| // |
| // Copyright © 2021 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ClConvolution3dWorkload.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/CLConv3D.h> |
| |
| namespace armnn |
| { |
| using namespace armcomputetensorutils; |
| |
| arm_compute::Status ClConvolution3dWorkloadValidate(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution3dDescriptor& 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 aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); |
| |
| arm_compute::TensorInfo aclBiasesInfo; |
| arm_compute::TensorInfo* optionalAclBiasesInfo = nullptr; |
| if (descriptor.m_BiasEnabled) |
| { |
| ARMNN_ASSERT(biases.has_value()); |
| aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); |
| optionalAclBiasesInfo = &aclBiasesInfo; |
| } |
| |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); |
| |
| const arm_compute::Conv3dInfo aclConv3DInfo = ComputeConv3DInfo(descriptor, |
| isFastMathEnabled, |
| activationDescriptor); |
| |
| return arm_compute::CLConv3D::validate(&aclInputInfo, |
| &aclWeightsInfo, |
| optionalAclBiasesInfo, |
| &aclOutputInfo, |
| aclConv3DInfo); |
| } |
| |
| ClConvolution3dWorkload::ClConvolution3dWorkload(const Convolution3dQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager, |
| const arm_compute::CLCompileContext& clCompileContext, |
| const bool isFastMathEnabled) |
| : ClBaseWorkload<Convolution3dQueueDescriptor>(descriptor, info) |
| , m_ConvolutionLayer() |
| { |
| IgnoreUnused(memoryManager); |
| |
| uint32_t numInputs = m_Data.m_Parameters.m_BiasEnabled ? 3: 2; |
| m_Data.ValidateInputsOutputs("ClConvolution3dWorkload", numInputs, 1); |
| |
| arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ICLTensor& weights = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); |
| arm_compute::ICLTensor* biasesPtr = nullptr; |
| if (m_Data.m_Parameters.m_BiasEnabled) |
| { |
| biasesPtr = &static_cast<IClTensorHandle*>(m_Data.m_Inputs[2])->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); |
| weights.info()->set_data_layout(aclDataLayout); |
| output.info()->set_data_layout(aclDataLayout); |
| |
| const arm_compute::Conv3dInfo aclConv3DInfo = ComputeConv3DInfo(descriptor, |
| isFastMathEnabled); |
| |
| { |
| ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClConvolution3dWorkload_configure"); |
| m_ConvolutionLayer.configure(clCompileContext, |
| &input, |
| &weights, |
| biasesPtr, |
| &output, |
| aclConv3DInfo); |
| } |
| // Add details for profiling output |
| WorkloadInfo detailsInfo; |
| |
| detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos; |
| detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos; |
| |
| // Report Profiling Details |
| ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClConvolution3dWorkload_Construct", |
| descriptor.m_Parameters, |
| detailsInfo, |
| this->GetGuid()); |
| |
| // Force Compute Library to perform the necessary copying and reshaping, after which |
| // delete all the input tensors that will no longer be needed |
| m_ConvolutionLayer.prepare(); |
| } |
| |
| void ClConvolution3dWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClConvolution3dWorkload_Execute", this->GetGuid()); |
| RunClFunction(m_ConvolutionLayer, CHECK_LOCATION()); |
| } |
| |
| } //namespace armnn |