
"""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


snake_case    =		get_logger(__name__)

def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_			):
					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	(       __magic_name__      ):

				"""simple docstring"""



				UpperCAmelCase_				:      str						  =				False  # to tell pytest it's not a test class


				@staticmethod
				def 							A					(				lowercase__			)    ->    Optional[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	parser.add_parser('test'		,	help='Test dataset implementation.'			)
									test_parser.add_argument('--name'		,	type=lowercase__		,	default=lowercase__		,	help='Dataset processing name'			)
									test_parser.add_argument(
									    '--cache_dir'		,	type=lowercase__		,	default=lowercase__		,	help='Cache directory where the datasets are stored.'		,	)
									test_parser.add_argument(
									    '--data_dir'		,	type=lowercase__		,	default=lowercase__		,	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=lowercase__		,	help='Name of the dataset to download'			)
									test_parser.set_defaults(func=_test_command_factory			)


				def __init__(				self		,	lowercase__		,	lowercase__		,	lowercase__		,	lowercase__		,	lowercase__		,	lowercase__		,	lowercase__		,	lowercase__		,	lowercase__		,	)    ->    Optional[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	dataset
									SCREAMING_SNAKE_CASE				=	name
									SCREAMING_SNAKE_CASE				=	cache_dir
									SCREAMING_SNAKE_CASE				=	data_dir
									SCREAMING_SNAKE_CASE				=	all_configs
									SCREAMING_SNAKE_CASE				=	save_infos
									SCREAMING_SNAKE_CASE				=	ignore_verifications
									SCREAMING_SNAKE_CASE				=	force_redownload
									SCREAMING_SNAKE_CASE				=	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:
														SCREAMING_SNAKE_CASE				=	True




				def 							A					(				self			)    ->    Union[str, Any]:
									"""simple docstring"""







									fl_logger().setLevel(lowercase__			)
									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			)
									SCREAMING_SNAKE_CASE	,    SCREAMING_SNAKE_CASE				=	self._dataset, self._name
									SCREAMING_SNAKE_CASE				=	dataset_module_factory(lowercase__			)
									SCREAMING_SNAKE_CASE				=	import_main_class(module.module_path			)
									SCREAMING_SNAKE_CASE				=	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=lowercase__		,	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})'''			)
														SCREAMING_SNAKE_CASE				=	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=lowercase__		,	)
														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:
																			SCREAMING_SNAKE_CASE				=	os.path.join(builder_cls.get_imported_module_dir()		,	'README.md'			)
																			SCREAMING_SNAKE_CASE				=	Path(lowercase__			).name + '.py'
																			SCREAMING_SNAKE_CASE				=	os.path.join(lowercase__		,	lowercase__			)
																			if os.path.isfile(lowercase__			):
																								SCREAMING_SNAKE_CASE				=	os.path.dirname(lowercase__			)
																			elif os.path.isfile(lowercase__			):
																								SCREAMING_SNAKE_CASE				=	path
																			elif os.path.isdir(lowercase__			):  # for local directories containing only data files
																								SCREAMING_SNAKE_CASE				=	path
																			else:  # in case of a remote dataset
																								SCREAMING_SNAKE_CASE				=	None
																								print(f'''Dataset card saved at {dataset_readme_path}'''			)

																			# Move dataset_info back to the user
																			if dataset_dir is not None:
																								SCREAMING_SNAKE_CASE				=	os.path.join(lowercase__		,	'README.md'			)
																								copyfile(lowercase__		,	lowercase__			)
																								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			)
																			SCREAMING_SNAKE_CASE				=	os.path.join(self._cache_dir		,	datasets.config.DOWNLOADED_DATASETS_DIR			)
																			if os.path.isdir(lowercase__			):
																								logger.warning(f'''Clearing cache at {download_dir}'''			)
																								rmtree(lowercase__			)

									print('Test successful.'			)


"""simple docstring"""




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
from ...utils import logging


snake_case    =		logging.get_logger(__name__)

snake_case    =		{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

snake_case    =		{
    'vocab_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json',
    },
}




class      UpperCamelCase	(       __magic_name__      ):

