Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 1 | // |
Teresa Charlin | c074cdb | 2023-01-13 18:44:00 +0000 | [diff] [blame] | 2 | // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include "ClBatchMatMulWorkload.hpp" |
| 7 | |
| 8 | #include "ClWorkloadUtils.hpp" |
| 9 | |
| 10 | #include <aclCommon/ArmComputeTensorUtils.hpp> |
| 11 | #include <aclCommon/ArmComputeUtils.hpp> |
| 12 | |
| 13 | #include <armnn/utility/PolymorphicDowncast.hpp> |
| 14 | |
| 15 | #include <armnnUtils/Permute.hpp> |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 16 | #include <armnnUtils/TensorUtils.hpp> |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 17 | |
| 18 | #include <backendsCommon/WorkloadUtils.hpp> |
| 19 | |
| 20 | #include <cl/ClTensorHandle.hpp> |
| 21 | |
| 22 | #include <arm_compute/runtime/CL/functions/CLGEMM.h> |
| 23 | #include <arm_compute/runtime/CL/functions/CLPermute.h> |
| 24 | |
| 25 | |
| 26 | namespace armnn |
| 27 | { |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 28 | |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 29 | arm_compute::Status ClBatchMatMulValidate(const TensorInfo& inputX, |
| 30 | const TensorInfo& inputY, |
| 31 | const TensorInfo& output, |
| 32 | const BatchMatMulDescriptor& descriptor) |
| 33 | { |
| 34 | if (descriptor.m_AdjointX || descriptor.m_AdjointY ) |
| 35 | { |
| 36 | throw Exception("Support for adjoint not implemented."); |
| 37 | } |
| 38 | if (descriptor.m_DataLayoutX != armnn::DataLayout::NCHW || descriptor.m_DataLayoutY != armnn::DataLayout::NCHW ) |
| 39 | { |
| 40 | throw Exception("Only supported the MatMul in the last 2 dimensions"); |
| 41 | } |
| 42 | |
| 43 | arm_compute::Status statusGEMM = arm_compute::Status(arm_compute::ErrorCode::OK); |
| 44 | arm_compute::Status statusPermuteX = arm_compute::Status(arm_compute::ErrorCode::OK); |
| 45 | arm_compute::Status statusPermuteY = arm_compute::Status(arm_compute::ErrorCode::OK); |
| 46 | |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 47 | // ClGemmMatrixMultiplyNativeKernel used by CLGEMM can only support 3 dimensional |
| 48 | // tensors so try to reduce the dimensions to 3 |
| 49 | const auto aclInputXInfo = armcomputetensorutils::BuildArmComputeTensorInfo(inputX, descriptor.m_DataLayoutX, 3); |
| 50 | const auto aclInputYInfo = armcomputetensorutils::BuildArmComputeTensorInfo(inputY, descriptor.m_DataLayoutY, 3); |
| 51 | const auto aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output, descriptor.m_DataLayoutY, 3); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 52 | |
| 53 | arm_compute::TensorInfo aclPermutedXInfo = arm_compute::TensorInfo(); |
| 54 | arm_compute::TensorInfo aclPermutedYInfo = arm_compute::TensorInfo(); |
| 55 | |
| 56 | if (descriptor.m_TransposeX == true) |
| 57 | { |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 58 | armnn::TensorInfo inputXStripped = armnnUtils::ReduceDims(inputX, 3); |
| 59 | |
| 60 | auto permutationXVector = GeneratePermutationVectorOnLastTwoDimensions(inputXStripped.GetNumDimensions()); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 61 | const auto aclPermutationXVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationXVector); |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 62 | const TensorInfo permutedXInfo = armnnUtils::Permuted(inputXStripped, permutationXVector); |
| 63 | aclPermutedXInfo = armcomputetensorutils::BuildArmComputeTensorInfo(permutedXInfo, 3); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 64 | |
| 65 | statusPermuteX = arm_compute::CLPermute::validate(&aclInputXInfo, |
| 66 | &aclPermutedXInfo, |
| 67 | aclPermutationXVector); |
| 68 | } |
| 69 | |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 70 | if (descriptor.m_TransposeY == true) |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 71 | { |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 72 | armnn::TensorInfo inputYStripped = armnnUtils::ReduceDims(inputY, 3); |
| 73 | |
