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Diffstat (limited to 'src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp')
-rw-r--r-- | src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp | 67 |
1 files changed, 67 insertions, 0 deletions
diff --git a/src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp b/src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp new file mode 100644 index 0000000000..a6e7aa4415 --- /dev/null +++ b/src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp @@ -0,0 +1,67 @@ +// +// Copyright © 2020 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "NeonBatchToSpaceNdWorkload.hpp" + +#include "NeonWorkloadUtils.hpp" +#include <ResolveType.hpp> + +namespace armnn +{ + +using namespace armcomputetensorutils; + +arm_compute::Status NeonBatchToSpaceNdWorkloadValidate(const TensorInfo& input, + const TensorInfo& output, + const BatchToSpaceNdDescriptor& desc) +{ + const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, desc.m_DataLayout); + const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, desc.m_DataLayout); + + // ArmNN blockShape is [H, W] Cl asks for W, H + int32_t blockHeight = boost::numeric_cast<int32_t>(desc.m_BlockShape[0]); + int32_t blockWidth = boost::numeric_cast<int32_t>(desc.m_BlockShape[1]); + + const arm_compute::Status aclStatus = arm_compute::NEBatchToSpaceLayer::validate(&aclInputInfo, + blockWidth, + blockHeight, + &aclOutputInfo); + return aclStatus; +} + +NeonBatchToSpaceNdWorkload::NeonBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDescriptor& desc, + const WorkloadInfo& info) + : BaseWorkload<BatchToSpaceNdQueueDescriptor>(desc, info) +{ + m_Data.ValidateInputsOutputs("NeonBatchToSpaceNdWorkload", 1, 1); + + arm_compute::ITensor& input = + boost::polymorphic_pointer_downcast<IAclTensorHandle>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = + boost::polymorphic_pointer_downcast<IAclTensorHandle>(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); + + // ArmNN blockShape is [H, W] Cl asks for W, H + int32_t blockHeight = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[0]); + int32_t blockWidth = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[1]); + + m_Layer.reset(new arm_compute::NEBatchToSpaceLayer()); + m_Layer->configure(&input, blockWidth, blockHeight, &output); + m_Layer->prepare(); +} + +void NeonBatchToSpaceNdWorkload::Execute() const +{ + if (m_Layer) + { + ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSpaceToBatchNdWorkload_Execute"); + m_Layer->run(); + } +} + +} //namespace armnn |