






'''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


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

SCREAMING_SNAKE_CASE__											=     '=======\n>>>>>>>\n'

SCREAMING_SNAKE_CASE__											=     [
    'TextEncoderConfig',
    'ByteTextEncoder',
    'SubwordTextEncoder',
    'encoder_config',
    'maybe_build_from_corpus',
    'manual_dir',
]

SCREAMING_SNAKE_CASE__											=     [
    # (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 					lowercase__				(   __UpperCamelCase					)->				List[str]:
      return ConvertCommand(args.tfds_path	,		args.datasets_directory					)






class        a_		(    lowerCamelCase       ):

  @staticmethod
  def 						A__		(   _SCREAMING_SNAKE_CASE   )						->   Optional[int]:



        """simple docstring"""






        UpperCamelCase       						=      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    ,	_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE    ,	*_SCREAMING_SNAKE_CASE   )						->   Union[str, Any]:



        """simple docstring"""






        UpperCamelCase       						=      get_logger("""datasets-cli/converting"""   )

        UpperCamelCase       						=      tfds_path
        UpperCamelCase       						=      datasets_directory


  def 						A__		(   self   )						->   str:



        """simple docstring"""






        if os.path.isdir(self._tfds_path   ):
              UpperCamelCase       						=      os.path.abspath(self._tfds_path   )
        elif os.path.isfile(self._tfds_path   ):
              UpperCamelCase       						=      os.path.dirname(self._tfds_path   )
        else:
              raise ValueError("""--tfds_path is neither a directory nor a file. Please check path."""   )

        UpperCamelCase       						=      os.path.abspath(self._datasets_directory   )

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

        UpperCamelCase       						=      []
        UpperCamelCase       						=      []
        UpperCamelCase       						=      {}

        if os.path.isdir(self._tfds_path   ):
              UpperCamelCase       						=      os.listdir(_SCREAMING_SNAKE_CASE   )
        else:
              UpperCamelCase       						=      [os.path.basename(self._tfds_path   )]

        for f_name in file_names:
              self._logger.info(F"Looking at file {f_name}"   )
              UpperCamelCase       						=      os.path.join(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE   )
              UpperCamelCase       						=      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:
                    UpperCamelCase       						=      f.readlines()

              UpperCamelCase       						=      []
              UpperCamelCase       						=      False
              UpperCamelCase       						=      False
              UpperCamelCase       						=      []
              for line in lines:
                    UpperCamelCase       						=      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:
                          UpperCamelCase       						=      """import datasets\n"""
                    elif "import tensorflow" in out_line:
                          # order is important here
                          UpperCamelCase       						=      """"""
                          continue
                    elif "from absl import logging" in out_line:
                          UpperCamelCase       						=      """from datasets import logging\n"""
                    elif "getLogger" in out_line:
                          UpperCamelCase       						=      out_line.replace("""getLogger"""    ,	"""get_logger"""   )
                    elif any(expression in out_line for expression in TO_HIGHLIGHT   ):
                          UpperCamelCase       						=      True
                          UpperCamelCase       						=      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:
                                UpperCamelCase       						=      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:
                          UpperCamelCase       						=      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(""","""   )   )
                          UpperCamelCase       						=      """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:
                          UpperCamelCase       						=      True
                    out_lines.append(_SCREAMING_SNAKE_CASE   )

              if is_builder or "wmt" in f_name:
                    # We create a new directory for each dataset
                    UpperCamelCase       						=      f_name.replace(""".py"""    ,	""""""   )
                    UpperCamelCase       						=      os.path.join(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE   )
                    UpperCamelCase       						=      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:
                    UpperCamelCase       						=      os.path.basename(_SCREAMING_SNAKE_CASE   )
                    UpperCamelCase       						=      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'."   )








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import _LazyModule


SCREAMING_SNAKE_CASE__											=     {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}


if TYPE_CHECKING:
     from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
     import sys

     SCREAMING_SNAKE_CASE__											=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
