code: 
  
  """simple docstring"""
  
  
  
  
  import os
  from argparse import ArgumentParser
  from pathlib import Path
  from shutil import copyfile, rmtree
  from typing import Generator
  
  import datasets.config
  from datasets.builder import DatasetBuilder
  from datasets.commands import BaseDatasetsCLICommand
  from datasets.download.download_manager import DownloadMode
  from datasets.load import dataset_module_factory, import_main_class
  from datasets.utils.filelock import logger as fl_logger
  from datasets.utils.info_utils import VerificationMode
  from datasets.utils.logging import ERROR, get_logger
  
  
  __A  :					Tuple												=	get_logger(__name__)
  def      __SCREAMING_SNAKE_CASE		(		lowercase__   ):
  					"""simple docstring"""
  					return TestCommand(
  					    args.dataset    ,							args.name    ,							args.cache_dir    ,							args.data_dir    ,							args.all_configs    ,							args.save_info or args.save_infos    ,							args.ignore_verifications    ,							args.force_redownload    ,							args.clear_cache    ,							)
  
  
  
  
  
  class     __UpperCamelCase				(     _A		):
  		SCREAMING_SNAKE_CASE              =					False  # to tell pytest it's not a test class
  
  
  		@staticmethod
  		def       SCREAMING_SNAKE_CASE__     (__SCREAMING_SNAKE_CASE				:	ArgumentParser):
  							A    =      parser.add_parser("test"  ,  help="Test dataset implementation.")
  							test_parser.add_argument("--name"  ,  type=__SCREAMING_SNAKE_CASE  ,  default=__SCREAMING_SNAKE_CASE  ,  help="Dataset processing name")
  							test_parser.add_argument(
  							    "--cache_dir"  ,  type=__SCREAMING_SNAKE_CASE  ,  default=__SCREAMING_SNAKE_CASE  ,  help="Cache directory where the datasets are stored."  ,  )
  							test_parser.add_argument(
  							    "--data_dir"  ,  type=__SCREAMING_SNAKE_CASE  ,  default=__SCREAMING_SNAKE_CASE  ,  help="Can be used to specify a manual directory to get the files from."  ,  )
  							test_parser.add_argument("--all_configs"  ,  action="store_true"  ,  help="Test all dataset configurations")
  							test_parser.add_argument(
  							    "--save_info"  ,  action="store_true"  ,  help="Save the dataset infos in the dataset card (README.md)")
  							test_parser.add_argument(
  							    "--ignore_verifications"  ,  action="store_true"  ,  help="Run the test without checksums and splits checks."  ,  )
  							test_parser.add_argument("--force_redownload"  ,  action="store_true"  ,  help="Force dataset redownload")
  							test_parser.add_argument(
  							    "--clear_cache"  ,  action="store_true"  ,  help="Remove downloaded files and cached datasets after each config test"  ,  )
  							# aliases
  							test_parser.add_argument("--save_infos"  ,  action="store_true"  ,  help="alias to save_info")
  							test_parser.add_argument("dataset"  ,  type=__SCREAMING_SNAKE_CASE  ,  help="Name of the dataset to download")
  							test_parser.set_defaults(func=_test_command_factory)
  
  
  		def __init__(self				:	Union[str, Any]  ,  __SCREAMING_SNAKE_CASE				:	str  ,  __SCREAMING_SNAKE_CASE				:	str  ,  __SCREAMING_SNAKE_CASE				:	str  ,  __SCREAMING_SNAKE_CASE				:	str  ,  __SCREAMING_SNAKE_CASE				:	bool  ,  __SCREAMING_SNAKE_CASE				:	bool  ,  __SCREAMING_SNAKE_CASE				:	bool  ,  __SCREAMING_SNAKE_CASE				:	bool  ,  __SCREAMING_SNAKE_CASE				:	bool  ,  ):
  							A    =      dataset
  							A    =      name
  							A    =      cache_dir
  							A    =      data_dir
  							A    =      all_configs
  							A    =      save_infos
  							A    =      ignore_verifications
  							A    =      force_redownload
  							A    =      clear_cache
  							if clear_cache and not cache_dir:
  												print(
  												    "When --clear_cache is used, specifying a cache directory is mandatory.\n"
  												    "The 'download' folder of the cache directory and the dataset builder cache will be deleted after each configuration test.\n"
  												    "Please provide a --cache_dir that will be used to test the dataset script.")
  												exit(1)
  							if save_infos:
  												A    =      True
  
