Update autoregressive/models/generate.py

autoregressive/models/generate.py

@@ -68,6 +68,10 @@ 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:
+        ### add to fix 'nan' and 'inf'
+        probs = torch.clamp(probs, min=0, max=None)  
+        probs = probs / probs.sum()  
+        ###
         idx = torch.multinomial(probs, num_samples=1)
     else:
         _, idx = torch.topk(probs, k=1, dim=-1)