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//
// Copyright © 2017, 2019-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClBatchToSpaceNdWorkload.hpp"
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <cl/ClTensorHandle.hpp>
namespace armnn
{
using namespace armcomputetensorutils;
arm_compute::Status ClBatchToSpaceNdWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const BatchToSpaceNdDescriptor& descriptor)
{
arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
arm_compute::Status statusBatchToSpace = arm_compute::Status(arm_compute::ErrorCode::OK);
arm_compute::Status statusReshapeInput = arm_compute::Status(arm_compute::ErrorCode::OK);
arm_compute::Status statusReshapeOutput = arm_compute::Status(arm_compute::ErrorCode::OK);
arm_compute::TensorInfo aclReshapeInputInfo = aclInputInfo;
arm_compute::TensorInfo aclReshapeOutputInfo = aclOutputInfo;
// When a spacial dimension is missing (rank=3) set W to 1
const unsigned int rank = input.GetNumDimensions();
if (rank == 3)
{
const arm_compute::TensorShape inputShape = aclInputInfo.tensor_shape();
const arm_compute::TensorShape outputShape = aclOutputInfo.tensor_shape();
if (descriptor.m_DataLayout == armnn::DataLayout::NHWC)
{
// In ACL dimensions are right to left: C, W, H, N
aclInputInfo.set_tensor_shape({inputShape.x(), 1, inputShape.y(), inputShape.z()});
aclOutputInfo.set_tensor_shape({outputShape.x(), 1, outputShape.y(), outputShape.z()});
}
else if (descriptor.m_DataLayout == armnn::DataLayout::NCHW)
{
// In ACL dimensions are right to left: W, H, C, N
aclInputInfo.set_tensor_shape({1, inputShape.x(), inputShape.y(), inputShape.z()});
aclOutputInfo.set_tensor_shape({1, outputShape.x(), outputShape.y(), outputShape.z()});
}
else
{
throw InvalidArgumentException("Unsupported or unknown DataLayout", CHECK_LOCATION());
}
statusReshapeInput = arm_compute::CLReshapeLayer::validate(&aclInputInfo, &aclReshapeInputInfo);
statusReshapeOutput = arm_compute::CLReshapeLayer::validate(&aclReshapeOutputInfo, &aclOutputInfo);
}
// ArmNN blockShape is [H, W] ACl asks for W, H
int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[0]);
int32_t blockWidth = (rank == 3) ? 1 : armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[1]);
const arm_compute::CropInfo cropInfo = BuildArmComputeCropInfo(descriptor, rank);
statusBatchToSpace = arm_compute::CLBatchToSpaceLayer::validate(rank == 3 ? &aclReshapeInputInfo : &aclInputInfo,
blockWidth,
blockHeight,
rank == 3 ? &aclReshapeOutputInfo : &aclOutputInfo,
cropInfo);
if (statusReshapeInput.error_code() == arm_compute::ErrorCode::OK &&
statusReshapeOutput.error_code() == arm_compute::ErrorCode::OK &&
statusBatchToSpace.error_code() == arm_compute::ErrorCode::OK)
{
return arm_compute::Status(arm_compute::ErrorCode::OK,
"All BatchToSpace layers validate status OK.");
}
else
{
return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR,
"BatchToSpace layer validate status failed."
+ statusBatchToSpace.error_description()
+ statusReshapeInput.error_description()
+ statusReshapeOutput.error_description());
}
}
ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDescriptor& descriptor,
const WorkloadInfo& info,
const arm_compute::CLCompileContext& clCompileContext)
: ClBaseWorkload<BatchToSpaceNdQueueDescriptor>(descriptor, info)
{
// Report Profiling Details
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClBatchToSpaceWorkload_Construct",
descriptor.m_Parameters,
info,
this->GetGuid());
m_Data.ValidateInputsOutputs("ClBatchToSpaceNdWorkload", 1, 1);
arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(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);
arm_compute::TensorInfo aclReshapeInputInfo = BuildArmComputeTensorInfo(info.m_InputTensorInfos[0],
m_Data.m_Parameters.m_DataLayout);
arm_compute::TensorInfo aclReshapeOutputInfo = BuildArmComputeTensorInfo(info.m_OutputTensorInfos[0],
m_Data.m_Parameters.m_DataLayout);
const unsigned int rank = info.m_InputTensorInfos[0].GetNumDimensions();
if (rank == 3)
{
const arm_compute::TensorShape inputShape = input.info()->tensor_shape();
const arm_compute::TensorShape outputShape = output.info()->tensor_shape();
// When a spacial dimension is missing set W to 1
if (m_Data.m_Parameters.m_DataLayout == armnn::DataLayout::NHWC)
{
// In ACL dimensions are right to left: C, W, H, N
aclReshapeInputInfo.set_tensor_shape({inputShape.x(), 1, inputShape.y(), inputShape.z()});
aclReshapeOutputInfo.set_tensor_shape({outputShape.x(), 1, outputShape.y(), outputShape.z()});
}
else if (m_Data.m_Parameters.m_DataLayout == armnn::DataLayout::NCHW)
{
// In ACL dimensions are right to left: W, H, C, N
aclReshapeInputInfo.set_tensor_shape({1, inputShape.x(), inputShape.y(), inputShape.z()});
aclReshapeOutputInfo.set_tensor_shape({1, outputShape.x(), outputShape.y(), outputShape.z()});
}
else
{
throw InvalidArgumentException("Unsupported or unknown DataLayout", CHECK_LOCATION());
}
m_ReshapeInputTensor.allocator()->init(aclReshapeInputInfo);
m_ReshapeOutputTensor.allocator()->init(aclReshapeOutputInfo);
InitialiseArmComputeTensorEmpty(m_ReshapeInputTensor);
InitialiseArmComputeTensorEmpty(m_ReshapeOutputTensor);
m_LayerReshapeInput.reset(new arm_compute::CLReshapeLayer());
m_LayerReshapeOutput.reset(new arm_compute::CLReshapeLayer());
m_LayerReshapeInput->configure(clCompileContext, &input, &m_ReshapeInputTensor);
m_LayerReshapeOutput->configure(clCompileContext, &m_ReshapeOutputTensor, &output);
}
// ArmNN blockShape is [H, W] ACl asks for W, H
int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[0]);
int32_t blockWidth = (rank == 3) ? 1 : armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[1]);
const arm_compute::CropInfo cropInfo = BuildArmComputeCropInfo(descriptor.m_Parameters);
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClBatchToSpaceNdWorkload_configure");
m_Layer.configure(clCompileContext,
(rank == 3) ? &m_ReshapeInputTensor : &input,
blockWidth,
blockHeight,
(rank == 3) ? &m_ReshapeOutputTensor : &output,
cropInfo);
}
}
void ClBatchToSpaceNdWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClBatchToSpaceNdWorkload_Execute", this->GetGuid());
if (m_LayerReshapeInput)
{
m_LayerReshapeInput->run();
}
RunClFunction(m_Layer, CHECK_LOCATION());
if (m_LayerReshapeOutput)
{
m_LayerReshapeOutput->run();
}
}
} //namespace armnn
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