Update autoregressive/models/generate.py

autoregressive/models/generate.py

@@ -68,6 +68,8 @@ def sample(logits, temperature: float=1.0, top_k: int=2000, top_p: float=1.0, sa
     # mask = (probs == values).float()
     # probs = probs * (1 - mask)
     if sample_logits:
+        print(f'inf：{torch.any(torch.isinf(probs))}')
+        print(f'nan: {torch.any(torch.isnan(probs))}')
         # add to fix 'nan' and 'inf'
         probs = torch.clamp(probs, min=0, max=None)  
         probs = probs / probs.sum()