// // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #include "NeonLogSoftmaxWorkload.hpp" #include "NeonWorkloadUtils.hpp" #include #include #include #include namespace armnn { arm_compute::Status NeonLogSoftmaxWorkloadValidate(const TensorInfo& input, const TensorInfo& output, const LogSoftmaxDescriptor& descriptor) { const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); int aclAxis = ComputeAclAxis(descriptor.m_Axis, input); return arm_compute::NELogSoftmaxLayer::validate(&aclInputInfo, &aclOutputInfo, descriptor.m_Beta, aclAxis); } NeonLogSoftmaxWorkload::NeonLogSoftmaxWorkload(const LogSoftmaxQueueDescriptor& descriptor, const WorkloadInfo& info, std::shared_ptr& memoryManager) : NeonBaseWorkload(descriptor, info) { // Report Profiling Details ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonLogSoftmaxWorkload_Construct", descriptor.m_Parameters, info, this->GetGuid()); m_Data.ValidateInputsOutputs("NeonLogSoftmaxWorkload", 1, 1); arm_compute::ITensor& input = PolymorphicDowncast(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ITensor& output = PolymorphicDowncast(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique(memoryManager); int aclAxis = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]); layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis); m_LogSoftmaxLayer.reset(layer.release()); } void NeonLogSoftmaxWorkload::Execute() const { ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonLogSoftmaxWorkload_Execute", this->GetGuid()); m_LogSoftmaxLayer->run(); } } //namespace armnn