  
  		def       SCREAMING_SNAKE_CASE__     (self				:	Tuple):
  							fl_logger().setLevel(__SCREAMING_SNAKE_CASE)
  							if self._name is not None and self._all_configs:
  												print("Both parameters `config` and `all_configs` can't be used at once.")
  												exit(1)
  							A    ,					A    =      self._dataset, self._name
  							A    =      dataset_module_factory(__SCREAMING_SNAKE_CASE)
  							A    =      import_main_class(module.module_path)
  							A    =      len(builder_cls.BUILDER_CONFIGS) if self._all_configs and builder_cls.BUILDER_CONFIGS else 1
  
  							def get_builders() -> Generator[DatasetBuilder, None, None]:
  												if self._all_configs and builder_cls.BUILDER_CONFIGS:
  																	for i, config in enumerate(builder_cls.BUILDER_CONFIGS):
  																						if "config_name" in module.builder_kwargs:
  																											yield builder_cls(
  																											    cache_dir=self._cache_dir  ,  data_dir=self._data_dir  ,  **module.builder_kwargs  ,  )
  																						else:
  																											yield builder_cls(
  																											    config_name=config.name  ,  cache_dir=self._cache_dir  ,  data_dir=self._data_dir  ,  **module.builder_kwargs  ,  )
  												else:
  																	if "config_name" in module.builder_kwargs:
  																						yield builder_cls(cache_dir=self._cache_dir  ,  data_dir=self._data_dir  ,  **module.builder_kwargs)
  																	else:
  																						yield builder_cls(
  																						    config_name=__SCREAMING_SNAKE_CASE  ,  cache_dir=self._cache_dir  ,  data_dir=self._data_dir  ,  **module.builder_kwargs  ,  )
  
  							for j, builder in enumerate(get_builders()):
  												print(F"""Testing builder '{builder.config.name}' ({j + 1}/{n_builders})""")
  												A    =      os.path.exists(
  												    os.path.join(builder.get_imported_module_dir()  ,  datasets.config.DATASETDICT_INFOS_FILENAME))  # record checksums only if we need to update a (deprecated) dataset_infos.json
  												builder.download_and_prepare(
  												    download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
  												    if not self._force_redownload
  												    else DownloadMode.FORCE_REDOWNLOAD  ,  verification_mode=VerificationMode.NO_CHECKS
  												    if self._ignore_verifications
  												    else VerificationMode.ALL_CHECKS  ,  try_from_hf_gcs=__SCREAMING_SNAKE_CASE  ,  )
  												builder.as_dataset()
  												if self._save_infos:
  																	builder._save_infos()
  
  												# If save_infos=True, the dataset card (README.md) is created next to the loaded module file.
  												# The dataset_infos are saved in the YAML part of the README.md
  
  												# Let's move it to the original directory of the dataset script, to allow the user to
  												# upload them on S3 at the same time afterwards.
  												if self._save_infos:
  																	A    =      os.path.join(builder_cls.get_imported_module_dir()  ,  "README.md")
  																	A    =      Path(__SCREAMING_SNAKE_CASE).name + ".py"
  																	A    =      os.path.join(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE)
  																	if os.path.isfile(__SCREAMING_SNAKE_CASE):
  																						A    =      os.path.dirname(__SCREAMING_SNAKE_CASE)
  																	elif os.path.isfile(__SCREAMING_SNAKE_CASE):
  																						A    =      path
  																	elif os.path.isdir(__SCREAMING_SNAKE_CASE):  # for local directories containing only data files
  																						A    =      path
  																	else:  # in case of a remote dataset
  																						A    =      None
  																						print(F"""Dataset card saved at {dataset_readme_path}""")
  
  																	# Move dataset_info back to the user
  																	if dataset_dir is not None:
  																						A    =      os.path.join(__SCREAMING_SNAKE_CASE  ,  "README.md")
  																						copyfile(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE)
  																						print(F"""Dataset card saved at {user_dataset_readme_path}""")
  
              # If clear_cache=True, the download folder and the dataset builder cache directory are deleted
  												if self._clear_cache:
  																	if os.path.isdir(builder._cache_dir):
  																						logger.warning(F"""Clearing cache at {builder._cache_dir}""")
  																						rmtree(builder._cache_dir)
  																	A    =      os.path.join(self._cache_dir  ,  datasets.config.DOWNLOADED_DATASETS_DIR)
  																	if os.path.isdir(__SCREAMING_SNAKE_CASE):
  																						logger.warning(F"""Clearing cache at {download_dir}""")
  																						rmtree(__SCREAMING_SNAKE_CASE)
  
  							print("Test successful.")
  
