| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonSoftmaxFloatWorkload.hpp" |
| |
| namespace armnn |
| { |
| |
| NeonSoftmaxFloatWorkload::NeonSoftmaxFloatWorkload(const SoftmaxQueueDescriptor& descriptor, |
| const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager) |
| : FloatWorkload<SoftmaxQueueDescriptor>(descriptor, info) |
| , m_SoftmaxLayer(memoryManager) |
| { |
| 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 = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| m_SoftmaxLayer.configure(&input, &output, m_Data.m_Parameters.m_Beta); |
| } |
| |
| void NeonSoftmaxFloatWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSoftmaxFloatWorkload_Execute"); |
| m_SoftmaxLayer.run(); |
| } |
| |
| } //namespace armnn |
| |