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path: root/src/backends/neon/workloads/NeonConvertFp16ToFp32Workload.cpp
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Diffstat (limited to 'src/backends/neon/workloads/NeonConvertFp16ToFp32Workload.cpp')
-rw-r--r--src/backends/neon/workloads/NeonConvertFp16ToFp32Workload.cpp45
1 files changed, 40 insertions, 5 deletions
diff --git a/src/backends/neon/workloads/NeonConvertFp16ToFp32Workload.cpp b/src/backends/neon/workloads/NeonConvertFp16ToFp32Workload.cpp
index ce6c785329..f65d71904f 100644
--- a/src/backends/neon/workloads/NeonConvertFp16ToFp32Workload.cpp
+++ b/src/backends/neon/workloads/NeonConvertFp16ToFp32Workload.cpp
@@ -11,22 +11,56 @@
#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);
- 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 using Half.hpp
+ GatherTensorHandlePairs(descriptor, m_TensorHandlePairs);
+ }
}
void NeonConvertFp16ToFp32Workload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonConvertFp16ToFp32Workload_Execute", this->GetGuid());
- auto convertFunc = [](uint8_t* dst, const uint8_t* src, size_t size)
+ 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);
@@ -34,9 +68,10 @@ void NeonConvertFp16ToFp32Workload::Execute() const
armnnUtils::FloatingPointConverter::ConvertFloat16To32(input, numElements, output);
};
- for (const auto& pair : m_TensorHandlePairs)
- {
- CopyTensorContentsGeneric(pair.first, pair.second, convertFunc);
+ for (const auto& pair : m_TensorHandlePairs)
+ {
+ CopyTensorContentsGeneric(pair.first, pair.second, convertFunc);
+ }
}
}