: Types.hpp:62

-ArmComputeUtils.hpp

-armnn::StridedSliceDescriptor::m_ShrinkAxisMask
int32_t m_ShrinkAxisMask
Shrink axis mask value. If set, the nth specification shrinks the dimensionality by 1...
Definition: Descriptors.hpp:1302

-armnn::StridedSliceDescriptor::m_Begin
std::vector< int > m_Begin
Begin values for the input that will be sliced.
Definition: Descriptors.hpp:1289

-armnn::TensorInfo
Definition: Tensor.hpp:152

-armnn::StridedSliceDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:1310

-armnn::Coordinates
std::array< unsigned int, MaxNumOfTensorDimensions > Coordinates
Definition: InternalTypes.hpp:15

-armnn::NeonStridedSliceWorkloadValidate
arm_compute::Status NeonStridedSliceWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const StridedSliceDescriptor &descriptor)
Definition: NeonStridedSliceWorkload.cpp:19

-NeonTensorHandle.hpp

-armnn::BaseWorkload< StridedSliceQueueDescriptor >::GetGuid
arm::pipe::ProfilingGuid GetGuid() const final
Definition: Workload.hpp:61

-ArmComputeTensorUtils.hpp

-armnn::QueueDescriptor::ValidateInputsOutputs
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Definition: WorkloadData.cpp:475

-NeonStridedSliceWorkload.hpp

-armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6

-armnn::SetNeonStridedSliceData
auto SetNeonStridedSliceData(const std::vector< int > &m_begin, const std::vector< int > &m_end, const std::vector< int > &m_stride)
Definition: NeonWorkloadUtils.hpp:131

-armnn::StridedSliceDescriptor::m_BeginMask
int32_t m_BeginMask
Begin mask value.
Definition: Descriptors.hpp:1297

-armnn::StridedSliceDescriptor::m_EndMask
int32_t m_EndMask
End mask value.
Definition: Descriptors.hpp:1300

-armnn::QueueDescriptorWithParameters::m_Parameters
LayerDescriptor m_Parameters
Definition: WorkloadData.hpp:66

-NumericCast.hpp

-PolymorphicDowncast.hpp

-armnn::NeonBaseWorkload
Definition: NeonBaseWorkload.hpp:13

-armnn::NeonStridedSliceWorkload::Execute
virtual void Execute() const override
Definition: NeonStridedSliceWorkload.cpp:94

-armnn::WorkloadInfo::m_InputTensorInfos
std::vector< TensorInfo > m_InputTensorInfos
Definition: WorkloadInfo.hpp:18

-armnn::BaseWorkload< StridedSliceQueueDescriptor >::m_Data
StridedSliceQueueDescriptor m_Data
Definition: Workload.hpp:83

-armnn::Status
Status
enumeration
Definition: Types.hpp:42

-NeonWorkloadUtils.hpp

-armnn::StridedSliceDescriptor::m_Stride
std::vector< int > m_Stride
Stride values for the input that will be sliced.
Definition: Descriptors.hpp:1293

-armnn::StridedSliceDescriptor::m_End
std::vector< int > m_End
End values for the input that will be sliced.
Definition: Descriptors.hpp:1291

-armnn::ConvertMaskToACLFormat
int32_t ConvertMaskToACLFormat(int32_t mask, int32_t numDim)
Definition: WorkloadUtils.cpp:286

-armnn::QueueDescriptor::m_Outputs
std::vector< ITensorHandle * > m_Outputs
Definition: WorkloadData.hpp:27

-armnn::StridedSliceQueueDescriptor
Definition: WorkloadData.hpp:462

-ARMNN_REPORT_PROFILING_WORKLOAD_DESC
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
Definition: Profiling.hpp:227

-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:35

-armnn::StridedSliceDescriptor
A StridedSliceDescriptor for the StridedSliceLayer.
Definition: Descriptors.hpp:1250

-armnn::WorkloadInfo
Contains information about TensorInfos of a layer.
Definition: WorkloadInfo.hpp:16

-armnn::NeonStridedSliceWorkload::NeonStridedSliceWorkload
NeonStridedSliceWorkload(const StridedSliceQueueDescriptor &descriptor, const WorkloadInfo &info)
Definition: NeonStridedSliceWorkload.cpp:49

-armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:26

-ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID
#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)
Definition: NeonWorkloadUtils.hpp:24

-armnn::TensorInfo::GetNumDimensions
unsigned int GetNumDimensions() const
Definition: Tensor.hpp:195

-WorkloadUtils.hpp

+Go to the documentation of this file. //

+ // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.

