




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

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


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

a													=			"=======\n>>>>>>>\n"

a													=			[
    "TextEncoderConfig",
    "ByteTextEncoder",
    "SubwordTextEncoder",
    "encoder_config",
    "maybe_build_from_corpus",
    "manual_dir",
]

a													=			[
    # (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        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				str:
						return ConvertCommand(args.tfds_path			,     args.datasets_directory       )




class       _A				(		__lowercase     ):






		@staticmethod
		def 				UpperCAmelCase (    _SCREAMING_SNAKE_CASE			):
								_UpperCAmelCase      =			parser.add_parser(
								    """convert"""						,		help="""Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset."""						,		)
								train_parser.add_argument(
								    """--tfds_path"""						,		type=_SCREAMING_SNAKE_CASE						,		required=_SCREAMING_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=_SCREAMING_SNAKE_CASE						,		required=_SCREAMING_SNAKE_CASE						,		help="""Path to the HuggingFace Datasets folder."""			)
								train_parser.set_defaults(func=_SCREAMING_SNAKE_CASE			)






		def __init__(    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		*_SCREAMING_SNAKE_CASE			):
								_UpperCAmelCase      =			get_logger("""datasets-cli/converting"""			)

								_UpperCAmelCase      =			tfds_path
								_UpperCAmelCase      =			datasets_directory






		def 				UpperCAmelCase (    self			):
								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(_SCREAMING_SNAKE_CASE			)
								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(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
														_UpperCAmelCase      =			os.path.join(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)

														if not os.path.isfile(_SCREAMING_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(_SCREAMING_SNAKE_CASE						,		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 _SCREAMING_SNAKE_CASE			: e in out_line						,		_SCREAMING_SNAKE_CASE			)			)
																										out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(_SCREAMING_SNAKE_CASE			) + """\n"""			)
																										out_lines.append(_SCREAMING_SNAKE_CASE			)
																										out_lines.append(_SCREAMING_SNAKE_CASE			)
																										continue
																				else:
																										for pattern, replacement in TO_CONVERT:
																																_UpperCAmelCase      =			re.sub(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)

                # 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]+)"""						,		_SCREAMING_SNAKE_CASE			)
																										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(_SCREAMING_SNAKE_CASE			)

														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(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
																				_UpperCAmelCase      =			os.path.join(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
																				os.makedirs(_SCREAMING_SNAKE_CASE						,		exist_ok=_SCREAMING_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(_SCREAMING_SNAKE_CASE			)

														if needs_manual_update:
																				with_manual_update.append(_SCREAMING_SNAKE_CASE			)

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

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





import logging

from transformers.configuration_utils import PretrainedConfig


a													=			logging.getLogger(__name__)




class       _A				(		__lowercase     ):
		__a					    =       """masked_bert"""






		def __init__(    self						,		_SCREAMING_SNAKE_CASE=3_0522						,		_SCREAMING_SNAKE_CASE=768						,		_SCREAMING_SNAKE_CASE=12						,		_SCREAMING_SNAKE_CASE=12						,		_SCREAMING_SNAKE_CASE=3072						,		_SCREAMING_SNAKE_CASE="gelu"						,		_SCREAMING_SNAKE_CASE=0.1						,		_SCREAMING_SNAKE_CASE=0.1						,		_SCREAMING_SNAKE_CASE=512						,		_SCREAMING_SNAKE_CASE=2						,		_SCREAMING_SNAKE_CASE=0.02						,		_SCREAMING_SNAKE_CASE=1e-12						,		_SCREAMING_SNAKE_CASE=0						,		_SCREAMING_SNAKE_CASE="topK"						,		_SCREAMING_SNAKE_CASE="constant"						,		_SCREAMING_SNAKE_CASE=0.0						,		**_SCREAMING_SNAKE_CASE						,		):
								super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE						,		**_SCREAMING_SNAKE_CASE			)

								_UpperCAmelCase      =			vocab_size
								_UpperCAmelCase      =			hidden_size
								_UpperCAmelCase      =			num_hidden_layers
								_UpperCAmelCase      =			num_attention_heads
								_UpperCAmelCase      =			hidden_act
								_UpperCAmelCase      =			intermediate_size
								_UpperCAmelCase      =			hidden_dropout_prob
								_UpperCAmelCase      =			attention_probs_dropout_prob
								_UpperCAmelCase      =			max_position_embeddings
								_UpperCAmelCase      =			type_vocab_size
								_UpperCAmelCase      =			initializer_range
								_UpperCAmelCase      =			layer_norm_eps
								_UpperCAmelCase      =			pruning_method
								_UpperCAmelCase      =			mask_init
								_UpperCAmelCase      =			mask_scale