fix auto models

pytorch_transformers/modeling_tf_auto.py

@@ -22,7 +22,7 @@ from .modeling_tf_bert import TFBertModel, TFBertForMaskedLM, TFBertForSequenceC
 from .modeling_tf_openai import TFOpenAIGPTModel, TFOpenAIGPTLMHeadModel
 from .modeling_tf_gpt2 import TFGPT2Model, TFGPT2LMHeadModel
 from .modeling_tf_transfo_xl import TFTransfoXLModel, TFTransfoXLLMHeadModel
-from .modeling_tf_xlnet import TFXLNetModel, TFXLNetLMHeadModel, TFXLNetForSequenceClassification, TFXLNetForQuestionAnswering
+from .modeling_tf_xlnet import TFXLNetModel, TFXLNetLMHeadModel, TFXLNetForSequenceClassification, TFXLNetForQuestionAnsweringSimple
 from .modeling_tf_xlm import TFXLMModel, TFXLMWithLMHeadModel, TFXLMForSequenceClassification, TFXLMForQuestionAnsweringSimple
 from .modeling_tf_roberta import TFRobertaModel, TFRobertaForMaskedLM, TFRobertaForSequenceClassification
 from .modeling_tf_distilbert import TFDistilBertModel, TFDistilBertForQuestionAnswering, TFDistilBertForMaskedLM, TFDistilBertForSequenceClassification
@@ -493,9 +493,9 @@ class TFAutoModelForQuestionAnswering(object):
         elif 'bert' in pretrained_model_name_or_path:
             return TFBertForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
         elif 'xlnet' in pretrained_model_name_or_path:
-            return TFXLNetForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
+            return TFXLNetForQuestionAnsweringSimple.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
         elif 'xlm' in pretrained_model_name_or_path:
-            return TFXLMForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
+            return TFXLMForQuestionAnsweringSimple.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
 
         raise ValueError("Unrecognized model identifier in {}. Should contains one of "
                          "'bert', 'xlnet', 'xlm'".format(pretrained_model_name_or_path))