

'''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


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

UpperCamelCase_    						=       """=======
>>>>>>>
"""

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

UpperCamelCase_    						=       [
    # (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			(   __magic_name__						:     Namespace						)				->  Dict:
						return ConvertCommand(args.tfds_path   , args.datasets_directory						)







class 		__SCREAMING_SNAKE_CASE							(			lowercase__      ):







				@staticmethod
				def  lowerCamelCase_	(       UpperCAmelCase__     :		ArgumentParser   ):
										'''simple docstring'''
										lowercase :							Optional[Any]    		=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     :		Tuple		,					UpperCAmelCase__     :		str		,					UpperCAmelCase__     :		str		,					*UpperCAmelCase__     :		Optional[int]   ):
										'''simple docstring'''
										lowercase :							int    		=get_logger('''datasets-cli/converting'''   )

										lowercase :							Tuple    		=tfds_path
										lowercase :							Any    		=datasets_directory







				def  lowerCamelCase_	(       self     :		Optional[Any]   ):
										'''simple docstring'''
										if os.path.isdir(self._tfds_path   ):
																lowercase :							List[Any]    		=os.path.abspath(self._tfds_path   )
										elif os.path.isfile(self._tfds_path   ):
																lowercase :							str    		=os.path.dirname(self._tfds_path   )
										else:
																raise ValueError('''--tfds_path is neither a directory nor a file. Please check path.'''   )

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

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

										lowercase :							Tuple    		=[]
										lowercase :							Optional[Any]    		=[]
										lowercase :							Tuple    		={}

										if os.path.isdir(self._tfds_path   ):
																lowercase :							Any    		=os.listdir(UpperCAmelCase__   )
										else:
																lowercase :							Dict    		=[os.path.basename(self._tfds_path   )]

										for f_name in file_names:
																self._logger.info(F'''Looking at file {f_name}'''   )
																lowercase :							Any    		=os.path.join(UpperCAmelCase__		,					UpperCAmelCase__   )
																lowercase :							int    		=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:
																						lowercase :							List[Any]    		=f.readlines()

																lowercase :							Optional[int]    		=[]
																lowercase :							Any    		=False
																lowercase :							Optional[Any]    		=False
																lowercase :							Optional[Any]    		=[]
																for line in lines:
																						lowercase :							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:
																												lowercase :							Tuple    		='''import datasets\n'''
																						elif "import tensorflow" in out_line:
																												# order is important here
																												lowercase :							List[str]    		=''''''
																												continue
																						elif "from absl import logging" in out_line:
																												lowercase :							Optional[int]    		='''from datasets import logging\n'''
																						elif "getLogger" in out_line:
																												lowercase :							Optional[Any]    		=out_line.replace('''getLogger'''		,					'''get_logger'''   )
																						elif any(expression in out_line for expression in TO_HIGHLIGHT   ):
																												lowercase :							int    		=True
																												lowercase :							Union[str, Any]    		=list(filter(lambda UpperCAmelCase__   : 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:
																																		lowercase :							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:
																												lowercase :							int    		=re.match(r'''from\stensorflow_datasets.*import\s([^\.\r\n]+)'''		,					UpperCAmelCase__   )
																												tfds_imports.extend(imp.strip() for imp in match.group(1   ).split(''','''   )   )
																												lowercase :							int    		='''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:
																												lowercase :							Optional[Any]    		=True
																						out_lines.append(UpperCAmelCase__   )

																if is_builder or "wmt" in f_name:
																						# We create a new directory for each dataset
																						lowercase :							Tuple    		=f_name.replace('''.py'''		,					''''''   )
																						lowercase :							Dict    		=os.path.join(UpperCAmelCase__		,					UpperCAmelCase__   )
																						lowercase :							List[str]    		=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:
																						lowercase :							str    		=os.path.basename(UpperCAmelCase__   )
																						lowercase :							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\'.'''   )










'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available


__lowerCAmelCase		     =  {
    '''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase		     =  [
							    '''ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''ErnieForCausalLM''',
							    '''ErnieForMaskedLM''',
							    '''ErnieForMultipleChoice''',
							    '''ErnieForNextSentencePrediction''',
							    '''ErnieForPreTraining''',
							    '''ErnieForQuestionAnswering''',
							    '''ErnieForSequenceClassification''',
							    '''ErnieForTokenClassification''',
							    '''ErnieModel''',
							    '''ErniePreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_ernie import (
														    ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ErnieForCausalLM,
														    ErnieForMaskedLM,
														    ErnieForMultipleChoice,
														    ErnieForNextSentencePrediction,
														    ErnieForPreTraining,
														    ErnieForQuestionAnswering,
														    ErnieForSequenceClassification,
														    ErnieForTokenClassification,
														    ErnieModel,
														    ErniePreTrainedModel,
														)

else:
							import sys

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




