| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonSoftmaxFloatWorkload.hpp" |
| |
| #include "NeonWorkloadUtils.hpp" |
| |
| #include <aclCommon/ArmComputeUtils.hpp> |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| |
| #include <arm_compute/runtime/NEON/functions/NESoftmaxLayer.h> |
| |
| namespace armnn |
| { |
| |
| NeonSoftmaxFloatWorkload::NeonSoftmaxFloatWorkload(const SoftmaxQueueDescriptor& descriptor, |
| const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager) |
| : FloatWorkload<SoftmaxQueueDescriptor>(descriptor, info) |
| { |
| m_Data.ValidateInputsOutputs("NeonSoftmaxFloatWorkload", 1, 1); |
| |
| // The ArmCompute softmax layer uses 2D input/output tensors, so flatten the first three dimensions. |
| arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| auto layer = std::make_unique<arm_compute::NESoftmaxLayer>(memoryManager); |
| unsigned int aclAxis = ComputeSoftmaxAclAxis(m_Data.m_Parameters, info.m_InputTensorInfos[0]); |
| layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis); |
| m_SoftmaxLayer.reset(layer.release()); |
| } |
| |
| void NeonSoftmaxFloatWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSoftmaxFloatWorkload_Execute"); |
| m_SoftmaxLayer->run(); |
| } |
| |
| } //namespace armnn |
| |