IVGCVSW-5167 Use a generic axis in CL/Neon LogSoftmax and Softmax workload
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Id72d2c2851adcc1dd8f00a6103642b16ebe3a964
diff --git a/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp b/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp
index 058756e..9c8ab07 100644
--- a/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp
+++ b/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp
@@ -23,7 +23,7 @@
const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input);
const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
- int aclAxis = ComputeSoftmaxAclAxis<int>(descriptor, input);
+ int aclAxis = ComputeAclAxis(descriptor.m_Axis, input);
return arm_compute::NELogSoftmaxLayer::validate(&aclInputInfo, &aclOutputInfo, descriptor.m_Beta, aclAxis);
}
@@ -38,7 +38,7 @@
arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
auto layer = std::make_unique<arm_compute::NELogSoftmaxLayer>(memoryManager);
- int aclAxis = ComputeSoftmaxAclAxis<int>(m_Data.m_Parameters, info.m_InputTensorInfos[0]);
+ int aclAxis = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]);
layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis);
m_LogSoftmaxLayer.reset(layer.release());
}