



'''simple docstring'''






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

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


lowerCAmelCase:      Tuple		 =		'<<<<<<< This should probably be modified because it mentions: '

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

lowerCAmelCase:      str		 =		[
    'TextEncoderConfig',
    'ByteTextEncoder',
    'SubwordTextEncoder',
    'encoder_config',
    'maybe_build_from_corpus',
    'manual_dir',
]

lowerCAmelCase:      Any		 =		[
    # (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    lowerCamelCase__ (		_A       ):
  return ConvertCommand(args.tfds_path				,    args.datasets_directory       )

class 							a__(      lowerCamelCase__			):







    @staticmethod
    def     lowercase_ (   __snake_case				:						ArgumentParser			):
      a		:      Union[str, Any]       =  parser.add_parser(
          'convert'		,    help='Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset.'		,    )
      train_parser.add_argument(
          '--tfds_path'		,    type=__snake_case		,    required=__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=__snake_case		,    required=__snake_case		,    help='Path to the HuggingFace Datasets folder.'			)
      train_parser.set_defaults(func=__snake_case			)







    def __init__(   self				:						Union[str, Any]		,    __snake_case				:						str		,    __snake_case				:						str		,    *__snake_case				:						str			):
      a		:      Union[str, Any]       =  get_logger('datasets-cli/converting'			)

      a		:      List[str]       =  tfds_path
      a		:      Dict       =  datasets_directory







    def     lowercase_ (   self				:						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		:      Dict       =  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		:      str       =  []
      a		:      Dict       =  {}

      if os.path.isdir(self._tfds_path			):
        a		:      Dict       =  os.listdir(__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		:      Any       =  os.path.join(__snake_case		,    __snake_case			)
        a		:      Optional[Any]       =  os.path.join(__snake_case		,    __snake_case			)

        if not os.path.isfile(__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(__snake_case		,    encoding='utf-8'			) as f:
          a		:      Optional[int]       =  f.readlines()

        a		:      List[str]       =  []
        a		:      Optional[Any]       =  False
        a		:      Optional[int]       =  False
        a		:      Dict       =  []
        for line in lines:
          a		:      int       =  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		:      Tuple       =  'import datasets\n'
          elif "import tensorflow" in out_line:
            # order is important here
            a		:      str       =  ''
            continue
          elif "from absl import logging" in out_line:
            a		:      int       =  'from datasets import logging\n'
          elif "getLogger" in out_line:
            a		:      str       =  out_line.replace('getLogger'		,    'get_logger'			)
          elif any(expression in out_line for expression in TO_HIGHLIGHT			):
            a		:      List[str]       =  True
            a		:      int       =  list(filter(lambda __snake_case			: e in out_line		,    __snake_case			)			)
            out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(__snake_case			) + '\n'			)
            out_lines.append(__snake_case			)
            out_lines.append(__snake_case			)
            continue
          else:
            for pattern, replacement in TO_CONVERT:
              a		:      Optional[Any]       =  re.sub(__snake_case		,    __snake_case		,    __snake_case			)

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

        if is_builder or "wmt" in f_name:
          # We create a new directory for each dataset
          a		:      List[str]       =  f_name.replace('.py'		,    ''			)
          a		:      int       =  os.path.join(__snake_case		,    __snake_case			)
          a		:      Any       =  os.path.join(__snake_case		,    __snake_case			)
          os.makedirs(__snake_case		,    exist_ok=__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(__snake_case			)

        if needs_manual_update:
          with_manual_update.append(__snake_case			)

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

      for utils_file in utils_files:
        try:
          a		:      Optional[Any]       =  os.path.basename(__snake_case			)
          a		:      Tuple       =  imports_to_builder_map[f_name.replace('.py'		,    ''			)]
          self._logger.info(F"""Moving {dest_folder} to {utils_file}"""			)
          shutil.copy(__snake_case		,    __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'."""			)




'''simple docstring'''






def    lowerCamelCase__ (		_A = 6008_5147_5143       ):

  try:
    a		:      Optional[int]       =  int(_A       )
  except (TypeError, ValueError):
    raise TypeError('Parameter n must be int or castable to int.'       )
  if n <= 0:
    raise ValueError('Parameter n must be greater than or equal to one.'       )
  a		:      Any       =  1
  a		:      Union[str, Any]       =  2
  while i * i <= n:
    while n % i == 0:
      a		:      str       =  i
      n //= i
    i += 1
  if n > 1:
    a		:      Any       =  n
  return int(_A       )


if __name__ == "__main__":
     print(F"{solution() = }")