diff options
Diffstat (limited to 'src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp')
-rw-r--r-- | src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp | 58 |
1 files changed, 47 insertions, 11 deletions
diff --git a/src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp b/src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp index 089716a4b4..017ed9867e 100644 --- a/src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp +++ b/src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp @@ -5,6 +5,7 @@ #include "NeonConvertFp32ToFp16Workload.hpp" +#include <arm_compute/runtime/NEON/functions/NECast.h> #include <Half.hpp> #include <Profiling.hpp> @@ -12,32 +13,67 @@ #include <backendsCommon/WorkloadUtils.hpp> +static constexpr arm_compute::ConvertPolicy g_AclConvertPolicy = arm_compute::ConvertPolicy::SATURATE; + namespace armnn { +arm_compute::Status NeonConvertFp32ToFp16WorkloadValidate(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(); +} + NeonConvertFp32ToFp16Workload::NeonConvertFp32ToFp16Workload(const ConvertFp32ToFp16QueueDescriptor& descriptor, const WorkloadInfo& info) : Float32ToFloat16Workload<ConvertFp32ToFp16QueueDescriptor>(descriptor, info) { this->m_Data.ValidateInputsOutputs("NeonConvertFp32ToFp16Workload", 1, 1); - GatherTensorHandlePairs(descriptor, m_TensorHandlePairs); + + 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 from Half.hpp + GatherTensorHandlePairs(descriptor, m_TensorHandlePairs); + } } void NeonConvertFp32ToFp16Workload::Execute() const { ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonConvertFp32ToFp16Workload_Execute", this->GetGuid()); - auto convertFunc = [](uint8_t* dst, const uint8_t* src, size_t size) - { - auto input = reinterpret_cast<const float*>(src); - auto output = reinterpret_cast<Half*>(dst); - size_t numElements = size/2; // 2 bytes per fp16 - armnnUtils::FloatingPointConverter::ConvertFloat32To16(input, numElements, output); - }; - - for (const auto& pair : m_TensorHandlePairs) + if (m_Cast) { - CopyTensorContentsGeneric(pair.first, pair.second, convertFunc); + // Use NECast if supported and initialised + m_Cast->run(); + } + else + { + // Else use softwre implementabion using Half.hpp + auto convertFunc = [](uint8_t* dst, const uint8_t* src, size_t size) + { + auto input = reinterpret_cast<const float*>(src); + auto output = reinterpret_cast<Half*>(dst); + size_t numElements = size/2; // 2 bytes per fp16 + armnnUtils::FloatingPointConverter::ConvertFloat32To16(input, numElements, output); + }; + + for (const auto& pair : m_TensorHandlePairs) + { + CopyTensorContentsGeneric(pair.first, pair.second, convertFunc); + } } } |