IVGCVSW-6494 Add CpuAcc Batch MatMul Workload Fp32
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I2def6995f81d33e68f1ea45d8d19a1e6294049b1
diff --git a/src/backends/neon/workloads/NeonBatchMatMulWorkload.cpp b/src/backends/neon/workloads/NeonBatchMatMulWorkload.cpp
new file mode 100644
index 0000000..3d8651f
--- /dev/null
+++ b/src/backends/neon/workloads/NeonBatchMatMulWorkload.cpp
@@ -0,0 +1,190 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NeonBatchMatMulWorkload.hpp"
+
+#include "NeonWorkloadUtils.hpp"
+
+#include <armnn/utility/PolymorphicDowncast.hpp>
+
+#include <armnnUtils/Permute.hpp>
+
+#include <backendsCommon/WorkloadUtils.hpp>
+
+#include <arm_compute/runtime/NEON/functions/NEGEMM.h>
+
+#include <arm_compute/runtime/NEON/functions/NEPermute.h>
+
+
+namespace armnn
+{
+arm_compute::Status NeonBatchMatMulValidate(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");
+ }
+
+ 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::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);
+
+ 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::NEPermute::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::NEPermute::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::NEGEMM::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 BatchMatMul 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());
+ }
+
+}
+
+NeonBatchMatMulWorkload::NeonBatchMatMulWorkload(
+ const BatchMatMulQueueDescriptor& descriptor, const WorkloadInfo& info)
+ : NeonBaseWorkload<BatchMatMulQueueDescriptor>(descriptor, info)
+{
+ 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");
+ }
+
+ // Report Profiling Details
+ ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonBatchMatMulWorkload_Construct",
+ descriptor.m_Parameters,
+ info,
+ this->GetGuid());
+
+ m_Data.ValidateInputsOutputs("NeonBatchMatMulWorkload", 2, 1);
+
+ arm_compute::ITensor& inputX = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+ arm_compute::ITensor& inputY = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
+ auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0]);
+ arm_compute::ITensor& output = outputHandle->GetTensor();
+
+ arm_compute::DataLayout aclDataLayoutX = ConvertDataLayout(m_Data.m_Parameters.m_DataLayoutX);
+ arm_compute::DataLayout aclDataLayoutY = ConvertDataLayout(m_Data.m_Parameters.m_DataLayoutY);
+
+ inputX.info()->set_data_layout(aclDataLayoutX);
+ inputY.info()->set_data_layout(aclDataLayoutY);
+
+ 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);
+
+ auto permuteLayerX = std::make_unique<arm_compute::NEPermute>();
+ BuildArmComputeTensor(m_PermutedTensorX, permutedXInfo);
+ InitialiseArmComputeTensorEmpty(m_PermutedTensorX);
+ permuteLayerX->configure(&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);
+
+ auto permuteLayerY = std::make_unique<arm_compute::NEPermute>();
+ BuildArmComputeTensor(m_PermutedTensorY, permutedYInfo);
+ InitialiseArmComputeTensorEmpty(m_PermutedTensorY);
+ permuteLayerY->configure(&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::NEGEMM>();
+ gemmLayer->configure(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 NeonBatchMatMulWorkload::Execute() const
+{
+ ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonBatchMatMulWorkload_Execute", this->GetGuid());
+ if (m_PermuteLayerX)
+ {
+ m_PermuteLayerX->run();
+ }
+ if (m_PermuteLayerY)
+ {
+ m_PermuteLayerY->run();
+ }
+ m_GEMMLayer->run();
+}
+} //namespace armnn