Update autoregressive/models/generate.py

autoregressive/models/generate.py

@@ -70,8 +70,9 @@ def sample(logits, temperature: float=1.0, top_k: int=2000, top_p: float=1.0, sa
     if sample_logits:
         # add to fix 'nan' and 'inf'
         probs = torch.where(torch.isnan(probs), torch.tensor(0.0), probs)
-        probs = torch.clamp(probs, min=0, max=None)  
-        # probs = probs / probs.sum()  
+        probs = torch.clamp(probs, min=0, max=None)   
+        print(probs.sum())
+        print(probs)
         print(f'inf：{torch.any(torch.isinf(probs))}')
         print(f'nan: {torch.any(torch.isnan(probs))}')