| 74 | auto permutationYVector = GeneratePermutationVectorOnLastTwoDimensions(inputYStripped.GetNumDimensions()); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 75 | const auto aclPermutationYVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationYVector); |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 76 | const TensorInfo permutedYInfo = armnnUtils::Permuted(inputYStripped, permutationYVector); |
| 77 | aclPermutedYInfo = armcomputetensorutils::BuildArmComputeTensorInfo(permutedYInfo, 3); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 78 | |
| 79 | statusPermuteY = arm_compute::CLPermute::validate(&aclInputYInfo, |
| 80 | &aclPermutedYInfo, |
| 81 | aclPermutationYVector); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 82 | } |
| 83 | |
| 84 | const arm_compute::GEMMInfo& gemm_info = arm_compute::GEMMInfo(false, // is inputX reshaped |
| 85 | false, // is inputY reshaped |
| 86 | false); // is inputY reshaped only 1st run |
| 87 | |
| 88 | |
| 89 | statusGEMM = arm_compute::CLGEMM::validate(descriptor.m_TransposeX ? &aclPermutedXInfo : &aclInputXInfo, |
| 90 | descriptor.m_TransposeY ? &aclPermutedYInfo : &aclInputYInfo, |
| 91 | nullptr, |
| 92 | &aclOutputInfo, |
| 93 | 1.0, |
| 94 | 0, |
| 95 | gemm_info); |
| 96 | |
| 97 | if (statusPermuteX.error_code() == arm_compute::ErrorCode::OK && |
| 98 | statusPermuteY.error_code() == arm_compute::ErrorCode::OK && |
| 99 | statusGEMM.error_code() == arm_compute::ErrorCode::OK) |
| 100 | { |
| 101 | return arm_compute::Status(arm_compute::ErrorCode::OK, |
| 102 | "All Batch Mat Mul layers validate status OK."); |
| 103 | } |
| 104 | else |
| 105 | { |
| 106 | return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, |
| 107 | "BatchMatMul layer validate status failed." |
| 108 | + statusGEMM.error_description() |
| 109 | + statusPermuteX.error_description() |
| 110 | + statusPermuteY.error_description()); |
| 111 | } |
| 112 | |
| 113 | } |
| 114 | |
| 115 | ClBatchMatMulWorkload::ClBatchMatMulWorkload(const BatchMatMulQueueDescriptor& descriptor, |
| 116 | const WorkloadInfo& info, |
| 117 | const arm_compute::CLCompileContext& clCompileContext) |
| 118 | : ClBaseWorkload<BatchMatMulQueueDescriptor>(descriptor, info) |
| 119 | { |
| 120 | // Report Profiling Details |
| 121 | ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClBatchMatMulWorkload_Construct", |
| 122 | descriptor.m_Parameters, |
| 123 | info, |
| 124 | this->GetGuid()); |
| 125 | |
| 126 | if (descriptor.m_Parameters.m_AdjointX || descriptor.m_Parameters.m_AdjointY ) |
| 127 | { |
| 128 | throw Exception("Support for adjoint not implemented."); |
| 129 | } |
| 130 | if (descriptor.m_Parameters.m_DataLayoutX != armnn::DataLayout::NCHW || |
| 131 | descriptor.m_Parameters.m_DataLayoutY != armnn::DataLayout::NCHW ) |
| 132 | { |
| 133 | throw Exception("Only supported the MatMul in the last 2 dimensions"); |
| 134 | } |
| 135 | |
| 136 | m_Data.ValidateInputsOutputs("ClBatchMatMulWorkload", 2, 1); |
| 137 | |
| 138 | const arm_compute::ICLTensor& inputX = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| 139 | const arm_compute::ICLTensor& inputY = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); |
| 140 | arm_compute::ICLTensor& output = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| 141 | |
| 142 | inputX.info()->set_data_layout(armcomputetensorutils::ConvertDataLayout(m_Data.m_Parameters.m_DataLayoutX)); |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 143 | arm_compute::TensorShape inputXTensorInfo = armcomputetensorutils::BuildArmComputeTensorShape( |
| 144 | info.m_InputTensorInfos[0].GetShape(), 3); |
| 145 | inputX.info()->set_tensor_shape(inputXTensorInfo); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 146 | inputY.info()->set_data_layout(armcomputetensorutils::ConvertDataLayout(m_Data.m_Parameters.m_DataLayoutY)); |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 147 | arm_compute::TensorShape inputYTensorInfo = armcomputetensorutils::BuildArmComputeTensorShape( |
