






'''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


UpperCAmelCase__						:Optional[Any]          =			"""<<<<<<< This should probably be modified because it mentions: """

UpperCAmelCase__						:List[str]          =			"""=======
>>>>>>>
"""

UpperCAmelCase__						:Optional[Any]          =			[
    """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     __lowercase  (_lowercase     )   ->     List[Any]:


     """simple docstring"""
     return ConvertCommand(args.tfds_path,						args.datasets_directory     )







class 	SCREAMING_SNAKE_CASE	(      lowerCAmelCase_  ):




       @staticmethod
       def 					a_					(					A__      : ArgumentParser					):


            """simple docstring"""







            __lowerCamelCase						:       int				   =				parser.add_parser(
                """convert"""	,    help="""Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset."""	,    )
            train_parser.add_argument(
                """--tfds_path"""	,    type=A__	,    required=A__	,    help="""Path to a TensorFlow Datasets folder to convert or a single tfds file to convert."""	,    )
            train_parser.add_argument(
                """--datasets_directory"""	,    type=A__	,    required=A__	,    help="""Path to the HuggingFace Datasets folder."""					)
            train_parser.set_defaults(func=A__					)




       def __init__(					self      : List[str]	,    A__      : str	,    A__      : str	,    *A__      : Dict					):


            """simple docstring"""







            __lowerCamelCase						:       Union[str, Any]				   =				get_logger("""datasets-cli/converting"""					)

            __lowerCamelCase						:       Tuple				   =				tfds_path
            __lowerCamelCase						:       List[Any]				   =				datasets_directory




       def 					a_					(					self      : Union[str, Any]					):


            """simple docstring"""







            if os.path.isdir(self._tfds_path					):
                 __lowerCamelCase						:       Dict				   =				os.path.abspath(self._tfds_path					)
            elif os.path.isfile(self._tfds_path					):
                 __lowerCamelCase						:       Union[str, Any]				   =				os.path.dirname(self._tfds_path					)
            else:
                 raise ValueError("""--tfds_path is neither a directory nor a file. Please check path."""					)

            __lowerCamelCase						:       int				   =				os.path.abspath(self._datasets_directory					)

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

            __lowerCamelCase						:       int				   =				[]
            __lowerCamelCase						:       int				   =				[]
            __lowerCamelCase						:       Union[str, Any]				   =				{}

            if os.path.isdir(self._tfds_path					):
                 __lowerCamelCase						:       Optional[int]				   =				os.listdir(A__					)
            else:
                 __lowerCamelCase						:       Union[str, Any]				   =				[os.path.basename(self._tfds_path					)]

            for f_name in file_names:
                 self._logger.info(f"Looking at file {f_name}"					)
                 __lowerCamelCase						:       Any				   =				os.path.join(A__	,    A__					)
                 __lowerCamelCase						:       List[Any]				   =				os.path.join(A__	,    A__					)

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

                 with open(A__	,    encoding="""utf-8"""					) as f:
                      __lowerCamelCase						:       Tuple				   =				f.readlines()

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

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

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

                 if needs_manual_update:
                      with_manual_update.append(A__					)

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

            for utils_file in utils_files:
                 try:
                      __lowerCamelCase						:       List[Any]				   =				os.path.basename(A__					)
                      __lowerCamelCase						:       int				   =				imports_to_builder_map[f_name.replace(""".py"""	,    """"""					)]
                      self._logger.info(f"Moving {dest_folder} to {utils_file}"					)
                      shutil.copy(A__	,    A__					)
                 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     __lowercase  (_lowercase     )   ->     list:


     """simple docstring"""

     # bit count represents no. of bits in the gray code
     if bit_count < 0:
          raise ValueError("""The given input must be positive"""     )

     # get the generated string sequence
     __lowerCamelCase						:       Optional[Any]				   =				gray_code_sequence_string(_lowercase     )
     #
     # convert them to integers
     for i in range(len(_lowercase     )     ):
          __lowerCamelCase						:       List[str]				   =				int(sequence[i],						2     )

     return sequence
def     __lowercase  (_lowercase     )   ->     list:


     """simple docstring"""

     # The approach is a recursive one
     # Base case achieved when either n = 0 or n=1
     if bit_count == 0:
          return ["0"]

     if bit_count == 1:
          return ["0", "1"]

     __lowerCamelCase						:       str				   =				1 << bit_count  # defines the length of the sequence
     # 1<< n is equivalent to 2^n

     # recursive answer will generate answer for n-1 bits
     __lowerCamelCase						:       Union[str, Any]				   =				gray_code_sequence_string(bit_count - 1     )

     __lowerCamelCase						:       Optional[int]				   =				[]

     # append 0 to first half of the smaller sequence generated
     for i in range(seq_len // 2     ):
          __lowerCamelCase						:       Union[str, Any]				   =				"""0""" + smaller_sequence[i]
          sequence.append(_lowercase     )

     # append 1 to second half ... start from the end of the list
     for i in reversed(range(seq_len // 2     )     ):
          __lowerCamelCase						:       Optional[Any]				   =				"""1""" + smaller_sequence[i]
          sequence.append(_lowercase     )

     return sequence


if __name__ == "__main__":
   import doctest

   doctest.testmod()



