1013 update

Amadeus/sampling_utils.py

@@ -1,6 +1,6 @@
 import torch
 import torch.nn.functional as F
-
+  
 def top_p_sampling(logits, thres=0.9):
   sorted_logits, sorted_indices = torch.sort(logits, descending=True)
   cum_probs = torch.cumsum(F.softmax(sorted_logits, dim=-1), dim=-1)
@@ -84,7 +84,7 @@ def sample_with_prob(logits, sampling_method, threshold, temperature):
     #  temporarily apply the sampling method to logits
     logits = logits / temperature
     # logits = add_gumbel_noise(logits, temperature)
-  
+    
     if sampling_method == "top_p":
         modified_logits = top_p_sampling(logits, thres=threshold)
     elif sampling_method == "typical":