				"""simple docstring"""



				def __init__(				self		,	lowercase__=None		,	lowercase__=None		,	lowercase__=False		,	lowercase__=True		,	lowercase__=False		,	lowercase__="<s>"		,	lowercase__="</s>"		,	lowercase__="<unk>"		,	lowercase__="<sep>"		,	lowercase__="<pad>"		,	lowercase__="<cls>"		,	lowercase__="<mask>"		,	lowercase__=["<eop>", "<eod>"]		,	**lowercase__		,	)    ->    int:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	AddedToken(lowercase__		,	lstrip=lowercase__		,	rstrip=lowercase__			) if isinstance(lowercase__		,	lowercase__			) else mask_token

									super().__init__(
									    vocab_file=lowercase__		,	tokenizer_file=lowercase__		,	do_lower_case=lowercase__		,	remove_space=lowercase__		,	keep_accents=lowercase__		,	bos_token=lowercase__		,	eos_token=lowercase__		,	unk_token=lowercase__		,	sep_token=lowercase__		,	pad_token=lowercase__		,	cls_token=lowercase__		,	mask_token=lowercase__		,	additional_special_tokens=lowercase__		,	**lowercase__		,	)

									SCREAMING_SNAKE_CASE				=	3
									SCREAMING_SNAKE_CASE				=	do_lower_case
									SCREAMING_SNAKE_CASE				=	remove_space
									SCREAMING_SNAKE_CASE				=	keep_accents
									SCREAMING_SNAKE_CASE				=	vocab_file
									SCREAMING_SNAKE_CASE				=	False if not self.vocab_file else True

									try:
														import jieba
									except ModuleNotFoundError as error:
														raise error.__class__(
														    'You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '
														    'See https://pypi.org/project/jieba/ for installation.'			)
									SCREAMING_SNAKE_CASE				=	jieba
									SCREAMING_SNAKE_CASE				=	str.maketrans(' \n'		,	'\u2582\u2583'			)


				def 							A					(				self		,	lowercase__		,	lowercase__ = None			)    ->    List[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[self.sep_token_id]
									SCREAMING_SNAKE_CASE				=	[self.cls_token_id]
									if token_ids_a is None:
														return token_ids_a + sep + cls
									return token_ids_a + sep + token_ids_a + sep + cls


				def 							A					(				self		,	lowercase__		,	lowercase__ = None			)    ->    List[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[self.sep_token_id]
									SCREAMING_SNAKE_CASE				=	[2]

									if token_ids_a is None:
														return len(token_ids_a + sep			) * [0] + cls_segment_id
									return len(token_ids_a + sep			) * [0] + len(token_ids_a + sep			) * [1] + cls_segment_id


				def 							A					(				self		,	lowercase__		,	lowercase__ = None			)    ->    Tuple[str]:
									"""simple docstring"""







									if not self.can_save_slow_tokenizer:
														raise ValueError(
														    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
														    'tokenizer.'			)

									if not os.path.isdir(lowercase__			):
														logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''			)
														return
									SCREAMING_SNAKE_CASE				=	os.path.join(
									    lowercase__		,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)

									if os.path.abspath(self.vocab_file			) != os.path.abspath(lowercase__			):
														copyfile(self.vocab_file		,	lowercase__			)

									return (out_vocab_file,)


				def 							A					(				self		,	lowercase__		,	*lowercase__		,	**lowercase__			)    ->    Any:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[
									    ' '.join([x.translate(self.translator			) for x in self.jieba.cut(lowercase__		,	cut_all=lowercase__			)]			)
									    for text in batch_text_or_text_pairs
									]
									return super()._batch_encode_plus(lowercase__		,	*lowercase__		,	**lowercase__			)




				def 							A					(				self		,	*lowercase__		,	**lowercase__			)    ->    Optional[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	super()._decode(*lowercase__		,	**lowercase__			)
									SCREAMING_SNAKE_CASE				=	text.replace(' '		,	''			).replace('\u2582'		,	' '			).replace('\u2583'		,	'\n'			)
									return text