  
  
  
  
  
style_context: 
  
  """simple docstring"""
  
  
  
  
  import os
  
  from ...utils import logging
  from .utils import DataProcessor, InputExample
  
  
  __A  :					List[Any]												=	logging.get_logger(__name__)
  
  
  
  
  
  class     __UpperCamelCase				(     _A		):
  
  
  		def __init__(self				:	Dict  ,  __SCREAMING_SNAKE_CASE				:	int  ,  __SCREAMING_SNAKE_CASE				:	Any=None):
  							A    =      language
  							A    =      train_language
  
  
  		def       SCREAMING_SNAKE_CASE__     (self				:	Tuple  ,  __SCREAMING_SNAKE_CASE				:	Tuple):
  							A    =      self.language if self.train_language is None else self.train_language
  							A    =      self._read_tsv(os.path.join(__SCREAMING_SNAKE_CASE  ,  F"""XNLI-MT-1.0/multinli/multinli.train.{lg}.tsv"""))
  							A    =      []
  							for i, line in enumerate(__SCREAMING_SNAKE_CASE):
  												if i == 0:
  																	continue
  												A    =      F"""train-{i}"""
  												A    =      line[0]
  												A    =      line[1]
  												A    =      "contradiction" if line[2] == "contradictory" else line[2]
  												if not isinstance(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE):
  																	raise ValueError(F"""Training input {text_a} is not a string""")
  												if not isinstance(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE):
  																	raise ValueError(F"""Training input {text_b} is not a string""")
  												if not isinstance(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE):
  																	raise ValueError(F"""Training label {label} is not a string""")
  												examples.append(InputExample(guid=__SCREAMING_SNAKE_CASE  ,  text_a=__SCREAMING_SNAKE_CASE  ,  text_b=__SCREAMING_SNAKE_CASE  ,  label=__SCREAMING_SNAKE_CASE))
  							return examples
  
  
  		def       SCREAMING_SNAKE_CASE__     (self				:	List[str]  ,  __SCREAMING_SNAKE_CASE				:	Tuple):
  							A    =      self._read_tsv(os.path.join(__SCREAMING_SNAKE_CASE  ,  "XNLI-1.0/xnli.test.tsv"))
  							A    =      []
  							for i, line in enumerate(__SCREAMING_SNAKE_CASE):
  												if i == 0:
  																	continue
  												A    =      line[0]
  												if language != self.language:
  																	continue
  												A    =      F"""test-{i}"""
  												A    =      line[6]
  												A    =      line[7]
  												A    =      line[1]
  												if not isinstance(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE):
  																	raise ValueError(F"""Training input {text_a} is not a string""")
  												if not isinstance(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE):
  																	raise ValueError(F"""Training input {text_b} is not a string""")
  												if not isinstance(__SCREAMING_SNAKE_CASE  ,  __SCREAMING_SNAKE_CASE):
  																	raise ValueError(F"""Training label {label} is not a string""")
  												examples.append(InputExample(guid=__SCREAMING_SNAKE_CASE  ,  text_a=__SCREAMING_SNAKE_CASE  ,  text_b=__SCREAMING_SNAKE_CASE  ,  label=__SCREAMING_SNAKE_CASE))
  							return examples
  
  
  		def       SCREAMING_SNAKE_CASE__     (self				:	str):
  							return ["contradiction", "entailment", "neutral"]
  
  __A  :					Optional[int]												=	{
      'xnli': XnliProcessor,
  }
  
  __A  :					Union[str, Any]												=	{
      'xnli': 'classification',
  }
  
  __A  :					Tuple												=	{
      'xnli': 3,
  }
  
  
  
  
  
  