| 148 | info.m_InputTensorInfos[1].GetShape(), 3); |
| 149 | inputY.info()->set_tensor_shape(inputYTensorInfo); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 150 | |
| 151 | arm_compute::TensorInfo aclPermutedXInfo = arm_compute::TensorInfo(); |
| 152 | arm_compute::TensorInfo aclPermutedYInfo = arm_compute::TensorInfo(); |
| 153 | |
| 154 | if (descriptor.m_Parameters.m_TransposeX == true) |
| 155 | { |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 156 | armnn::TensorInfo strippedInfo = armnnUtils::ReduceDims(info.m_InputTensorInfos[0], 3); |
| 157 | |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 158 | armnn::PermutationVector permutationXVector |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 159 | = GeneratePermutationVectorOnLastTwoDimensions(strippedInfo.GetNumDimensions()); |
| 160 | const TensorInfo permutedXInfo = armnnUtils::Permuted(strippedInfo, permutationXVector); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 161 | const auto aclPermutationXVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationXVector); |
| 162 | armcomputetensorutils::BuildArmComputeTensor(m_PermutedTensorX, permutedXInfo); |
| 163 | armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_PermutedTensorX); |
| 164 | |
| 165 | auto permuteLayerX = std::make_unique<arm_compute::CLPermute>(); |
| 166 | permuteLayerX->configure(clCompileContext, |
| 167 | &inputX, |
| 168 | &m_PermutedTensorX, |
| 169 | aclPermutationXVector); |
| 170 | m_PermuteLayerX.reset(permuteLayerX.release()); |
| 171 | } |
| 172 | |
| 173 | if (descriptor.m_Parameters.m_TransposeY == true) |
| 174 | { |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 175 | armnn::TensorInfo strippedInfo = armnnUtils::ReduceDims(info.m_InputTensorInfos[1], 3); |
| 176 | |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 177 | armnn::PermutationVector permutationYVector |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 178 | = GeneratePermutationVectorOnLastTwoDimensions(strippedInfo.GetNumDimensions()); |
| 179 | const TensorInfo permutedYInfo = armnnUtils::Permuted(strippedInfo, permutationYVector); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 180 | const auto aclPermutationYVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationYVector); |
| 181 | armcomputetensorutils::BuildArmComputeTensor(m_PermutedTensorY, permutedYInfo); |
| 182 | armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_PermutedTensorY); |
| 183 | |
Teresa Charlin | c074cdb | 2023-01-13 18:44:00 +0000 | [diff] [blame] | 184 | auto permuteLayerY = std::make_unique<arm_compute::CLPermute>(); |
Teresa Charlin | 94916a5 | 2022-10-19 08:48:07 +0100 | [diff] [blame] | 185 | permuteLayerY->configure(clCompileContext, |
| 186 | &inputY, |
| 187 | &m_PermutedTensorY, |
| 188 | aclPermutationYVector); |
| 189 | m_PermuteLayerY.reset(permuteLayerY.release()); |
| 190 | } |
| 191 | |
| 192 | const arm_compute::GEMMInfo& gemm_info = arm_compute::GEMMInfo(false, // is inputX reshaped |
| 193 | false, // is inputY reshaped |
| 194 | false); // is inputY reshaped only 1st run |
| 195 | auto gemmLayer = std::make_unique<arm_compute::CLGEMM>(); |
| 196 | gemmLayer->configure(clCompileContext, |
| 197 | descriptor.m_Parameters.m_TransposeX ? &m_PermutedTensorX : &inputX, |
| 198 | descriptor.m_Parameters.m_TransposeY ? &m_PermutedTensorY : &inputY, |
| 199 | nullptr, |
| 200 | &output, |
| 201 | 1.0, |
| 202 | 0, |
| 203 | gemm_info); |
| 204 | m_GEMMLayer.reset(gemmLayer.release()); |
| 205 | } |
| 206 | |
| 207 | void ClBatchMatMulWorkload::Execute() const |
| 208 | { |
| 209 | ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClBatchMatMulWorkload_Execute", this->GetGuid()); |
| 210 | if (m_PermuteLayerX) |
| 211 | { |
| 212 | m_PermuteLayerX->run(); |
| 213 | } |
| 214 | if (m_PermuteLayerY) |
| 215 | { |
| 216 | m_PermuteLayerY->run(); |
| 217 | } |
| 218 | m_GEMMLayer->run(); |
| 219 | } |
| 220 | } //namespace armnn |