
from ..utils import DummyObject, requires_backends

class __snake_case		(				metaclass=lowerCAmelCase					):
    _a		:						Optional[Any]=    ["transformers", "torch", "note_seq"]
    def __init__(  self		,*snake_case		,**snake_case				):



           '''simple docstring'''







           requires_backends(self		,["""transformers""", """torch""", """note_seq"""]				)
    @classmethod
    def 				_SCREAMING_SNAKE_CASE	(  cls		,*snake_case		,**snake_case				):



           '''simple docstring'''







           requires_backends(cls		,["""transformers""", """torch""", """note_seq"""]				)
    @classmethod
    def 				_SCREAMING_SNAKE_CASE	(  cls		,*snake_case		,**snake_case				):



           '''simple docstring'''







           requires_backends(cls		,["""transformers""", """torch""", """note_seq"""]				)


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

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


lowercase  : Tuple						   =							"""<<<<<<< This should probably be modified because it mentions: """

lowercase  : Any						   =							"""=======
>>>>>>>
"""

lowercase  : List[str]						   =							[
    """TextEncoderConfig""",
    """ByteTextEncoder""",
    """SubwordTextEncoder""",
    """encoder_config""",
    """maybe_build_from_corpus""",
    """manual_dir""",
]

lowercase  : 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 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   List[Any]:
       return ConvertCommand(args.tfds_path ,     args.datasets_directory    )




class __snake_case		(				lowerCAmelCase					):
    @staticmethod
    def 				_SCREAMING_SNAKE_CASE	(  snake_case				):



           '''simple docstring'''







           lowercase							:					str	     =				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		,snake_case		,snake_case		,*snake_case				):



           '''simple docstring'''







           lowercase							:					Optional[Any]	     =				get_logger("""datasets-cli/converting"""				)

           lowercase							:					Optional[int]	     =				tfds_path
           lowercase							:					Dict	     =				datasets_directory
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







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

           lowercase							:					Optional[int]	     =				os.path.abspath(self._datasets_directory				)

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

           lowercase							:					List[Any]	     =				[]
           lowercase							:					Optional[int]	     =				[]
           lowercase							:					Dict	     =				{}

           if os.path.isdir(self._tfds_path				):
                  lowercase							:					int	     =				os.listdir(snake_case				)
           else:
                  lowercase							:					List[Any]	     =				[os.path.basename(self._tfds_path				)]

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

                  lowercase							:					Union[str, Any]	     =				[]
                  lowercase							:					Optional[Any]	     =				False
                  lowercase							:					Optional[Any]	     =				False
                  lowercase							:					Optional[int]	     =				[]
                  for line in lines:
                         lowercase							:					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:
                                lowercase							:					Union[str, Any]	     =				"""import datasets\n"""
                         elif "import tensorflow" in out_line:
                                # order is important here
                                lowercase							:					List[Any]	     =				""""""
                                continue
                         elif "from absl import logging" in out_line:
                                lowercase							:					Optional[int]	     =				"""from datasets import logging\n"""
                         elif "getLogger" in out_line:
                                lowercase							:					Any	     =				out_line.replace("""getLogger"""		,"""get_logger"""				)
                         elif any(expression in out_line for expression in TO_HIGHLIGHT				):
                                lowercase							:					Optional[Any]	     =				True
                                lowercase							:					Optional[Any]	     =				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:
                                       lowercase							:					Union[str, 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:
                                lowercase							:					Dict	     =				re.match(r"""from\stensorflow_datasets.*import\s([^\.\r\n]+)"""		,snake_case				)
                                tfds_imports.extend(imp.strip() for imp in match.group(1				).split(""","""				)				)
                                lowercase							:					Optional[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:
                                lowercase							:					Any	     =				True
                         out_lines.append(snake_case				)

                  if is_builder or "wmt" in f_name:
                         # We create a new directory for each dataset
                         lowercase							:					Union[str, Any]	     =				f_name.replace(""".py"""		,""""""				)
                         lowercase							:					Optional[Any]	     =				os.path.join(snake_case		,snake_case				)
                         lowercase							:					List[str]	     =				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:
                         lowercase							:					Optional[int]	     =				os.path.basename(snake_case				)
                         lowercase							:					int	     =				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'."				)
