Release 18.08

[platform/upstream/armnn.git] / src / armnn / backends / NeonWorkloads / NeonSoftmaxFloat32Workload.cpp

diff --git a/src/armnn/backends/NeonWorkloads/NeonSoftmaxFloat32Workload.cpp b/src/armnn/backends/NeonWorkloads/NeonSoftmaxFloat32Workload.cpp
index 5e2925c..027b508 100644 (file)
--- a/src/armnn/backends/NeonWorkloads/NeonSoftmaxFloat32Workload.cpp
+++ b/src/armnn/backends/NeonWorkloads/NeonSoftmaxFloat32Workload.cpp
@@ -10,12 +10,12 @@ namespace armnn
 
 NeonSoftmaxFloat32Workload::NeonSoftmaxFloat32Workload(const SoftmaxQueueDescriptor& descriptor,
     const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
-    : Float32Workload<SoftmaxQueueDescriptor>(descriptor, info)
+    : FloatWorkload<SoftmaxQueueDescriptor>(descriptor, info)
     , m_SoftmaxLayer(memoryManager)
 {
     m_Data.ValidateInputsOutputs("NeonSoftmaxFloat32Workload", 1, 1);
 
-    // The ArmCompute softmax layer uses 2D input/output tensors, so flatten the first three dimensions
+    // The ArmCompute softmax layer uses 2D input/output tensors, so flatten the first three dimensions.
     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();
 
@@ -24,7 +24,7 @@ NeonSoftmaxFloat32Workload::NeonSoftmaxFloat32Workload(const SoftmaxQueueDescrip
 
 void NeonSoftmaxFloat32Workload::Execute() const
 {
-    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuAcc, "NeonSoftmaxFloat32Workload_Execute");
+    ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSoftmaxFloat32Workload_Execute");
     m_SoftmaxLayer.run();
 }