



import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()

def 	_lowerCAmelCase (    A__    ,	A__    ,	A__						):
      # Initialise PyTorch model
      lowercase__  =	TaConfig.from_json_file(A__						)
      print(F'''Building PyTorch model from configuration: {config}'''						)
      lowercase__  =	TaForConditionalGeneration(A__						)

      # Load weights from tf checkpoint
      load_tf_weights_in_ta(A__    ,	A__    ,	A__						)

      # Save pytorch-model
      print(F'''Save PyTorch model to {pytorch_dump_path}'''						)
      model.save_pretrained(A__						)


if __name__ == "__main__":
       a__   :					Optional[Any] 						=      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(
           "--config_file",
           default=None,
           type=str,
           required=True,
           help=(
               "The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture."
           ),
       )
       parser.add_argument(
           "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
       )
       a__   :					Dict 						=      parser.parse_args()
       convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)





a__   :					Tuple 						=      "Tobias Carryer"

from time import time



class    UpperCAmelCase__:

   '''simple docstring'''




   def __init__(    self	:      str      ,					lowerCAmelCase	:      List[str]      ,					lowerCAmelCase	:      Any      ,					lowerCAmelCase	:      str      ,					lowerCAmelCase	:      str=int(time()))						->					List[Any]:  # noqa: B008




         """simple docstring"""

         lowercase__  =	multiplier
         lowercase__  =	increment
         lowercase__  =	modulo
         lowercase__  =	seed



   def       UpperCAmelCase		(    self	:      int)						->					Tuple:




         """simple docstring"""

         lowercase__  =	(self.multiplier * self.seed + self.increment) % self.modulo
         return self.seed


if __name__ == "__main__":
       # Show the LCG in action.
       a__   :					str 						=      LinearCongruentialGenerator(1_66_45_25, 10_13_90_42_23, 2 << 31)
       while True:
              print(lcg.next_number())
