

"""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


snake_case_ : List[str]   =							"""<<<<<<< This should probably be modified because it mentions: """

snake_case_ : List[Any]   =							"""=======
>>>>>>>
"""

snake_case_ : Any   =							[
    """TextEncoderConfig""",
    """ByteTextEncoder""",
    """SubwordTextEncoder""",
    """encoder_config""",
    """maybe_build_from_corpus""",
    """manual_dir""",
]

snake_case_ : 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							:		Namespace						):




					'''simple docstring'''






					return ConvertCommand(args.tfds_path				,   args.datasets_directory						)







class    snake_case__	(			lowerCAmelCase_  ):







			@staticmethod
			def       __lowerCAmelCase					(      lowercase      :			ArgumentParser	):





								'''simple docstring'''



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







			def __init__(      self      :			List[str]      ,	lowercase      :			str      ,	lowercase      :			str      ,	*lowercase      :			Union[str, Any]	):





								'''simple docstring'''



								UpperCAmelCase      : Tuple   =					get_logger("datasets-cli/converting"	)

								UpperCAmelCase      : int   =					tfds_path
								UpperCAmelCase      : Optional[int]   =					datasets_directory







			def       __lowerCAmelCase					(      self      :			List[str]	):





								'''simple docstring'''



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

								UpperCAmelCase      : Union[str, Any]   =					os.path.abspath(self._datasets_directory	)

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

								UpperCAmelCase      : Optional[Any]   =					[]
								UpperCAmelCase      : Optional[int]   =					[]
								UpperCAmelCase      : str   =					{}

								if os.path.isdir(self._tfds_path	):
													UpperCAmelCase      : Optional[Any]   =					os.listdir(__UpperCamelCase	)
								else:
													UpperCAmelCase      : List[Any]   =					[os.path.basename(self._tfds_path	)]

								for f_name in file_names:
													self._logger.info(f"""Looking at file {f_name}"""	)
													UpperCAmelCase      : Tuple   =					os.path.join(__UpperCamelCase      ,	__UpperCamelCase	)
													UpperCAmelCase      : Union[str, Any]   =					os.path.join(__UpperCamelCase      ,	__UpperCamelCase	)

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

													with open(__UpperCamelCase      ,	encoding="utf-8"	) as f:
																		UpperCAmelCase      : Any   =					f.readlines()

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

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

													if is_builder or "wmt" in f_name:
																		# We create a new directory for each dataset
																		UpperCAmelCase      : Dict   =					f_name.replace(".py"      ,	""	)
																		UpperCAmelCase      : List[Any]   =					os.path.join(__UpperCamelCase      ,	__UpperCamelCase	)
																		UpperCAmelCase      : Tuple   =					os.path.join(__UpperCamelCase      ,	__UpperCamelCase	)
																		os.makedirs(__UpperCamelCase      ,	exist_ok=__UpperCamelCase	)
																		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(__UpperCamelCase	)

													if needs_manual_update:
																		with_manual_update.append(__UpperCamelCase	)

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

								for utils_file in utils_files:
													try:
																		UpperCAmelCase      : Union[str, Any]   =					os.path.basename(__UpperCamelCase	)
																		UpperCAmelCase      : Optional[int]   =					imports_to_builder_map[f_name.replace(".py"      ,	""	)]
																		self._logger.info(f"""Moving {dest_folder} to {utils_file}"""	)
																		shutil.copy(__UpperCamelCase      ,	__UpperCamelCase	)
													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\'."""	)




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


lowercase   =	{}


try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	['''MLukeTokenizer''']

if TYPE_CHECKING:
		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_mluke import MLukeTokenizer


else:
		import sys

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





