diff --git a/nntrainer/layers/layer_context.cpp b/nntrainer/layers/layer_context.cpp
index 9091e0b1e2..ed3668598d 100644
--- a/nntrainer/layers/layer_context.cpp
+++ b/nntrainer/layers/layer_context.cpp
@@ -52,7 +52,7 @@ InitLayerContext::InitLayerContext(
   prefix(prefix_),
   tensor_type(tensor_type_),
   loss_scale(loss_scale_),
-  mode(mode_){
+  mode(mode_) {
   NNTR_THROW_IF(!validate(), std::invalid_argument)
     << "Invalid init context name: " << name
     << " num inputs: " << getNumInputs();
@@ -292,7 +292,6 @@ const Tensor RunLayerContext::getIncomingDerivative(unsigned int idx) const {
   return getOutputGrad(idx);
 }
 
-
 /**
  * @brief Get the Input tensor object
  *
diff --git a/nntrainer/tensor/manager.cpp b/nntrainer/tensor/manager.cpp
index 4a2838d05e..f77a012b49 100644
--- a/nntrainer/tensor/manager.cpp
+++ b/nntrainer/tensor/manager.cpp
@@ -455,8 +455,8 @@ std::vector<Weight *> Manager::requestWeights(
          * reduce the memory.
          */
         bool is_wgrad = true;
-        if (Weight::isGradientClipByGlobalNorm(clip_by_global_norm))
-          is_wgrad = false;
+        //        if (Weight::isGradientClipByGlobalNorm(clip_by_global_norm))
+        //          is_wgrad = false;
         grad = tensor_pool.request(name + Var_Grad::grad_suffix, dim_g,
                                    grad_exec_order, grad_ls,
                                    Tensor::Initializer::ZEROS, is_wgrad);
diff --git a/nntrainer/tensor/tensor.cpp b/nntrainer/tensor/tensor.cpp
index 827ba7e979..cfab9bb488 100644
--- a/nntrainer/tensor/tensor.cpp
+++ b/nntrainer/tensor/tensor.cpp
@@ -3319,13 +3319,17 @@ void Tensor::setValue(float val) {
 void Tensor::setZero() {
   if (dim.getDataType() == ml::train::TensorDim::DataType::FP32) {
     if (contiguous)
-      sscal(size(), 0, getData<float>(), 1);
+      //      sscal(size(), 0, getData<float>(), 1);
+      /// @note we cannot use sscal, when we set zero. if the data is inf or
+      /// NaN, then the inf or NaN still remain.
+      memset(getData<_FP16>(), 0, sizeof(float) * size());
     else
       apply_i<float>([](float val) -> float { return 0; });
   } else if (dim.getDataType() == ml::train::TensorDim::DataType::FP16) {
 #ifdef ENABLE_FP16
     if (contiguous)
-      sscal(size(), 0, getData<_FP16>(), 1);
+      // sscal(size(), 0, getData<_FP16>(), 1);
+      memset(getData<_FP16>(), 0, sizeof(_FP16) * size());
     else
       apply_i<_FP16>([](_FP16 val) -> _FP16 { return 0; });
 #else