


import os
import re
import shutil
from argparse import ArgumentParser, Namespace

from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger


UpperCAmelCase_   :				Optional[Any]						      = '<<<<<<< This should probably be modified because it mentions: '

UpperCAmelCase_   :				List[str]						      = '=======\n>>>>>>>\n'

UpperCAmelCase_   :				int						      = [
    'TextEncoderConfig',
    'ByteTextEncoder',
    'SubwordTextEncoder',
    'encoder_config',
    'maybe_build_from_corpus',
    'manual_dir',
]

UpperCAmelCase_   :				Tuple						      = [
    # (pattern, replacement)
    # Order is important here for some replacements
    (R'tfds\.core', R'datasets'),
    (R'tf\.io\.gfile\.GFile', R'open'),
    (R'tf\.([\w\d]+)', R'datasets.Value(\'\1\')'),
    (R'tfds\.features\.Text\(\)', R'datasets.Value(\'string\')'),
    (R'tfds\.features\.Text\(', R'datasets.Value(\'string\'),'),
    (R'features\s*=\s*tfds.features.FeaturesDict\(', R'features=datasets.Features('),
    (R'tfds\.features\.FeaturesDict\(', R'dict('),
    (R'The TensorFlow Datasets Authors', R'The TensorFlow Datasets Authors and the HuggingFace Datasets Authors'),
    (R'tfds\.', R'datasets.'),
    (R'dl_manager\.manual_dir', R'self.config.data_dir'),
    (R'self\.builder_config', R'self.config'),
]







def  SCREAMING_SNAKE_CASE_		(    __A				:    Namespace       )			->	List[str]:

       """simple docstring"""

       return ConvertCommand(args.tfds_path						,					args.datasets_directory       )
class 				SCREAMING_SNAKE_CASE__						(       lowercase__    ):
      @staticmethod
      def  SCREAMING_SNAKE_CASE							( SCREAMING_SNAKE_CASE__       : ArgumentParser  )	->    Dict:
             a_      :	Dict							=						parser.add_parser(
                 'convert'  ,							help='Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset.'  ,							)
             train_parser.add_argument(
                 '--tfds_path'  ,							type=SCREAMING_SNAKE_CASE__  ,							required=SCREAMING_SNAKE_CASE__  ,							help='Path to a TensorFlow Datasets folder to convert or a single tfds file to convert.'  ,							)
             train_parser.add_argument(
                 '--datasets_directory'  ,							type=SCREAMING_SNAKE_CASE__  ,							required=SCREAMING_SNAKE_CASE__  ,							help='Path to the HuggingFace Datasets folder.'  )
             train_parser.set_defaults(func=SCREAMING_SNAKE_CASE__  )
      def __init__( self       : Optional[int]  ,							SCREAMING_SNAKE_CASE__       : str  ,							SCREAMING_SNAKE_CASE__       : str  ,							*SCREAMING_SNAKE_CASE__       : List[str]  )	->    List[str]:
             a_      :	int							=						get_logger('datasets-cli/converting'  )

             a_      :	Tuple							=						tfds_path
             a_      :	str							=						datasets_directory

      def  SCREAMING_SNAKE_CASE							( self       : Optional[int]  )	->    List[Any]:
             if os.path.isdir(self._tfds_path  ):
                    a_      :	Optional[int]							=						os.path.abspath(self._tfds_path  )
             elif os.path.isfile(self._tfds_path  ):
                    a_      :	int							=						os.path.dirname(self._tfds_path  )
             else:
                    raise ValueError('--tfds_path is neither a directory nor a file. Please check path.'  )

             a_      :	Optional[Any]							=						os.path.abspath(self._datasets_directory  )

             self._logger.info(F"""Converting datasets from {abs_tfds_path} to {abs_datasets_path}"""  )

             a_      :	str							=						[]
             a_      :	Optional[Any]							=						[]
             a_      :	Tuple							=						{}

             if os.path.isdir(self._tfds_path  ):
                    a_      :	Dict							=						os.listdir(SCREAMING_SNAKE_CASE__  )
             else:
                    a_      :	Union[str, Any]							=						[os.path.basename(self._tfds_path  )]

             for f_name in file_names:
                    self._logger.info(F"""Looking at file {f_name}"""  )
                    a_      :	int							=						os.path.join(SCREAMING_SNAKE_CASE__  ,							SCREAMING_SNAKE_CASE__  )
                    a_      :	Optional[int]							=						os.path.join(SCREAMING_SNAKE_CASE__  ,							SCREAMING_SNAKE_CASE__  )

                    if not os.path.isfile(SCREAMING_SNAKE_CASE__  ) or "__init__" in f_name or "_test" in f_name or ".py" not in f_name:
                           self._logger.info('Skipping file'  )
                           continue

                    with open(SCREAMING_SNAKE_CASE__  ,							encoding='utf-8'  ) as f:
                           a_      :	Optional[int]							=						f.readlines()

                    a_      :	Dict							=						[]
                    a_      :	int							=						False
                    a_      :	Any							=						False
                    a_      :	int							=						[]
                    for line in lines:
                           a_      :	List[Any]							=						line

