update transfo xl example

examples/run_transfo_xl.py

@@ -28,7 +28,7 @@ import math
 
 import torch
 
-from pytorch_pretrained_bert import TransfoXLModel, TransfoXLCorpus
+from pytorch_pretrained_bert import TransfoXLLMHeadModel, TransfoXLCorpus
 
 logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s -   %(message)s',
                     datefmt = '%m/%d/%Y %H:%M:%S',
@@ -79,7 +79,7 @@ def main():
         device=device, ext_len=args.ext_len)
 
     # Load a pre-trained model
-    model = TransfoXLModel.from_pretrained(args.model_name)
+    model = TransfoXLLMHeadModel.from_pretrained(args.model_name)
     model = model.to(device)
 
     logger.info('Evaluating with bsz {} tgt_len {} ext_len {} mem_len {} clamp_len {}'.format(
@@ -139,4 +139,4 @@ def main():
     logger.info('=' * 100)
 
 if __name__ == '__main__':
-    main()
+    main()

pytorch_pretrained_bert/modeling_transfo_xl_utilities.py

@@ -169,7 +169,7 @@ class ProjectedAdaptiveLogSoftmax(nn.Module):
 
                 if i == 0:
                     if target is not None:
-                        logprob_i = head_logprob_i.gather(1, target_i[:,None]).squeeze(1)
+                        logprob_i = head_logprob_i.gather(1, target_i[:, None]).squeeze(1)
                     else:
                         out[:, :self.cutoffs[0]] = head_logprob[:, :self.cutoffs[0]]
                 else: