IVGCVSW-2354 Caffe SqueezeNet through armnn Cl and Neon

 * Compute Softmax Acl axis for Cl and Neon
 * Add unittests for Softmax in 3D and 4D
 * Correct input and output layer names in CaffeSqueezeNet inference test

Change-Id: I2d369d9a2db19c40f2af3341039dd33f0c5637b1
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>

1 files changed, 3 insertions, 1 deletions

diff --git a/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp b/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp
index d9c78bbd43..afc6135e0f 100644
--- a/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp
+++ b/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp
@@ -7,6 +7,7 @@
 
 #include "NeonWorkloadUtils.hpp"
 
+#include <aclCommon/ArmComputeUtils.hpp>
 #include <arm_compute/runtime/NEON/functions/NESoftmaxLayer.h>
 
 namespace armnn
@@ -22,8 +23,9 @@ NeonSoftmaxFloatWorkload::NeonSoftmaxFloatWorkload(const SoftmaxQueueDescriptor&
     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();
 
+    unsigned int aclAxis = ComputeSoftmaxAclAxis(info.m_InputTensorInfos[0]);
     auto layer = std::make_unique<arm_compute::NESoftmaxLayer>(memoryManager);
-    layer->configure(&input, &output, m_Data.m_Parameters.m_Beta);
+    layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis);
     m_SoftmaxLayer.reset(layer.release());
 }