diff --git a/assignment 4/nmt_model.py b/assignment 4/nmt_model.py
index 0e4b7c5..dcebbfc 100644
--- a/assignment 4/nmt_model.py	
+++ b/assignment 4/nmt_model.py	
@@ -336,6 +336,18 @@ def step(self, Ybar_t: torch.Tensor,
 
         ### END YOUR CODE
 
+       
+        dec_state = self.decoder(Ybar_t,dec_state)
+        dec_hidden, dec_cell = dec_state
+        dec_hidden = torch.unsqueeze(dec_hidden,dim=1)
+       
+        enc_hiddens_proj = torch.transpose(enc_hiddens_proj,1,2)
+       
+        e_t = torch.bmm(dec_hidden,enc_hiddens_proj)
+        e_t = torch.squeeze(e_t,dim=1)
+        
+         
+
         # Set e_t to -inf where enc_masks has 1
         if enc_masks is not None:
             e_t.data.masked_fill_(enc_masks.bool(), -float('inf'))
@@ -366,8 +378,22 @@ def step(self, Ybar_t: torch.Tensor,
         ###         https://pytorch.org/docs/stable/torch.html#torch.cat
         ###     Tanh:
         ###         https://pytorch.org/docs/stable/torch.html#torch.tanh
+        
+        alpha_t = nn.functional.softmax(e_t,dim=1)
+        
+        alpha_t = torch.unsqueeze(alpha_t,dim=1)
 
-
+        a_t = torch.bmm(alpha_t,enc_hiddens)
+        
+        a_t = torch.squeeze(a_t,1)
+
+       
+        dec_hidden = torch.squeeze(dec_hidden,1)
+        U_t = torch.cat((a_t,dec_hidden),dim=1)
+        V_t= self.combined_output_projection(U_t)
+        O_t = nn.functional.tanh(V_t)
+        O_t = self.dropout(O_t)
+        
         ### END YOUR CODE
 
         combined_output = O_t