+ // SPDX-License-Identifier: MIT

+ //

+

+ #include "NeonStridedSliceWorkload.hpp"

+

+ #include "NeonWorkloadUtils.hpp"

+ #include <neon/NeonTensorHandle.hpp>

+ #include <aclCommon/ArmComputeUtils.hpp>

+ #include <aclCommon/ArmComputeTensorUtils.hpp>

+ #include <armnn/utility/NumericCast.hpp>

+ #include <armnn/utility/PolymorphicDowncast.hpp>

+ #include <backendsCommon/WorkloadUtils.hpp>

+

+ namespace armnn

+ {

+

+ arm_compute::Status NeonStridedSliceWorkloadValidate(const TensorInfo& input,

+                                                      const TensorInfo& output,

+                                                      const StridedSliceDescriptor& descriptor)

+ {

+     const arm_compute::TensorInfo aclInput = armcomputetensorutils::BuildArmComputeTensorInfo(input);

+     const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);

+

+     arm_compute::Coordinates starts;

+     arm_compute::Coordinates ends;

+     arm_compute::Coordinates strides;

+

+     std::tie(starts, ends, strides) = SetNeonStridedSliceData(descriptor.m_Begin,

+                                                               descriptor.m_End,

+                                                               descriptor.m_Stride);

+

+     auto numDimensions       = armnn::numeric_cast<int>(input.GetNumDimensions());

+     int32_t begin_mask       = ConvertMaskToACLFormat(descriptor.m_BeginMask, numDimensions);

+     int32_t end_mask         = ConvertMaskToACLFormat(descriptor.m_EndMask, numDimensions);

+     int32_t shrink_axis_mask = ConvertMaskToACLFormat(descriptor.m_ShrinkAxisMask, numDimensions);

+

+     return arm_compute::NEStridedSlice::validate(&aclInput,

+                                                  &aclOutput,

+                                                  starts,

+                                                  ends,

+                                                  strides,

+                                                  begin_mask,

+                                                  end_mask,

+                                                  shrink_axis_mask);

+ }

+

+ NeonStridedSliceWorkload::NeonStridedSliceWorkload(const StridedSliceQueueDescriptor& descriptor,

+                                                    const WorkloadInfo& info)

+         : NeonBaseWorkload<StridedSliceQueueDescriptor>(descriptor, info)

+ {

+     // Report Profiling Details

+     ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonStridedSliceWorkload_Construct",

+                                          descriptor.m_Parameters,

+                                          info,

+                                          this->GetGuid());

+

+     m_Data.ValidateInputsOutputs("NeonStridedSliceWorkload", 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::Coordinates starts;

+     arm_compute::Coordinates ends;

+     arm_compute::Coordinates strides;

+

+     std::tie(starts, ends, strides) = SetNeonStridedSliceData(m_Data.m_Parameters.m_Begin,

+                                                               m_Data.m_Parameters.m_End,

+                                                               m_Data.m_Parameters.m_Stride);

+

+     auto numDimensions       = armnn::numeric_cast<int>(info.m_InputTensorInfos[0].GetNumDimensions());

+     int32_t begin_mask       = ConvertMaskToACLFormat(m_Data.m_Parameters.m_BeginMask, numDimensions);

+     int32_t end_mask         = ConvertMaskToACLFormat(m_Data.m_Parameters.m_EndMask, numDimensions);

+     int32_t shrink_axis_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_ShrinkAxisMask, numDimensions);

+

+     arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);

+     input.info()->set_data_layout(aclDataLayout);

+     output.info()->set_data_layout(aclDataLayout);

+

+     auto layer = std::make_unique<arm_compute::NEStridedSlice>();

+

+     layer->configure(&input,

+                      &output,

+                      starts,

+                      ends,

+                      strides,

+                      begin_mask,

+                      end_mask,

+                      shrink_axis_mask);

+     m_Layer.reset(layer.release());

+ }

+

+ void NeonStridedSliceWorkload::Execute() const

+ {

+     ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonStridedSliceWorkload_Execute", this->GetGuid());

+     m_Layer->run();

+ }

+

+ } //namespace armnn