| // |
| // Copyright © 2017-2019,2021-2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonConvertFp16ToFp32Workload.hpp" |
| |
| #include <armnnUtils/FloatingPointConverter.hpp> |
| |
| #include <Half.hpp> |
| |
| #include <backendsCommon/WorkloadUtils.hpp> |
| |
| static constexpr arm_compute::ConvertPolicy g_AclConvertPolicy = arm_compute::ConvertPolicy::SATURATE; |
| |
| namespace armnn |
| { |
| |
| arm_compute::Status NeonConvertFp16ToFp32WorkloadValidate(const TensorInfo& input, const TensorInfo& output) |
| { |
| // Fallback to portable software implementation if Compute Library NECast won't work, so |
| // this method always returns success |
| |
| armnn::IgnoreUnused(input); |
| armnn::IgnoreUnused(output); |
| return arm_compute::Status(); |
| } |
| |
| NeonConvertFp16ToFp32Workload::NeonConvertFp16ToFp32Workload(const ConvertFp16ToFp32QueueDescriptor& descriptor, |
| const WorkloadInfo& info) |
| : Float16ToFloat32Workload<ConvertFp16ToFp32QueueDescriptor>(descriptor, info) |
| { |
| this->m_Data.ValidateInputsOutputs("NeonConvertFp16ToFp32Workload", 1, 1); |
| |
| arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| if (arm_compute::NECast::validate(input.info(), output.info(), g_AclConvertPolicy)) |
| { |
| // Use NECast if supported (needs hardware support for FP16) |
| m_Cast.reset(new arm_compute::NECast()); |
| m_Cast->configure(&input, &output, g_AclConvertPolicy); |
| } |
| else |
| { |
| // Else use software implementation using Half.hpp |
| GatherTensorHandlePairs(descriptor, m_TensorHandlePairs); |
| } |
| } |
| |
| void NeonConvertFp16ToFp32Workload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID("NeonConvertFp16ToFp32Workload_Execute"); |
| |
| if (m_Cast) |
| { |
| // Use NECast if supported and initialised |
| m_Cast->run(); |
| } |
| else |
| { |
| // Else use softare implementation using Half.hpp |
| auto convertFunc = [](uint8_t* dst, const uint8_t* src, size_t size) |
| { |
| auto input = reinterpret_cast<const Half*>(src); |
| auto output = reinterpret_cast<float*>(dst); |
| size_t numElements = size/2; // 2 bytes per fp16 |
| armnnUtils::FloatingPointConverter::ConvertFloat16To32(input, numElements, output); |
| }; |
| |
| for (const auto& pair : m_TensorHandlePairs) |
| { |
| CopyTensorContentsGeneric(pair.first, pair.second, convertFunc); |
| } |
| } |
| } |
| |
| void NeonConvertFp16ToFp32Workload::ReplaceInputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot) |
| { |
| ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot]; |
| this->m_Data.m_Inputs[slot] = tensorHandle; |
| try |
| { |
| Reconfigure(); |
| } |
| catch(armnn::UnimplementedException& e) |
| { |
| // Cannot reconfigure, revert the slot back and throw the exception. |
| this->m_Data.m_Inputs[slot] = backupHandle; |
| throw e; |
| } |
| } |
| |
| // Replace output tensor handle with the given TensorHandle |
| void NeonConvertFp16ToFp32Workload::ReplaceOutputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot) |
| { |
| ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot]; |
| this->m_Data.m_Inputs[slot] = tensorHandle; |
| try |
| { |
| Reconfigure(); |
| } |
| catch(armnn::UnimplementedException& e) |
| { |
| // Cannot reconfigure, revert the slot back and throw the exception. |
| this->m_Data.m_Inputs[slot] = backupHandle; |
| throw e; |
| } |
| } |
| |
| void NeonConvertFp16ToFp32Workload::Reconfigure() |
| { |
| throw armnn::UnimplementedException("Reconfigure not implemented for this workload"); |
| } |
| |
| } //namespace armnn |