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, 4 insertions, 2 deletions

diff --git a/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp b/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp
index f780589075..7f295d6548 100644
--- a/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp
+++ b/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp
@@ -4,9 +4,10 @@
 //
 
 #include "NeonSoftmaxUint8Workload.hpp"
-
 #include "NeonWorkloadUtils.hpp"
 
+#include <aclCommon/ArmComputeUtils.hpp>
+
 #include <arm_compute/runtime/NEON/functions/NESoftmaxLayer.h>
 
 namespace armnn
@@ -29,9 +30,10 @@ NeonSoftmaxUint8Workload::NeonSoftmaxUint8Workload(const SoftmaxQueueDescriptor&
         throw InvalidArgumentException(
             "Invalid quantization for output. Only scale = 1.0f / 256.0f and offset = 0 supported");
     }
+    unsigned int aclAxis = ComputeSoftmaxAclAxis(info.m_InputTensorInfos[0]);
 
     auto layer = std::make_unique<arm_compute::NESoftmaxLayer>(memoryManager);
-    layer->configure(&input, &output, descriptor.m_Parameters.m_Beta);
+    layer->configure(&input, &output, descriptor.m_Parameters.m_Beta, aclAxis);
     m_SoftmaxLayer.reset(layer.release());
 }