code: 
  
  
  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
  
  
  lowercase_								=    get_logger(__name__)
  
  
  def 							SCREAMING_SNAKE_CASE					(  _UpperCAmelCase				):
  						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 (      lowerCAmelCase_	):
  
  
  
  
  
  
  
  							'''simple docstring'''
  							_A  				=  False  # to tell pytest it's not a test class
  
  
  
  
  
  
  
  							@staticmethod
  							def 		_UpperCAmelCase	(		SCREAMING_SNAKE_CASE_  :				Any		):
  													_a     =			parser.add_parser('test'		,				help='Test dataset implementation.'		)
  													test_parser.add_argument('--name'		,				type=lowerCamelCase_		,				default=lowerCamelCase_		,				help='Dataset processing name'		)
  													test_parser.add_argument(
  													    '--cache_dir'		,				type=lowerCamelCase_		,				default=lowerCamelCase_		,				help='Cache directory where the datasets are stored.'		,				)
  													test_parser.add_argument(
  													    '--data_dir'		,				type=lowerCamelCase_		,				default=lowerCamelCase_		,				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=lowerCamelCase_		,				help='Name of the dataset to download'		)
  													test_parser.set_defaults(func=_test_command_factory		)
  
  
  
  
  
  
  
  							def __init__(		self  :				Any		,				SCREAMING_SNAKE_CASE_  :				Dict		,				SCREAMING_SNAKE_CASE_  :				Optional[int]		,				SCREAMING_SNAKE_CASE_  :				Any		,				SCREAMING_SNAKE_CASE_  :				List[str]		,				SCREAMING_SNAKE_CASE_  :				str		,				SCREAMING_SNAKE_CASE_  :				List[str]		,				SCREAMING_SNAKE_CASE_  :				Tuple		,				SCREAMING_SNAKE_CASE_  :				str		,				SCREAMING_SNAKE_CASE_  :				str		,				):
  													_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 		_UpperCAmelCase	(		self  :				Optional[int]		):
  													fl_logger().setLevel(lowerCamelCase_		)
  													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(lowerCamelCase_		)
  													_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=lowerCamelCase_		,				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=lowerCamelCase_		,				)
  																			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(lowerCamelCase_		).name + '.py'
  																									_a     =			os.path.join(lowerCamelCase_		,				lowerCamelCase_		)
  																									if os.path.isfile(lowerCamelCase_		):
  																															_a     =			os.path.dirname(lowerCamelCase_		)
  																									elif os.path.isfile(lowerCamelCase_		):
  																															_a     =			path
  																									elif os.path.isdir(lowerCamelCase_		):  # 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(lowerCamelCase_		,				'README.md'		)
  																															copyfile(lowerCamelCase_		,				lowerCamelCase_		)
  																															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(lowerCamelCase_		):
  																															logger.warning(f"""Clearing cache at {download_dir}"""		)
  																															rmtree(lowerCamelCase_		)
  
  													print('Test successful.'		)
  
  
  
style_context: 
  
  
  from typing import List, Union
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowercase_								=    logging.get_logger(__name__)
  
  lowercase_								=    {
      'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/config.json',
      # See all LED models at https://huggingface.co/models?filter=led
  }
  
  
  
  
  class 					_UpperCamelCase (      lowerCamelCase__	):
  
  
  
  
  
  
  
  							'''simple docstring'''
  							_A  				=  "led"
  							_A  				=  {
  							    "num_attention_heads": "encoder_attention_heads",
  							    "hidden_size": "d_model",
  							    "attention_probs_dropout_prob": "attention_dropout",
  							    "initializer_range": "init_std",
  							}
  
  
  
  
  
  
  
  							def __init__(		self  :				List[str]		,				SCREAMING_SNAKE_CASE_  :				List[str]=5_0_2_6_5		,				SCREAMING_SNAKE_CASE_  :				str=1_6_3_8_4		,				SCREAMING_SNAKE_CASE_  :				List[Any]=1_0_2_4		,				SCREAMING_SNAKE_CASE_  :				List[str]=1_2		,				SCREAMING_SNAKE_CASE_  :				Any=4_0_9_6		,				SCREAMING_SNAKE_CASE_  :				Optional[Any]=1_6		,				SCREAMING_SNAKE_CASE_  :				str=1_2		,				SCREAMING_SNAKE_CASE_  :				List[Any]=4_0_9_6		,				SCREAMING_SNAKE_CASE_  :				List[str]=1_6		,				SCREAMING_SNAKE_CASE_  :				Optional[int]=0.0		,				SCREAMING_SNAKE_CASE_  :				Union[str, Any]=0.0		,				SCREAMING_SNAKE_CASE_  :				List[Any]=True		,				SCREAMING_SNAKE_CASE_  :				str=True		,				SCREAMING_SNAKE_CASE_  :				List[str]="gelu"		,				SCREAMING_SNAKE_CASE_  :				List[Any]=1_0_2_4		,				SCREAMING_SNAKE_CASE_  :				Tuple=0.1		,				SCREAMING_SNAKE_CASE_  :				Dict=0.0		,				SCREAMING_SNAKE_CASE_  :				Optional[Any]=0.0		,				SCREAMING_SNAKE_CASE_  :				Tuple=0.02		,				SCREAMING_SNAKE_CASE_  :				str=2		,				SCREAMING_SNAKE_CASE_  :				Tuple=0.0		,				SCREAMING_SNAKE_CASE_  :				Optional[int]=1		,				SCREAMING_SNAKE_CASE_  :				str=0		,				SCREAMING_SNAKE_CASE_  :				Union[str, Any]=2		,				SCREAMING_SNAKE_CASE_  :				Union[List[int], int] = 5_1_2		,				**SCREAMING_SNAKE_CASE_  :				Dict		,				):
  													_a     =			vocab_size
  													_a     =			max_encoder_position_embeddings
  													_a     =			max_decoder_position_embeddings
  													_a     =			d_model
  													_a     =			encoder_ffn_dim
  													_a     =			encoder_layers
  													_a     =			encoder_attention_heads
  													_a     =			decoder_ffn_dim
  													_a     =			decoder_layers
  													_a     =			decoder_attention_heads
  													_a     =			dropout
  													_a     =			attention_dropout
  													_a     =			activation_dropout
  													_a     =			activation_function
  													_a     =			init_std
  													_a     =			encoder_layerdrop
  													_a     =			decoder_layerdrop
  													_a     =			classifier_dropout
  													_a     =			use_cache
  													_a     =			encoder_layers
  													_a     =			attention_window
  
  													super().__init__(
  													    pad_token_id=SCREAMING_SNAKE_CASE_		,				bos_token_id=SCREAMING_SNAKE_CASE_		,				eos_token_id=SCREAMING_SNAKE_CASE_		,				is_encoder_decoder=SCREAMING_SNAKE_CASE_		,				decoder_start_token_id=SCREAMING_SNAKE_CASE_		,				**SCREAMING_SNAKE_CASE_		,				)
  
  
  