





import argparse

import torch

from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()




def    __UpperCAmelCase(      lowercase_ ,    lowercase_ ,    lowercase_      ):
       # Construct model
       if gpta_config_file == "":
              _lowerCamelCase							:     Union[str, Any]	=		GPTaConfig()
       else:
              _lowerCamelCase							:     Optional[int]	=		GPTaConfig.from_json_file(lowercase_      )
       _lowerCamelCase							:     Optional[int]	=		GPTaModel(lowercase_      )

       # Load weights from numpy
       load_tf_weights_in_gpta(lowercase_ ,    lowercase_ ,    lowercase_      )

       # Save pytorch-model
       _lowerCamelCase							:     Union[str, Any]	=		pytorch_dump_folder_path + '''/''' + WEIGHTS_NAME
       _lowerCamelCase							:     Any	=		pytorch_dump_folder_path + '''/''' + CONFIG_NAME
       print(F"""Save PyTorch model to {pytorch_weights_dump_path}"""      )
       torch.save(model.state_dict() ,    lowercase_      )
       print(F"""Save configuration file to {pytorch_config_dump_path}"""      )
       with open(lowercase_ ,    '''w''' ,    encoding='''utf-8'''      ) as f:
              f.write(config.to_json_string()      )


if __name__ == "__main__":
       _lowerCamelCase			       =      argparse.ArgumentParser()
       # Required parameters
       parser.add_argument(
           '--gpt2_checkpoint_path', default=None, type=str, required=True, help='Path to the TensorFlow checkpoint path.'
       )
       parser.add_argument(
           '--pytorch_dump_folder_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
       )
       parser.add_argument(
           '--gpt2_config_file',
           default='',
           type=str,
           help=(
               'An optional config json file corresponding to the pre-trained OpenAI model. \n'
               'This specifies the model architecture.'
           ),
       )
       _lowerCamelCase			       =      parser.parse_args()
       convert_gpta_checkpoint_to_pytorch(args.gpta_checkpoint_path, args.gpta_config_file, args.pytorch_dump_folder_path)








import warnings

from .generation import TFGenerationMixin







class 			__A       (      lowerCamelCase__  ):




      """simple docstring"""







      warnings.warn(
          """Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
          """be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead.""" ,lowerCamelCase__ ,)

