| // |
| // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ClBatchMatMulWorkload.hpp" |
| |
| #include "ClWorkloadUtils.hpp" |
| |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| #include <aclCommon/ArmComputeUtils.hpp> |
| |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| |
| #include <armnnUtils/Permute.hpp> |
| |
| #include <backendsCommon/WorkloadUtils.hpp> |
| |
| #include <cl/ClTensorHandle.hpp> |
| |
| #include <arm_compute/runtime/CL/functions/CLGEMM.h> |
| #include <arm_compute/runtime/CL/functions/CLPermute.h> |
| |
| |
| namespace armnn |
| { |
| arm_compute::Status ClBatchMatMulValidate(const TensorInfo& inputX, |
| const TensorInfo& inputY, |
| const TensorInfo& output, |
| const BatchMatMulDescriptor& descriptor) |
| { |
| if (descriptor.m_AdjointX || descriptor.m_AdjointY ) |
| { |
| throw Exception("Support for adjoint not implemented."); |
| } |
| if (descriptor.m_DataLayoutX != armnn::DataLayout::NCHW || descriptor.m_DataLayoutY != armnn::DataLayout::NCHW ) |
| { |
| throw Exception("Only supported the MatMul in the last 2 dimensions"); |
| } |
| |
| arm_compute::Status statusGEMM = arm_compute::Status(arm_compute::ErrorCode::OK); |
| arm_compute::Status statusPermuteX = arm_compute::Status(arm_compute::ErrorCode::OK); |
| arm_compute::Status statusPermuteY = arm_compute::Status(arm_compute::ErrorCode::OK); |
| |
| const auto aclInputXInfo = armcomputetensorutils::BuildArmComputeTensorInfo(inputX, descriptor.m_DataLayoutX); |
| const auto aclInputYInfo = armcomputetensorutils::BuildArmComputeTensorInfo(inputY, descriptor.m_DataLayoutY); |
| const auto aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); |
| |
| arm_compute::TensorInfo aclPermutedXInfo = arm_compute::TensorInfo(); |
| arm_compute::TensorInfo aclPermutedYInfo = arm_compute::TensorInfo(); |
| |
| if (descriptor.m_TransposeX == true) |
| { |
| auto permutationXVector = GeneratePermutationVectorOnLastTwoDimensions(inputX.GetNumDimensions()); |
| const auto aclPermutationXVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationXVector); |
| const TensorInfo permutedXInfo = armnnUtils::Permuted(inputX, permutationXVector); |
| aclPermutedXInfo = armcomputetensorutils::BuildArmComputeTensorInfo(permutedXInfo); |
| |
| statusPermuteX = arm_compute::CLPermute::validate(&aclInputXInfo, |
| &aclPermutedXInfo, |
| aclPermutationXVector); |
| } |
| |
| if ( descriptor.m_TransposeY == true) |
| { |
| auto permutationYVector = GeneratePermutationVectorOnLastTwoDimensions(inputY.GetNumDimensions()); |
| const auto aclPermutationYVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationYVector); |
| const TensorInfo permutedYInfo = armnnUtils::Permuted(inputY, permutationYVector); |
| aclPermutedYInfo = armcomputetensorutils::BuildArmComputeTensorInfo(permutedYInfo); |
| |
| statusPermuteY = arm_compute::CLPermute::validate(&aclInputYInfo, |
| &aclPermutedYInfo, |
| aclPermutationYVector); |
| |
| } |
| |
| const arm_compute::GEMMInfo& gemm_info = arm_compute::GEMMInfo(false, // is inputX reshaped |
| false, // is inputY reshaped |
| false); // is inputY reshaped only 1st run |
| |
| |
| statusGEMM = arm_compute::CLGEMM::validate(descriptor.m_TransposeX ? &aclPermutedXInfo : &aclInputXInfo, |
| descriptor.m_TransposeY ? &aclPermutedYInfo : &aclInputYInfo, |
| nullptr, |
| &aclOutputInfo, |
| 1.0, |
| 0, |
| gemm_info); |
| |
| if (statusPermuteX.error_code() == arm_compute::ErrorCode::OK && |
| statusPermuteY.error_code() == arm_compute::ErrorCode::OK && |
| statusGEMM.error_code() == arm_compute::ErrorCode::OK) |
| { |
| return arm_compute::Status(arm_compute::ErrorCode::OK, |
| "All Batch Mat Mul layers validate status OK."); |
| } |
| else |
| { |
| return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, |
| "BatchMatMul layer validate status failed." |
| + statusGEMM.error_description() |
| + statusPermuteX.error_description() |
| + statusPermuteY.error_description()); |
| } |
| |
| } |
| |
