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path: root/src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp
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Diffstat (limited to 'src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp')
-rw-r--r--src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp58
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);
+ }
}
}