| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonSoftmaxUint8Workload.hpp" |
| |
| namespace armnn |
| { |
| |
| NeonSoftmaxUint8Workload::NeonSoftmaxUint8Workload(const SoftmaxQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager) |
| : Uint8Workload<SoftmaxQueueDescriptor>(descriptor, info) |
| , m_SoftmaxLayer(memoryManager) |
| { |
| m_Data.ValidateInputsOutputs("NeonSoftmaxUint8Workload", 1, 1); |
| |
| 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(); |
| |
| const auto outputQuantization = output.info()->quantization_info(); |
| |
| if ((outputQuantization.scale != (1.0f / 256.0f)) || (outputQuantization.offset != 0)) |
| { |
| throw InvalidArgumentException( |
| "Invalid quantization for output. Only scale = 1.0f / 256.0f and offset = 0 supported"); |
| } |
| |
| m_SoftmaxLayer.configure(&input, &output, descriptor.m_Parameters.m_Beta); |
| } |
| |
| void NeonSoftmaxUint8Workload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSoftmaxUint8Workload_Execute"); |
| |
| m_SoftmaxLayer.run(); |
| } |
| |
| } //namespace armnn |
| |
