| // |
| // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ClConvolution2dWorkload.hpp" |
| |
| #include "ClWorkloadUtils.hpp" |
| |
| #include <cl/ClLayerSupport.hpp> |
| #include <cl/ClTensorHandle.hpp> |
| #include <cl/ClLayerSupport.hpp> |
| #include <aclCommon/ArmComputeUtils.hpp> |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| #include <armnn/backends/TensorHandle.hpp> |
| |
| #include <arm_compute/runtime/CL/functions/CLConvolutionLayer.h> |
| |
| namespace armnn |
| { |
| using namespace armcomputetensorutils; |
| |
| arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| bool isFastMathEnabled, |
| const ActivationDescriptor* activationDescriptor) |
| { |
| const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); |
| arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); |
| aclWeightsInfo.set_are_values_constant(weights.IsConstant()); |
| |
| const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(descriptor.m_DilationX, |
| descriptor.m_DilationY); |
| |
| arm_compute::TensorInfo aclBiasesInfo; |
| arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr; |
| |
| if (descriptor.m_BiasEnabled) |
| { |
| ARMNN_ASSERT(biases.has_value()); |
| // Same for bias as weights. We don't currently support non const. |
| if (!biases.value().IsConstant()) |
| { |
| return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, |
| "ArmNN ClConvolution2dWorkload does not support non constant bias."}; |
| } |
| aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); |
| aclBiasesInfo.set_are_values_constant(biases.value().IsConstant()); |
| optionalAclBiasesInfo = &aclBiasesInfo; |
| } |
| |
| arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor); |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo( |
| activationDescriptor); |
| |
| return arm_compute::CLConvolutionLayer::validate(&aclInputInfo, |
| &aclWeightsInfo, |
| optionalAclBiasesInfo, |
| &aclOutputInfo, |
| layerInfo, |
| arm_compute::WeightsInfo(), |
| aclDilationInfo, |
| activationInfo, |
| isFastMathEnabled); |
| } |
| |
| ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager, |
| const arm_compute::CLCompileContext& clCompileContext, |
| const bool isFastMathEnabled) |
| : ClBaseWorkload<Convolution2dQueueDescriptor>(descriptor, info) |
| , m_ConvolutionLayer(memoryManager) |
| { |
| ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClConvolution2dWorkload"); |
| |
| const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(m_Data.m_Parameters.m_DilationX, |
| m_Data.m_Parameters.m_DilationY); |
| |
| uint32_t numInputs = m_Data.m_Parameters.m_BiasEnabled ? 3: 2; |
| m_Data.ValidateInputsOutputs("ClConvolution2dWorkload", numInputs, 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::ICLTensor& weights = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); |
| if (m_Data.m_Parameters.m_BiasEnabled) |
| { |
| arm_compute::ICLTensor& bias = static_cast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor(); |
| m_BiasProxy = std::make_unique<ICLTensorProxy>(&bias); |
| } |
| |
| // Create Proxy tensor and set the initial tensor handle to it |
| m_InputProxy = std::make_unique<ICLTensorProxy>(&input); |
| m_OutputProxy = std::make_unique<ICLTensorProxy>(&output); |
| m_WeightsProxy = std::make_unique<ICLTensorProxy>(&weights); |
| |
| arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); |
| input.info()->set_data_layout(aclDataLayout); |
| output.info()->set_data_layout(aclDataLayout); |
| weights.info()->set_data_layout(aclDataLayout); |
| |
| arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters); |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor); |
| |
| { |
| ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClConvolution2dWorkload_configure"); |
| m_ConvolutionLayer.configure(clCompileContext, |
| m_InputProxy.get(), |
| m_WeightsProxy.get(), |
| m_BiasProxy.get(), |
| m_OutputProxy.get(), |
| padStrideInfo, |
| arm_compute::WeightsInfo(), |
| aclDilationInfo, |
| activationInfo, |
| isFastMathEnabled); |
| } |
| |
| m_ConvolutionMethod = |
| m_ConvolutionLayer.get_convolution_method(input.info(), |
| weights.info(), |
| output.info(), |
| padStrideInfo, |
| arm_compute::WeightsInfo(), |
| activationInfo, |
| arm_compute::CLScheduler::get().target(), |
| aclDilationInfo, |
| isFastMathEnabled); |
| |
| // Add details for profiling output |
| WorkloadInfo detailsInfo; |
| |
| detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos; |
| detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos; |
| detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(info.m_InputTensorInfos[1]); |
| detailsInfo.m_ConvolutionMethod = armnn::Optional<std::string>(GetConvolutionMethodString(m_ConvolutionMethod)); |
| if (descriptor.m_Parameters.m_BiasEnabled) |
| { |
| detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(info.m_InputTensorInfos[2]); |
| } |
| |
| // Report Profiling Details |
| ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClConvolution2dWorkload_Construct", |
| descriptor.m_Parameters, |
| detailsInfo, |
| GetGuid()); |
| } |
| |
| void ClConvolution2dWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClConvolution2dWorkload_Execute", GetGuid()); |
| RunClFunction(m_ConvolutionLayer, CHECK_LOCATION()); |
| } |
| |
| arm_compute::ConvolutionMethod ClConvolution2dWorkload::GetConvolutionMethod() const |
| { |
| return m_ConvolutionMethod; |
| } |
| |
| void ClConvolution2dWorkload::Reconfigure() |
| { |
| 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(); |
| |
| m_InputProxy->set(&input); |
| m_OutputProxy->set(&output); |
| } |
| |
| } //namespace armnn |