COMPMID-550: Adds support for branches.

Change-Id: I778007c9221ce3156400284c4039b90245eb2b7f
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/90043
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 18 insertions, 14 deletions

diff --git a/src/graph/nodes/NormalizationLayer.cpp b/src/graph/nodes/NormalizationLayer.cpp
index 47f0891dfb..319a4252b6 100644
--- a/src/graph/nodes/NormalizationLayer.cpp
+++ b/src/graph/nodes/NormalizationLayer.cpp
@@ -36,7 +36,7 @@ using namespace arm_compute::graph;
 namespace
 {
 template <typename NormalizationType, typename TensorType, TargetHint target_hint>
-std::unique_ptr<arm_compute::IFunction> instantiate_function(ITensor *input, ITensor *output, const NormalizationLayerInfo &norm_info)
+std::unique_ptr<arm_compute::IFunction> instantiate_function(arm_compute::ITensor *input, arm_compute::ITensor *output, const NormalizationLayerInfo &norm_info)
 {
     auto norm = arm_compute::support::cpp14::make_unique<NormalizationType>();
     norm->configure(
@@ -48,18 +48,18 @@ std::unique_ptr<arm_compute::IFunction> instantiate_function(ITensor *input, ITe
 }
 
 template <TargetHint                    target_hint>
-std::unique_ptr<arm_compute::IFunction> instantiate(ITensor *input, ITensor *output, const NormalizationLayerInfo &norm_info);
+std::unique_ptr<arm_compute::IFunction> instantiate(arm_compute::ITensor *input, arm_compute::ITensor *output, const NormalizationLayerInfo &norm_info);
 
 template <>
-std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::OPENCL>(ITensor *input, ITensor *output, const NormalizationLayerInfo &norm_info)
+std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::OPENCL>(arm_compute::ITensor *input, arm_compute::ITensor *output, const NormalizationLayerInfo &norm_info)
 {
-    return instantiate_function<arm_compute::CLNormalizationLayer, arm_compute::CLTensor, TargetHint::OPENCL>(input, output, norm_info);
+    return instantiate_function<arm_compute::CLNormalizationLayer, arm_compute::ICLTensor, TargetHint::OPENCL>(input, output, norm_info);
 }
 
 template <>
-std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::NEON>(ITensor *input, ITensor *output, const NormalizationLayerInfo &norm_info)
+std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::NEON>(arm_compute::ITensor *input, arm_compute::ITensor *output, const NormalizationLayerInfo &norm_info)
 {
-    return instantiate_function<arm_compute::NENormalizationLayer, arm_compute::Tensor, TargetHint::NEON>(input, output, norm_info);
+    return instantiate_function<arm_compute::NENormalizationLayer, arm_compute::ITensor, TargetHint::NEON>(input, output, norm_info);
 }
 } // namespace
 
@@ -68,25 +68,29 @@ NormalizationLayer::NormalizationLayer(const NormalizationLayerInfo norm_info)
 {
 }
 
-std::unique_ptr<arm_compute::IFunction> NormalizationLayer::instantiate_node(GraphContext &ctx, ITensor *input, ITensor *output)
+std::unique_ptr<arm_compute::IFunction> NormalizationLayer::instantiate_node(GraphContext &ctx, ITensorObject *input, ITensorObject *output)
 {
+    ARM_COMPUTE_ERROR_ON(input == nullptr || input->tensor() == nullptr);
+    ARM_COMPUTE_ERROR_ON(output == nullptr || output->tensor() == nullptr);
+
     std::unique_ptr<arm_compute::IFunction> func;
     _target_hint = ctx.hints().target_hint();
 
+    arm_compute::ITensor *in  = input->tensor();
+    arm_compute::ITensor *out = output->tensor();
+
     if(_target_hint == TargetHint::OPENCL)
     {
-        func = instantiate<TargetHint::OPENCL>(input, output, _norm_info);
-        ARM_COMPUTE_LOG("Instantiating CLNormalizationLayer");
+        func = instantiate<TargetHint::OPENCL>(in, out, _norm_info);
     }
     else
     {
-        func = instantiate<TargetHint::NEON>(input, output, _norm_info);
-        ARM_COMPUTE_LOG("Instantiating NENormalizationLayer");
+        func = instantiate<TargetHint::NEON>(in, out, _norm_info);
     }
 
-    ARM_COMPUTE_LOG(" Data Type: " << input->info()->data_type()
-                    << " Input shape: " << input->info()->tensor_shape()
-                    << " Output shape: " << output->info()->tensor_shape()
+    ARM_COMPUTE_LOG(" Data Type: " << in->info()->data_type()
+                    << " Input shape: " << in->info()->tensor_shape()
+                    << " Output shape: " << out->info()->tensor_shape()
                     << " Normalization info: " << _norm_info
                     << std::endl);