





'''simple docstring'''

import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()





def lowerCamelCase						(					__lowerCamelCase			:   List[Any] ,	__lowerCamelCase			:   Optional[Any]   )						->Dict:
    _SCREAMING_SNAKE_CASE     =      CanineConfig()
    _SCREAMING_SNAKE_CASE     =      CanineModel(SCREAMING_SNAKE_CASE_   )
    model.eval()

    print(F'Building PyTorch model from configuration: {config}'   )

    # Load weights from tf checkpoint
    load_tf_weights_in_canine(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_   )

    # Save pytorch-model (weights and configuration)
    print(F'Save PyTorch model to {pytorch_dump_path}'   )
    model.save_pretrained(SCREAMING_SNAKE_CASE_   )

    # Save tokenizer files
    _SCREAMING_SNAKE_CASE     =      CanineTokenizer()
    print(F'Save tokenizer files to {pytorch_dump_path}'   )
    tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_   )


if __name__ == "__main__":
      lowercase_         =			argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          """--tf_checkpoint_path""",
          default=None,
          type=str,
          required=True,
          help="""Path to the TensorFlow checkpoint. Should end with model.ckpt""",
      )
      parser.add_argument(
          """--pytorch_dump_path""",
          default=None,
          type=str,
          required=True,
          help="""Path to a folder where the PyTorch model will be placed.""",
      )
      lowercase_         =			parser.parse_args()
      convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)










'''simple docstring'''

import os
import sys
import time

from . import transposition_cipher as trans_cipher





def lowerCamelCase						(					)						->None:
    _SCREAMING_SNAKE_CASE     =      """Prehistoric Men.txt"""
    _SCREAMING_SNAKE_CASE     =      """Output.txt"""
    _SCREAMING_SNAKE_CASE     =      int(input("""Enter key: """   )   )
    _SCREAMING_SNAKE_CASE     =      input("""Encrypt/Decrypt [e/d]: """   )

    if not os.path.exists(__lowerCamelCase   ):
        print(F'File {input_file} does not exist. Quitting...'   )
        sys.exit()
    if os.path.exists(__lowerCamelCase   ):
        print(F'Overwrite {output_file}? [y/n]'   )
        _SCREAMING_SNAKE_CASE     =      input("""> """   )
        if not response.lower().startswith("""y"""   ):
            sys.exit()

    _SCREAMING_SNAKE_CASE     =      time.time()
    if mode.lower().startswith("""e"""   ):
        with open(__lowerCamelCase   ) as f:
            _SCREAMING_SNAKE_CASE     =      f.read()
        _SCREAMING_SNAKE_CASE     =      trans_cipher.encrypt_message(__lowerCamelCase ,	__lowerCamelCase   )
    elif mode.lower().startswith("""d"""   ):
        with open(__lowerCamelCase   ) as f:
            _SCREAMING_SNAKE_CASE     =      f.read()
        _SCREAMING_SNAKE_CASE     =      trans_cipher.decrypt_message(__lowerCamelCase ,	__lowerCamelCase   )

    with open(__lowerCamelCase ,	"""w"""   ) as output_obj:
        output_obj.write(__lowerCamelCase   )

    _SCREAMING_SNAKE_CASE     =      round(time.time() - start_time ,	2   )
    print(("""Done (""", total_time, """seconds )""")   )


if __name__ == "__main__":
      main()



