| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ClDepthwiseConvolutionWorkload.hpp" |
| |
| #include <ResolveType.hpp> |
| #include "ClWorkloadUtils.hpp" |
| |
| #include <armnn/Exceptions.hpp> |
| #include <aclCommon/ArmComputeUtils.hpp> |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| #include <cl/ClTensorHandle.hpp> |
| #include <backendsCommon/TensorHandle.hpp> |
| #include <backendsCommon/WorkloadUtils.hpp> |
| #include <backendsCommon/WorkloadData.hpp> |
| |
| #include <arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h> |
| |
| namespace armnn |
| { |
| |
| using namespace armcomputetensorutils; |
| |
| arm_compute::Status ClDepthwiseConvolutionWorkloadValidate(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| const ActivationDescriptor* activationDescriptor) |
| { |
| const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); |
| |
| // ArmNN's weight format is [ M, I, H, W ] |
| const unsigned int aclDepthMultiplier = weights.GetShape()[0]; |
| |
| // Convert the weight format from ArmNN's [ M, I, H, W ] (does NOT depend on the data layout) to either |
| // [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library |
| TensorInfo weightsPermuted = ConvertWeightTensorInfoFromArmnnToAcl(weights, descriptor.m_DataLayout); |
| |
| // Convert the weights into the compute library format |
| const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weightsPermuted, 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::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor); |
| const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D( |
| descriptor.m_DilationX, |
| descriptor.m_DilationY); |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo( |
| activationDescriptor); |
| |
| return arm_compute::CLDepthwiseConvolutionLayer::validate(&aclInputInfo, |
| &aclWeightsInfo, |
| optionalAclBiasesInfo, |
| &aclOutputInfo, |
| aclPadStrideInfo, |
| aclDepthMultiplier, |
| activationInfo, |
| aclDilationInfo); |
| |
| } |
| |
| ClDepthwiseConvolutionWorkload::ClDepthwiseConvolutionWorkload( |
| const DepthwiseConvolution2dQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| const arm_compute::CLCompileContext& clCompileContext) |
| : BaseWorkload<DepthwiseConvolution2dQueueDescriptor>(descriptor, info) |
| { |
| // Allocate a buffer for the swizzling of the weight tensor |
| std::unique_ptr<unsigned char[]> permuteBuffer(new unsigned char[m_Data.m_Weight->GetTensorInfo().GetNumBytes()]); |
| |
| // Convert the weight format from ArmNN's [ M, I, H, W ] (does NOT depend on the data layout) to either |
| // [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library |
| ConstTensor weightPermuted = ConvertWeightTensorFromArmnnToAcl(m_Data.m_Weight, |
| m_Data.m_Parameters.m_DataLayout, |
| permuteBuffer.get()); |
| |
| // Convert the weights into the compute library format |
| m_KernelTensor = std::make_unique<arm_compute::CLTensor>(); |
| BuildArmComputeTensor(*m_KernelTensor, weightPermuted.GetInfo(), m_Data.m_Parameters.m_DataLayout); |
| |
| if (m_Data.m_Parameters.m_BiasEnabled) |
| { |
| m_BiasTensor = std::make_unique<arm_compute::CLTensor>(); |
| BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); |
| } |
| |
| const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D( |
| m_Data.m_Parameters.m_DilationX, |
| m_Data.m_Parameters.m_DilationY); |
| |
| |
| std::string name = std::string("ClDepthwiseConvolutionWorkload"); |
| m_Data.ValidateInputsOutputs(name, 1, 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::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); |
| input.info()->set_data_layout(aclDataLayout); |
| output.info()->set_data_layout(aclDataLayout); |
| |
| // ArmNN's weight format is [ M, I, H, W ] |
| auto& weightInfo = m_Data.m_Weight->GetTensorInfo(); |
| |
| // Get the depth multiplier |
| const unsigned int depthMultiplier = weightInfo.GetShape()[0]; |
| |
| arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters); |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor); |
| |
| m_DepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer>(); |
| static_cast<arm_compute::CLDepthwiseConvolutionLayer*>(m_DepthwiseConvolutionLayer.get())->configure( |
| clCompileContext, |
| &input, |
| m_KernelTensor.get(), |
| m_BiasTensor.get(), |
| &output, |
| padStrideInfo, |
| depthMultiplier, |
| activationInfo, |
| aclDilationInfo); |
| |
| ARMNN_ASSERT(m_DepthwiseConvolutionLayer); |
| |
| ScopedTensorHandle weightsPermutedHandle(weightPermuted); |
| InitializeArmComputeClTensorData(*m_KernelTensor, &weightsPermutedHandle); |
| |
| if (m_BiasTensor) |
| { |
| InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias); |
| } |
| |
| m_DepthwiseConvolutionLayer->prepare(); |
| FreeUnusedTensors(); |
| } |
| |
| void ClDepthwiseConvolutionWorkload::FreeUnusedTensors() |
| { |
| FreeTensorIfUnused(m_KernelTensor); |
| FreeTensorIfUnused(m_BiasTensor); |
| } |
| |
| void ClDepthwiseConvolutionWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL("ClDepthwiseConvolutionWorkload_Execute"); |
| ARMNN_ASSERT(m_DepthwiseConvolutionLayer); |
| |
| RunClFunction(*m_DepthwiseConvolutionLayer, CHECK_LOCATION()); |
| } |
| |
| } // namespace armnn |