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Diffstat (limited to 'src/backends/neon/workloads/NeonSplitterWorkload.cpp')
-rw-r--r-- | src/backends/neon/workloads/NeonSplitterWorkload.cpp | 112 |
1 files changed, 112 insertions, 0 deletions
diff --git a/src/backends/neon/workloads/NeonSplitterWorkload.cpp b/src/backends/neon/workloads/NeonSplitterWorkload.cpp new file mode 100644 index 0000000000..bf35939127 --- /dev/null +++ b/src/backends/neon/workloads/NeonSplitterWorkload.cpp @@ -0,0 +1,112 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "NeonSplitterWorkload.hpp" + +#include "NeonWorkloadUtils.hpp" + +#include <aclCommon/ArmComputeTensorUtils.hpp> +#include <aclCommon/ArmComputeUtils.hpp> +#include <backendsCommon/CpuTensorHandle.hpp> +#include <neon/NeonTensorHandle.hpp> + + +namespace armnn +{ + +using namespace armcomputetensorutils; + +namespace +{ +unsigned int CalcAclAxis(unsigned int numDimensions, unsigned int splitAxis) +{ + return (numDimensions - splitAxis) - 1; +} + +} //namespace + +arm_compute::Status NeonSplitterWorkloadValidate(const TensorInfo& input, + const std::vector<std::reference_wrapper<TensorInfo>>& outputs, + unsigned int splitAxis) +{ + const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input); + + size_t numOutputs = outputs.size(); + + std::vector<arm_compute::TensorInfo> aclOutputs; + aclOutputs.reserve(numOutputs); + + std::vector<arm_compute::ITensorInfo*> aclOutputPtr; + aclOutputPtr.reserve(numOutputs); + + for (size_t i = 0u; i < outputs.size(); ++i) + { + aclOutputs.emplace_back(BuildArmComputeTensorInfo(outputs[i])); + aclOutputPtr.emplace_back(&aclOutputs.back()); + } + + unsigned int aclAxis = CalcAclAxis(input.GetNumDimensions(), splitAxis); + return arm_compute::NESplit::validate(&aclInputInfo, aclOutputPtr, aclAxis); +} + +NeonSplitterWorkload::NeonSplitterWorkload(const SplitterQueueDescriptor& descriptor, const WorkloadInfo& info) + : BaseWorkload<SplitterQueueDescriptor>(descriptor, info) +{ + bool allOutputsAreSubtensors = true; + + // Check that all outputs are sub-tensors + for (auto output : m_Data.m_Outputs) + { + if (output && !output->GetParent()) + { + // Non sub-tensor input found so we need to execute the split function + allOutputsAreSubtensors = false; + break; + } + } + + if (allOutputsAreSubtensors) + { + // Can skip configuring the split function since it's not executed + return; + } + + arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + + std::vector<arm_compute::ITensor *> aclOutputs; + for (auto output : m_Data.m_Outputs) + { + arm_compute::ITensor& aclOutput = boost::polymorphic_pointer_downcast<INeonTensorHandle>(output)->GetTensor(); + aclOutputs.emplace_back(&aclOutput); + } + + // Create the layer function + m_Layer.reset(new arm_compute::NESplit()); + + // Configure input and output tensors + std::set<unsigned int> splitAxis = ComputeSplitAxis(descriptor.m_Parameters, m_Data.m_Inputs[0]->GetShape()); + if (splitAxis.size() != 1) + { + throw InvalidArgumentException("Cannot derive split axis from SplitterDescriptor"); + } + + unsigned int aclAxis = CalcAclAxis(descriptor.m_Parameters.GetNumDimensions(), *splitAxis.begin()); + m_Layer->configure(&input, aclOutputs, aclAxis); + + // Prepare + m_Layer->prepare(); +} + +void NeonSplitterWorkload::Execute() const +{ + if (m_Layer) + { + ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSplitterWorkload_Execute"); + m_Layer->run(); + } +} + +} //namespace armnn + |