






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


__UpperCAmelCase										=		get_logger(__name__)




def   lowercase__   (  __snake_case					:							List[Any]						):


					'''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 						lowerCamelCase   (_snake_case    ):







		'''simple docstring'''



		_snake_case					:					Dict 		=						False  # to tell pytest it's not a test class



		@staticmethod
		def       __UpperCAmelCase    (							_UpperCamelCase     )			->							Any:
							UpperCAmelCase_					:   List[Any]   =		parser.add_parser('test'       ,	help='Test dataset implementation.'     )
							test_parser.add_argument('--name'       ,	type=_UpperCamelCase       ,	default=_UpperCamelCase       ,	help='Dataset processing name'     )
							test_parser.add_argument(
							    '--cache_dir'       ,	type=_UpperCamelCase       ,	default=_UpperCamelCase       ,	help='Cache directory where the datasets are stored.'       ,	)
							test_parser.add_argument(
							    '--data_dir'       ,	type=_UpperCamelCase       ,	default=_UpperCamelCase       ,	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=_UpperCamelCase       ,	help='Name of the dataset to download'     )
							test_parser.set_defaults(func=_test_command_factory     )



		def __init__(							self       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	_UpperCamelCase       ,	)			->							List[str]:
							UpperCAmelCase_					:   Dict   =		dataset
							UpperCAmelCase_					:   Optional[Any]   =		name
							UpperCAmelCase_					:   int   =		cache_dir
							UpperCAmelCase_					:   Tuple   =		data_dir
							UpperCAmelCase_					:   Dict   =		all_configs
							UpperCAmelCase_					:   Optional[Any]   =		save_infos
							UpperCAmelCase_					:   Optional[int]   =		ignore_verifications
							UpperCAmelCase_					:   Tuple   =		force_redownload
							UpperCAmelCase_					:   Union[str, Any]   =		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:
												UpperCAmelCase_					:   Any   =		True



		def       __UpperCAmelCase    (							self     )			->							List[Any]:
							fl_logger().setLevel(_UpperCamelCase     )
							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     )
							UpperCAmelCase_ ,						UpperCAmelCase_					:   Optional[int]   =		self._dataset, self._name
							UpperCAmelCase_					:   Optional[Any]   =		dataset_module_factory(_UpperCamelCase     )
							UpperCAmelCase_					:   List[str]   =		import_main_class(module.module_path     )
							UpperCAmelCase_					:   Union[str, Any]   =		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=_UpperCamelCase       ,	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})"     )
												UpperCAmelCase_					:   Union[str, Any]   =		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=_UpperCamelCase       ,	)
												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:
																	UpperCAmelCase_					:   Union[str, Any]   =		os.path.join(builder_cls.get_imported_module_dir()       ,	'README.md'     )
																	UpperCAmelCase_					:   Any   =		Path(_UpperCamelCase     ).name + '.py'
																	UpperCAmelCase_					:   Optional[int]   =		os.path.join(_UpperCamelCase       ,	_UpperCamelCase     )
																	if os.path.isfile(_UpperCamelCase     ):
																						UpperCAmelCase_					:   Optional[int]   =		os.path.dirname(_UpperCamelCase     )
																	elif os.path.isfile(_UpperCamelCase     ):
																						UpperCAmelCase_					:   List[Any]   =		path
																	elif os.path.isdir(_UpperCamelCase     ):  # for local directories containing only data files
																						UpperCAmelCase_					:   Any   =		path
																	else:  # in case of a remote dataset
																						UpperCAmelCase_					:   Optional[Any]   =		None
																						print(f"Dataset card saved at {dataset_readme_path}"     )

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

							print('Test successful.'     )














import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin



class 						lowerCamelCase   (_snake_case				,						unittest.TestCase    ):







		'''simple docstring'''



		_snake_case					:					Tuple 		=						BertweetTokenizer
		_snake_case					:					List[str] 		=						False



		def       __UpperCAmelCase    (							self     )			->							Optional[int]:
							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							UpperCAmelCase_					:   Optional[int]   =		['I', 'm', 'V@@', 'R@@', 'r', 'e@@']
							UpperCAmelCase_					:   Dict   =		dict(zip(_UpperCamelCase       ,	range(len(_UpperCamelCase     )     )     )     )
							UpperCAmelCase_					:   List[Any]   =		['#version: 0.2', 'a m</w>']
							UpperCAmelCase_					:   Union[str, Any]   =		{'unk_token': '<unk>'}

							UpperCAmelCase_					:   Optional[Any]   =		os.path.join(self.tmpdirname       ,	VOCAB_FILES_NAMES['vocab_file']     )
							UpperCAmelCase_					:   List[str]   =		os.path.join(self.tmpdirname       ,	VOCAB_FILES_NAMES['merges_file']     )
							with open(self.vocab_file       ,	'w'       ,	encoding='utf-8'     ) as fp:
												for token in vocab_tokens:
																	fp.write(f"{token} {vocab_tokens[token]}\n"     )
							with open(self.merges_file       ,	'w'       ,	encoding='utf-8'     ) as fp:
												fp.write('\n'.join(_UpperCamelCase     )     )



		def       __UpperCAmelCase    (							self       ,	**_UpperCamelCase     )			->							List[Any]:
							kwargs.update(self.special_tokens_map     )
							return BertweetTokenizer.from_pretrained(self.tmpdirname       ,	**_UpperCamelCase     )



		def       __UpperCAmelCase    (							self       ,	_UpperCamelCase     )			->							List[Any]:
							UpperCAmelCase_					:   Any   =		'I am VinAI Research'
							UpperCAmelCase_					:   Any   =		'I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
							return input_text, output_text



		def       __UpperCAmelCase    (							self     )			->							Tuple:
							UpperCAmelCase_					:   Union[str, Any]   =		BertweetTokenizer(self.vocab_file       ,	self.merges_file       ,	**self.special_tokens_map     )
							UpperCAmelCase_					:   Optional[Any]   =		'I am VinAI Research'
							UpperCAmelCase_					:   str   =		'I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
							UpperCAmelCase_					:   Any   =		tokenizer.tokenize(_UpperCamelCase     )
							self.assertListEqual(_UpperCamelCase       ,	_UpperCamelCase     )

							UpperCAmelCase_					:   Optional[int]   =		tokens + [tokenizer.unk_token]

							UpperCAmelCase_					:   List[str]   =		[4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase     )       ,	_UpperCamelCase     )