                           # Convert imports
                           if "import tensorflow.compat.v2 as tf" in out_line:
                                  continue
                           elif "@tfds.core" in out_line:
                                  continue
                           elif "builder=self" in out_line:
                                  continue
                           elif "import tensorflow_datasets.public_api as tfds" in out_line:
                                  a_      :	Any							=						'import datasets\n'
                           elif "import tensorflow" in out_line:
                                  # order is important here
                                  a_      :	int							=						''
                                  continue
                           elif "from absl import logging" in out_line:
                                  a_      :	Dict							=						'from datasets import logging\n'
                           elif "getLogger" in out_line:
                                  a_      :	List[Any]							=						out_line.replace('getLogger'  ,							'get_logger'  )
                           elif any(expression in out_line for expression in TO_HIGHLIGHT  ):
                                  a_      :	str							=						True
                                  a_      :	List[Any]							=						list(filter(lambda SCREAMING_SNAKE_CASE__  : e in out_line  ,							SCREAMING_SNAKE_CASE__  )  )
                                  out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(SCREAMING_SNAKE_CASE__  ) + '\n'  )
                                  out_lines.append(SCREAMING_SNAKE_CASE__  )
                                  out_lines.append(SCREAMING_SNAKE_CASE__  )
                                  continue
                           else:
                                  for pattern, replacement in TO_CONVERT:
                                         a_      :	List[Any]							=						re.sub(SCREAMING_SNAKE_CASE__  ,							SCREAMING_SNAKE_CASE__  ,							SCREAMING_SNAKE_CASE__  )

                # Take care of saving utilities (to later move them together with main script)
                           if "tensorflow_datasets" in out_line:
                                  a_      :	List[Any]							=						re.match(r'from\stensorflow_datasets.*import\s([^\.\r\n]+)'  ,							SCREAMING_SNAKE_CASE__  )
                                  tfds_imports.extend(imp.strip() for imp in match.group(1  ).split(','  )  )
                                  a_      :	int							=						'from . import ' + match.group(1  )

                           # Check we have not forget anything
                           if "tf." in out_line or "tfds." in out_line or "tensorflow_datasets" in out_line:
                                  raise ValueError(F"""Error converting {out_line.strip()}"""  )

                           if "GeneratorBasedBuilder" in out_line or "BeamBasedBuilder" in out_line:
                                  a_      :	str							=						True
                           out_lines.append(SCREAMING_SNAKE_CASE__  )

                    if is_builder or "wmt" in f_name:
                           # We create a new directory for each dataset
                           a_      :	str							=						f_name.replace('.py'  ,							''  )
                           a_      :	List[Any]							=						os.path.join(SCREAMING_SNAKE_CASE__  ,							SCREAMING_SNAKE_CASE__  )
                           a_      :	Optional[int]							=						os.path.join(SCREAMING_SNAKE_CASE__  ,							SCREAMING_SNAKE_CASE__  )
                           os.makedirs(SCREAMING_SNAKE_CASE__  ,							exist_ok=SCREAMING_SNAKE_CASE__  )
                           self._logger.info(F"""Adding directory {output_dir}"""  )
                           imports_to_builder_map.update({imp: output_dir for imp in tfds_imports}  )
                    else:
                           # Utilities will be moved at the end
                           utils_files.append(SCREAMING_SNAKE_CASE__  )

                    if needs_manual_update:
                           with_manual_update.append(SCREAMING_SNAKE_CASE__  )

                    with open(SCREAMING_SNAKE_CASE__  ,							'w'  ,							encoding='utf-8'  ) as f:
                           f.writelines(SCREAMING_SNAKE_CASE__  )
                    self._logger.info(F"""Converted in {output_file}"""  )

             for utils_file in utils_files:
                    try:
                           a_      :	Tuple							=						os.path.basename(SCREAMING_SNAKE_CASE__  )
                           a_      :	Tuple							=						imports_to_builder_map[f_name.replace('.py'  ,							''  )]
                           self._logger.info(F"""Moving {dest_folder} to {utils_file}"""  )
                           shutil.copy(SCREAMING_SNAKE_CASE__  ,							SCREAMING_SNAKE_CASE__  )
                    except KeyError:
                           self._logger.error(F"""Cannot find destination folder for {utils_file}. Please copy manually."""  )

             if with_manual_update:
                    for file_path in with_manual_update:
                           self._logger.warning(
                               F"""You need to manually update file {file_path} to remove configurations using 'TextEncoderConfig'."""  )






import random
class 				SCREAMING_SNAKE_CASE__						:
      @staticmethod
      def  SCREAMING_SNAKE_CASE							( SCREAMING_SNAKE_CASE__       : str  )	->    tuple[list[int], list[int]]:
             a_      :	int							=						[ord(SCREAMING_SNAKE_CASE__  ) for i in text]
             a_      :	Any							=						[]
             a_      :	Optional[int]							=						[]
             for i in plain:
                    a_      :	Tuple							=						random.randint(1  ,							3_0_0  )
                    a_      :	Optional[int]							=						(i + k) * k
                    cipher.append(SCREAMING_SNAKE_CASE__  )
                    key.append(SCREAMING_SNAKE_CASE__  )
             return cipher, key

      @staticmethod
      def  SCREAMING_SNAKE_CASE							( SCREAMING_SNAKE_CASE__       : list[int]  ,							SCREAMING_SNAKE_CASE__       : list[int]  )	->    str:
             a_      :	List[Any]							=						[]
             for i in range(len(SCREAMING_SNAKE_CASE__  )  ):
                    a_      :	str							=						int((cipher[i] - (key[i]) ** 2) / key[i]  )
                    plain.append(chr(SCREAMING_SNAKE_CASE__  )  )
             return "".join(SCREAMING_SNAKE_CASE__  )


if __name__ == "__main__":
   UpperCAmelCase_      ,     UpperCAmelCase_   :				Any						      = Onepad().encrypt('Hello')
   print(c, k)
   print(Onepad().decrypt(c, k))


