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

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


_UpperCAmelCase :			Union[str, Any]              =	"<<<<<<< This should probably be modified because it mentions: "

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

_UpperCAmelCase :			Optional[int]              =	[
    "TextEncoderConfig",
    "ByteTextEncoder",
    "SubwordTextEncoder",
    "encoder_config",
    "maybe_build_from_corpus",
    "manual_dir",
]

_UpperCAmelCase :			Optional[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 				A	( lowercase			)       ->  Optional[Any]:
		'''simple docstring'''

		return ConvertCommand(args.tfds_path   ,	args.datasets_directory			)


class     lowercase (		_SCREAMING_SNAKE_CASE       ):



		@staticmethod
		def __UpperCamelCase			(			A_	)  -> Union[str, Any]:
				"""simple docstring"""
				UpperCamelCase          =					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_	)  -> Any:
				"""simple docstring"""
				UpperCamelCase          =					get_logger('datasets-cli/converting'	)

				UpperCamelCase          =					tfds_path
				UpperCamelCase          =					datasets_directory



		def __UpperCamelCase			(			self	)  -> int:
				"""simple docstring"""
				if os.path.isdir(self._tfds_path	):
						UpperCamelCase          =					os.path.abspath(self._tfds_path	)
				elif os.path.isfile(self._tfds_path	):
						UpperCamelCase          =					os.path.dirname(self._tfds_path	)
				else:
						raise ValueError('--tfds_path is neither a directory nor a file. Please check path.'	)

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

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

				UpperCamelCase          =					[]
				UpperCamelCase          =					[]
				UpperCamelCase          =					{}

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

				for f_name in file_names:
						self._logger.info(F'''Looking at file {f_name}'''	)
						UpperCamelCase          =					os.path.join(A_    ,				A_	)
						UpperCamelCase          =					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:
								UpperCamelCase          =					f.readlines()

						UpperCamelCase          =					[]
						UpperCamelCase          =					False
						UpperCamelCase          =					False
						UpperCamelCase          =					[]
						for line in lines:
								UpperCamelCase          =					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          =					'import datasets\n'
								elif "import tensorflow" in out_line:
										# order is important here
										UpperCamelCase          =					''
										continue
								elif "from absl import logging" in out_line:
										UpperCamelCase          =					'from datasets import logging\n'
								elif "getLogger" in out_line:
										UpperCamelCase          =					out_line.replace('getLogger'    ,				'get_logger'	)
								elif any(expression in out_line for expression in TO_HIGHLIGHT	):
										UpperCamelCase          =					True
										UpperCamelCase          =					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:
												UpperCamelCase          =					re.sub(A_    ,				A_    ,				A_	)

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

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


import logging
import os

from .state import PartialState


class     lowercase (		logging.LoggerAdapter       ):



		@staticmethod
		def __UpperCamelCase			(			A_	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					PartialState()
				return not main_process_only or (main_process_only and state.is_main_process)



		def __UpperCamelCase			(			self    ,				A_    ,				A_    ,				*A_    ,				**A_	)  -> Union[str, Any]:
				"""simple docstring"""
				if PartialState._shared_state == {}:
						raise RuntimeError(
						    'You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility.'	)
				UpperCamelCase          =					kwargs.pop('main_process_only'    ,				A_	)
				UpperCamelCase          =					kwargs.pop('in_order'    ,				A_	)

				if self.isEnabledFor(A_	):
						if self._should_log(A_	):
								UpperCamelCase     ,  UpperCamelCase          =					self.process(A_    ,				A_	)
								self.logger.log(A_    ,				A_    ,				*A_    ,				**A_	)

						elif in_order:
								UpperCamelCase          =					PartialState()
								for i in range(state.num_processes	):
										if i == state.process_index:
												UpperCamelCase     ,  UpperCamelCase          =					self.process(A_    ,				A_	)
												self.logger.log(A_    ,				A_    ,				*A_    ,				**A_	)
										state.wait_for_everyone()






def 				A	( lowercase   ,	lowercase = None			)       ->  Dict:
		'''simple docstring'''

		if log_level is None:
				UpperCamelCase          =					os.environ.get('ACCELERATE_LOG_LEVEL'   ,	lowercase			)
		UpperCamelCase          =					logging.getLogger(lowercase			)
		if log_level is not None:
				logger.setLevel(log_level.upper()			)
				logger.root.setLevel(log_level.upper()			)
		return MultiProcessAdapter(lowercase   ,	{}			)