| ClBatchMatMulWorkload::ClBatchMatMulWorkload(const BatchMatMulQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| const arm_compute::CLCompileContext& clCompileContext) |
| : ClBaseWorkload<BatchMatMulQueueDescriptor>(descriptor, info) |
| { |
| // Report Profiling Details |
| ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClBatchMatMulWorkload_Construct", |
| descriptor.m_Parameters, |
| info, |
| this->GetGuid()); |
| |
| if (descriptor.m_Parameters.m_AdjointX || descriptor.m_Parameters.m_AdjointY ) |
| { |
| throw Exception("Support for adjoint not implemented."); |
| } |
| if (descriptor.m_Parameters.m_DataLayoutX != armnn::DataLayout::NCHW || |
| descriptor.m_Parameters.m_DataLayoutY != armnn::DataLayout::NCHW ) |
| { |
| throw Exception("Only supported the MatMul in the last 2 dimensions"); |
| } |
| |
| m_Data.ValidateInputsOutputs("ClBatchMatMulWorkload", 2, 1); |
| |
| const arm_compute::ICLTensor& inputX = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| const arm_compute::ICLTensor& inputY = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); |
| arm_compute::ICLTensor& output = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| inputX.info()->set_data_layout(armcomputetensorutils::ConvertDataLayout(m_Data.m_Parameters.m_DataLayoutX)); |
| inputY.info()->set_data_layout(armcomputetensorutils::ConvertDataLayout(m_Data.m_Parameters.m_DataLayoutY)); |
| |
| arm_compute::TensorInfo aclPermutedXInfo = arm_compute::TensorInfo(); |
| arm_compute::TensorInfo aclPermutedYInfo = arm_compute::TensorInfo(); |
| |
| if (descriptor.m_Parameters.m_TransposeX == true) |
| { |
| armnn::PermutationVector permutationXVector |
| = GeneratePermutationVectorOnLastTwoDimensions(info.m_InputTensorInfos[0].GetNumDimensions()); |
| const TensorInfo permutedXInfo = armnnUtils::Permuted(info.m_InputTensorInfos[0], permutationXVector); |
| const auto aclPermutationXVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationXVector); |
| armcomputetensorutils::BuildArmComputeTensor(m_PermutedTensorX, permutedXInfo); |
| armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_PermutedTensorX); |
| |
| auto permuteLayerX = std::make_unique<arm_compute::CLPermute>(); |
| permuteLayerX->configure(clCompileContext, |
| &inputX, |
| &m_PermutedTensorX, |
| aclPermutationXVector); |
| m_PermuteLayerX.reset(permuteLayerX.release()); |
| } |
| |
| if (descriptor.m_Parameters.m_TransposeY == true) |
| { |
| armnn::PermutationVector permutationYVector |
| = GeneratePermutationVectorOnLastTwoDimensions(info.m_InputTensorInfos[1].GetNumDimensions()); |
| const TensorInfo permutedYInfo = armnnUtils::Permuted(info.m_InputTensorInfos[1], permutationYVector); |
| const auto aclPermutationYVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationYVector); |
| armcomputetensorutils::BuildArmComputeTensor(m_PermutedTensorY, permutedYInfo); |
| armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_PermutedTensorY); |
| |
| auto permuteLayerY = std::make_unique<arm_compute::CLPermute>(); |
| permuteLayerY->configure(clCompileContext, |
| &inputY, |
| &m_PermutedTensorY, |
| aclPermutationYVector); |
| m_PermuteLayerY.reset(permuteLayerY.release()); |
| } |
| |
| const arm_compute::GEMMInfo& gemm_info = arm_compute::GEMMInfo(false, // is inputX reshaped |
| false, // is inputY reshaped |
| false); // is inputY reshaped only 1st run |
| auto gemmLayer = std::make_unique<arm_compute::CLGEMM>(); |
| gemmLayer->configure(clCompileContext, |
| descriptor.m_Parameters.m_TransposeX ? &m_PermutedTensorX : &inputX, |
| descriptor.m_Parameters.m_TransposeY ? &m_PermutedTensorY : &inputY, |
| nullptr, |
| &output, |
| 1.0, |
| 0, |
| gemm_info); |
| m_GEMMLayer.reset(gemmLayer.release()); |
| } |
| |
| void ClBatchMatMulWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClBatchMatMulWorkload_Execute", this->GetGuid()); |
| if (m_PermuteLayerX) |
| { |
| m_PermuteLayerX->run(); |
| } |
| if (m_PermuteLayerY) |
| { |
| m_PermuteLayerY->run(); |
| } |
| m_GEMMLayer->run(); |
| } |
| } //namespace armnn |