



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

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


_lowercase: Any      			=		"<<<<<<< This should probably be modified because it mentions: "

_lowercase: List[Any]      			=		"=======\n>>>>>>>\n"

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

_lowercase: 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     a(      A       :    Namespace       )		->       List[Any]:
					"""simple docstring"""





					return ConvertCommand(args.tfds_path ,     args.datasets_directory       )







class 	_lowercase							(   lowerCAmelCase	):





	"""simple docstring"""




	@staticmethod
	def      UpperCamelCase_       (lowerCamelCase_		):
						"""simple docstring"""

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




	def __init__(self		,       lowerCamelCase_		,       lowerCamelCase_		,       *lowerCamelCase_		):
						"""simple docstring"""

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

						a					     =   tfds_path
						a					     =   datasets_directory




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

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

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

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

						a					     =   []
						a					     =   []
						a					     =   {}

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

						for f_name in file_names:
											self._logger.info(F'''Looking at file {f_name}'''		)
											a					     =   os.path.join(lowerCamelCase_		,       lowerCamelCase_		)
											a					     =   os.path.join(lowerCamelCase_		,       lowerCamelCase_		)

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

											with open(lowerCamelCase_		,       encoding="utf-8"		) as f:
																a					     =   f.readlines()

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

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

											if is_builder or "wmt" in f_name:
																# We create a new directory for each dataset
																a					     =   f_name.replace(".py"		,       ""		)
																a					     =   os.path.join(lowerCamelCase_		,       lowerCamelCase_		)
																a					     =   os.path.join(lowerCamelCase_		,       lowerCamelCase_		)
																os.makedirs(lowerCamelCase_		,       exist_ok=lowerCamelCase_		)
																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(lowerCamelCase_		)

											if needs_manual_update:
																with_manual_update.append(lowerCamelCase_		)

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

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





def     a(      A       :    list       )		->       list:
					"""simple docstring"""





					if any(not isinstance(A ,     A       ) or x < 0 for x in sequence       ):
										raise TypeError("Sequence must be list of non-negative integers"       )
					for _ in range(len(A       )       ):
										for i, (rod_upper, rod_lower) in enumerate(zip(A ,     sequence[1:]       )       ):
															if rod_upper > rod_lower:
																				sequence[i] -= rod_upper - rod_lower
																				sequence[i + 1] += rod_upper - rod_lower
					return sequence


if __name__ == "__main__":
				assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
				assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]
