diff --git a/Project_Model/Libs/Transformer/Classes/Decoder.py b/Project_Model/Libs/Transformer/Classes/Decoder.py
index 97cd148..10422b8 100644
--- a/Project_Model/Libs/Transformer/Classes/Decoder.py
+++ b/Project_Model/Libs/Transformer/Classes/Decoder.py
@@ -19,7 +19,7 @@ class Decoder(nn.Module):
         self.__attention_heads = number_of_attention_heads
         super().__init__()
 
-        
+
 
         self.__masked_attention = MultiHeadAttention(
             embedding_dimension, number_of_attention_heads, dropout=0.1
@@ -68,12 +68,12 @@ class Decoder(nn.Module):
         )
 
         # 2) Dropout
-        # DROPPED_MASKED_ATTENTION = self.__dropout(MASKED_ATTENTION)
-        # del MASKED_ATTENTION
+        DROPPED_MASKED_ATTENTION = self.__dropout(MASKED_ATTENTION)
+        del MASKED_ATTENTION
 
         # 3) Residual Connection
-        x = x + MASKED_ATTENTION
-        del MASKED_ATTENTION
+        x = x + DROPPED_MASKED_ATTENTION
+        del DROPPED_MASKED_ATTENTION
 
         # 4) Layer Normalization
         x = self.__layer_norm_1(x)
@@ -86,12 +86,12 @@ class Decoder(nn.Module):
             )
 
             # 6) Dropout
-            # DROPPED_CROSS_ATTENTION = self.__dropout(CROSS_ATTENTION)
-            # del CROSS_ATTENTION
+            DROPPED_CROSS_ATTENTION = self.__dropout(CROSS_ATTENTION)
+            del CROSS_ATTENTION
 
             # 7) Residual Connection
-            x = x + CROSS_ATTENTION
-            del CROSS_ATTENTION
+            x = x + DROPPED_CROSS_ATTENTION
+            del DROPPED_CROSS_ATTENTION
 
             # 8) Layer Normalization
             x = self.__layer_norm_2(x)
@@ -100,12 +100,12 @@ class Decoder(nn.Module):
         FEED_FORWARD = self.__feed_forward_network(x)
 
         # 10) Dropout
-        # DROPPED_FEED_FORWARD = self.__dropout(FEED_FORWARD)
-        # del FEED_FORWARD
+        DROPPED_FEED_FORWARD = self.__dropout(FEED_FORWARD)
+        del FEED_FORWARD
 
         # 11) Residual Connection
-        x = x + FEED_FORWARD
-        del FEED_FORWARD
+        x = x + DROPPED_FEED_FORWARD
+        del DROPPED_FEED_FORWARD
 
         # 12) Layer Normalization
         x = self.__layer_norm_3(x)
diff --git a/Project_Model/Libs/Transformer/Classes/Encoder.py b/Project_Model/Libs/Transformer/Classes/Encoder.py
index 78fca5e..d5d6498 100644
--- a/Project_Model/Libs/Transformer/Classes/Encoder.py
+++ b/Project_Model/Libs/Transformer/Classes/Encoder.py
@@ -43,12 +43,12 @@ class Encoder(
         ATTENTION = self.__attention(x, x, x, key_padding_mask=padding_mask)
 
         # 2) Dropout
-        # DROPPED_ATTENTION = self.__dropout(ATTENTION)
-        # del ATTENTION
+        DROPPED_ATTENTION = self.__dropout(ATTENTION)
+        del ATTENTION
 
         # 3) Residual Connection
-        x = x + ATTENTION
-        del ATTENTION
+        x = x + DROPPED_ATTENTION
+        del DROPPED_ATTENTION
 
         # 4) Layer Normalization
         x = self.__layer_norm_1(x)
@@ -57,12 +57,12 @@ class Encoder(
         FEED_FORWARD = self.__feed_forward(x)
 
         # 6) Dropout
-        # DROPPED_FEED_FORWARD = self.__dropout(FEED_FORWARD)
-        # del FEED_FORWARD
+        DROPPED_FEED_FORWARD = self.__dropout(FEED_FORWARD)
+        del FEED_FORWARD
 
         # 7) Residual Connection
-        x = x + FEED_FORWARD
-        del FEED_FORWARD
+        x = x + DROPPED_FEED_FORWARD
+        del DROPPED_FEED_FORWARD
 
         # 8) Layer Normalization
         x = self.__layer_norm_2(x)
diff --git a/Project_Model/Libs/Transformer/Classes/FeedForwardNetwork.py b/Project_Model/Libs/Transformer/Classes/FeedForwardNetwork.py
index a5a29ac..4cfc7e6 100644
--- a/Project_Model/Libs/Transformer/Classes/FeedForwardNetwork.py
+++ b/Project_Model/Libs/Transformer/Classes/FeedForwardNetwork.py
@@ -35,7 +35,7 @@ class FeedForwardNetwork(nn.Module):
         x = self.__relu(x)
 
         # 3) Dropout
-        # x = self.__dropout(x)
+        x = self.__dropout(x)
 
         # 4) Linear Layer
         x = self.__fully_connected_2(x)