| // |
| // Copyright © 2017,2019-2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #include "ClConcatWorkload.hpp" |
| #include "ClWorkloadUtils.hpp" |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| #include <armnn/backends/TensorHandle.hpp> |
| #include <cl/ClTensorHandle.hpp> |
| #include <cl/ClLayerSupport.hpp> |
| |
| #include <arm_compute/core/Types.h> |
| |
| namespace armnn |
| { |
| using namespace armcomputetensorutils; |
| |
| namespace |
| { |
| size_t CalcAxis(const OriginsDescriptor& descriptor) |
| { |
| return (descriptor.GetNumDimensions() - descriptor.GetConcatAxis()) - 1; |
| } |
| } //namespace |
| |
| arm_compute::Status ClConcatWorkloadValidate(const std::vector<const TensorInfo*>& inputs, |
| const TensorInfo& output, |
| const OriginsDescriptor& descriptor) |
| { |
| std::vector<arm_compute::TensorInfo> aclInputs; |
| for (const TensorInfo* input : inputs) |
| { |
| arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(*input, armnn::DataLayout::NCHW); |
| aclInputs.emplace_back(aclInputInfo); |
| } |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output); |
| std::vector<const arm_compute::ITensorInfo*> aclInputPtrs; |
| for (arm_compute::ITensorInfo& input : aclInputs) |
| { |
| aclInputPtrs.emplace_back(&input); |
| } |
| |
| size_t aclAxis = CalcAxis(descriptor); |
| return arm_compute::CLConcatenateLayer::validate(aclInputPtrs, &aclOutputInfo, aclAxis); |
| } |
| |
| ClConcatWorkload::ClConcatWorkload(const ConcatQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| const arm_compute::CLCompileContext& clCompileContext) |
| : ClBaseWorkload<ConcatQueueDescriptor>(descriptor, info) |
| { |
| // Report Profiling Details |
| ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClConcatWorkload_Construct", |
| descriptor.m_Parameters, |
| info, |
| this->GetGuid()); |
| |
| bool allInputsAreSubtensors = true; |
| |
| // Check that all inputs are sub-tensors |
| for (auto input : descriptor.m_Inputs) |
| { |
| if (!input->GetParent()) |
| { |
| // Non sub-tensor input found so we need to execute the concat function |
| allInputsAreSubtensors = false; |
| break; |
| } |
| } |
| |
| if (allInputsAreSubtensors) |
| { |
| // Can skip configuring the concat function since it's not executed |
| return; |
| } |
| |
| std::vector<const arm_compute::ICLTensor *> aclInputs; |
| for (auto input : m_Data.m_Inputs) |
| { |
| arm_compute::ICLTensor& aclInput = armnn::PolymorphicPointerDowncast<IClTensorHandle>(input)->GetTensor(); |
| aclInputs.emplace_back(&aclInput); |
| } |
| |
| arm_compute::ICLTensor& output = |
| armnn::PolymorphicPointerDowncast<IClTensorHandle>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| // Create the layer function |
| auto layer = std::make_unique<arm_compute::CLConcatenateLayer>(); |
| |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClConcatWorkload_configure"); |
| // Configure input and output tensors |
| size_t aclAxis = CalcAxis(descriptor.m_Parameters); |
| layer->configure(clCompileContext, aclInputs, &output, aclAxis); |
| } |
| |
| // Prepare |
| layer->prepare(); |
| m_Layer = std::move(layer); |
| } |
| |
| void ClConcatWorkload::Execute() const |
| { |
| if (m_Layer) |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClConcatWorkload_Execute"); |
| m_Layer->run(); |
| } |
| } |
| |
| } //namespace armnn |