


"""simple docstring"""






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       A_   (   _lowerCAmelCase     :					Tuple,     _lowerCAmelCase     :					str,     _lowerCAmelCase     :					Any       ):






     """simple docstring"""

     if gpta_config_file == "":
          _a    	=				GPTaConfig()
     else:
          _a    	=				GPTaConfig.from_json_file(_lowerCAmelCase       )
     _a    	=				GPTaModel(_lowerCAmelCase       )

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

     # Save pytorch-model
     _a    	=				pytorch_dump_folder_path + '''/''' + WEIGHTS_NAME
     _a    	=				pytorch_dump_folder_path + '''/''' + CONFIG_NAME
     print(f'Save PyTorch model to {pytorch_weights_dump_path}'       )
     torch.save(model.state_dict(),     _lowerCAmelCase       )
     print(f'Save configuration file to {pytorch_config_dump_path}'       )
     with open(_lowerCAmelCase,     '''w''',     encoding='''utf-8'''       ) as f:
          f.write(config.to_json_string()       )


if __name__ == "__main__":
   __snake_case		=       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.'''
       ),
   )
   __snake_case		=       parser.parse_args()
   convert_gpta_checkpoint_to_pytorch(args.gpta_checkpoint_path, args.gpta_config_file, args.pytorch_dump_folder_path)



"""simple docstring"""






from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels