
'''simple docstring'''



import argparse

from transformers import ConvBertConfig, ConvBertModel, TFConvBertModel, load_tf_weights_in_convbert
from transformers.utils import logging


logging.set_verbosity_info()
def 				lowerCAmelCase_		(			SCREAMING_SNAKE_CASE_      , SCREAMING_SNAKE_CASE_      , SCREAMING_SNAKE_CASE_  )       ->       Any:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE       	=			ConvBertConfig.from_json_file(SCREAMING_SNAKE_CASE_  )
   _SCREAMING_SNAKE_CASE       	=			ConvBertModel(SCREAMING_SNAKE_CASE_  )

   _SCREAMING_SNAKE_CASE       	=			load_tf_weights_in_convbert(SCREAMING_SNAKE_CASE_      , SCREAMING_SNAKE_CASE_      , SCREAMING_SNAKE_CASE_  )
   model.save_pretrained(SCREAMING_SNAKE_CASE_  )

   _SCREAMING_SNAKE_CASE       	=			TFConvBertModel.from_pretrained(SCREAMING_SNAKE_CASE_      , from_pt=SCREAMING_SNAKE_CASE_  )
   tf_model.save_pretrained(SCREAMING_SNAKE_CASE_  )


if __name__ == "__main__":
     UpperCamelCase__ :						List[str]    							=					argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
     )
     parser.add_argument(
         "--convbert_config_file",
         default=None,
         type=str,
         required=True,
         help=(
             "The config json file corresponding to the pre-trained ConvBERT model. \n"
             "This specifies the model architecture."
         ),
     )
     parser.add_argument(
         "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
     )
     UpperCamelCase__ :						Optional[Any]    							=					parser.parse_args()
     convert_orig_tfa_checkpoint_to_pytorch(args.tf_checkpoint_path, args.convbert_config_file, args.pytorch_dump_path)








'''simple docstring'''



def 				lowerCAmelCase_		(			SCREAMING_SNAKE_CASE_  )       ->       str:




   """simple docstring"""
   return " ".join(sorted(set(sentence.split()  )  )  )


if __name__ == "__main__":
     import doctest

     doctest.testmod()






