


"""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


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

A     :   Optional[int]			    =			"=======\n>>>>>>>\n"

A     :   Dict			    =			[
    "TextEncoderConfig",
    "ByteTextEncoder",
    "SubwordTextEncoder",
    "encoder_config",
    "maybe_build_from_corpus",
    "manual_dir",
]

A     :   List[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 _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			return ConvertCommand(args.tfds_path    , args.datasets_directory      )


class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							@staticmethod
							def 			snake_case				(     __a	):
										__lowerCAmelCase				    =			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    ,   __a    ,   __a    ,   *__a	):
										__lowerCAmelCase				    =			get_logger("datasets-cli/converting"	)

										__lowerCAmelCase				    =			tfds_path
										__lowerCAmelCase				    =			datasets_directory



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

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

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

										__lowerCAmelCase				    =			[]
										__lowerCAmelCase				    =			[]
										__lowerCAmelCase				    =			{}

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

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

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

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


class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							pass
class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							pass
class   _UpperCamelCase  :
							'''simple docstring'''







							def __init__(     self	):
										__lowerCAmelCase				    =			[
										    [],
										    [],
										    [],
										]

							def 			snake_case				(     self    ,   __a    ,   __a	):
										try:
													if len(self.queues[priority]	) >= 1_00:
																raise OverflowError("Maximum queue size is 100"	)
													self.queues[priority].append(__a	)
										except IndexError:
													raise ValueError("Valid priorities are 0, 1, and 2"	)

							def 			snake_case				(     self	):
										for queue in self.queues:
													if queue:
																return queue.pop(0	)
										raise UnderFlowError("All queues are empty"	)



							def __str__(     self	):
										return "\n".join(f"Priority {i}: {q}" for i, q in enumerate(self.queues	)	)
class   _UpperCamelCase  :
							'''simple docstring'''







							def __init__(     self	):
										__lowerCAmelCase				    =			[]

							def 			snake_case				(     self    ,   __a	):
										if len(self.queue	) == 1_00:
													raise OverFlowError("Maximum queue size is 100"	)
										self.queue.append(__a	)

							def 			snake_case				(     self	):
										if not self.queue:
													raise UnderFlowError("The queue is empty"	)
										else:
													__lowerCAmelCase				    =			min(self.queue	)
													self.queue.remove(__a	)
													return data



							def __str__(     self	):
										return str(self.queue	)


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			FixedPriorityQueue()
			fpq.enqueue(0    , 10      )
			fpq.enqueue(1    , 70      )
			fpq.enqueue(0    , 100      )
			fpq.enqueue(2    , 1      )
			fpq.enqueue(2    , 5      )
			fpq.enqueue(1    , 7      )
			fpq.enqueue(2    , 4      )
			fpq.enqueue(1    , 64      )
			fpq.enqueue(0    , 128      )
			print(_UpperCamelCase      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(_UpperCamelCase      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )
			print(fpq.dequeue()      )


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			ElementPriorityQueue()
			epq.enqueue(10      )
			epq.enqueue(70      )
			epq.enqueue(100      )
			epq.enqueue(1      )
			epq.enqueue(5      )
			epq.enqueue(7      )
			epq.enqueue(4      )
			epq.enqueue(64      )
			epq.enqueue(128      )
			print(_UpperCamelCase      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(_UpperCamelCase      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )
			print(epq.dequeue()      )


if __name__ == "__main__":
	fixed_priority_queue()
	element_priority_queue()




