[ Bug ] Fix the bug read the weight for batch normalization layer

There is bug when the model loads the data for the batch normalziation
layer.

During the setup the requestWeights in manager, it add the max
execution order for graddient for gradient clipping, but variable
weight also added. This pr fixs it.

**Self evaluation:**
1. Build test:	 [X]Passed [ ]Failed [ ]Skipped
2. Run test:	 [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: jijoong.moon <jijoong.moon@samsung.com>

diff --git a/nntrainer/tensor/manager.cpp b/nntrainer/tensor/manager.cpp
index 536a273..8496207 100644 (file)
--- a/nntrainer/tensor/manager.cpp
+++ b/nntrainer/tensor/manager.cpp
@@ -398,7 +398,9 @@ std::vector<Weight *> Manager::requestWeights(
      */
     if (Weight::isGradientClipByGlobalNorm(clip_by_global_norm)) {
       grad_exec_order.push_back(TensorPool::PERSIST_END_ORDER);
-      var_exec_order.push_back(TensorPool::PERSIST_END_ORDER);
+      // TODO: We need double check if it is OK not to add PERSIST_END_ORDER
+      // here or add other conditions
+      // var_exec_order.push_back(TensorPool::PERSIST_END_ORDER);
     }
 
     Tensor *var = nullptr, *grad = nullptr;