


"""simple docstring"""




import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase						=		get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')





class  _a							(    _lowercase					,						unittest.TestCase):
	_a  :  Tuple				   =							BartphoTokenizer
	_a  :  Optional[int]				   =							False
	_a  :  Dict				   =							True




	def 							UpperCAmelCase__( self						:		str		)->	str:
			super().setUp()

			lowerCAmelCase__       :      Optional[int]   					= ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
			lowerCAmelCase__       :      Dict   					= dict(zip(_SCREAMING_SNAKE_CASE		, range(len(_SCREAMING_SNAKE_CASE		)		)		)		)
			lowerCAmelCase__       :      List[str]   					= {'''unk_token''': '''<unk>'''}

			lowerCAmelCase__       :      Optional[int]   					= os.path.join(self.tmpdirname		, VOCAB_FILES_NAMES['''monolingual_vocab_file''']		)
			with open(self.monolingual_vocab_file		, '''w'''		, encoding='''utf-8'''		) as fp:
					for token in vocab_tokens:
							fp.write(F'{token} {vocab_tokens[token]}\n'		)

			lowerCAmelCase__       :      List[str]   					= BartphoTokenizer(_SCREAMING_SNAKE_CASE		, self.monolingual_vocab_file		, **self.special_tokens_map		)
			tokenizer.save_pretrained(self.tmpdirname		)




	def 							UpperCAmelCase__( self						:		List[Any]		, **_SCREAMING_SNAKE_CASE						:		Optional[int]		)->	Optional[int]:
			kwargs.update(self.special_tokens_map		)
			return BartphoTokenizer.from_pretrained(self.tmpdirname		, **_SCREAMING_SNAKE_CASE		)




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		Optional[int]		)->	Dict:
			lowerCAmelCase__       :      Any   					= '''This is a là test'''
			lowerCAmelCase__       :      List[str]   					= '''This is a<unk><unk> test'''
			return input_text, output_text




	def 							UpperCAmelCase__( self						:		int		)->	Union[str, Any]:
			lowerCAmelCase__       :      Optional[Any]   					= BartphoTokenizer(_SCREAMING_SNAKE_CASE		, self.monolingual_vocab_file		, **self.special_tokens_map		)
			lowerCAmelCase__       :      Union[str, Any]   					= '''This is a là test'''
			lowerCAmelCase__       :      Optional[int]   					= '''▁This ▁is ▁a ▁l à ▁t est'''.split()
			lowerCAmelCase__       :      Union[str, Any]   					= tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
			self.assertListEqual(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)

			lowerCAmelCase__       :      Dict   					= tokens + [tokenizer.unk_token]
			lowerCAmelCase__       :      List[Any]   					= [4, 5, 6, 3, 3, 7, 8, 3]
			self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)		, _SCREAMING_SNAKE_CASE		)








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase						=		{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		['''BeitFeatureExtractor''']
		lowerCamelCase						=		['''BeitImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BeitForImageClassification''',
		    '''BeitForMaskedImageModeling''',
		    '''BeitForSemanticSegmentation''',
		    '''BeitModel''',
		    '''BeitPreTrainedModel''',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''FlaxBeitForImageClassification''',
		    '''FlaxBeitForMaskedImageModeling''',
		    '''FlaxBeitModel''',
		    '''FlaxBeitPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_beit import BeitFeatureExtractor
				from .image_processing_beit import BeitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_beit import (
				    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BeitForImageClassification,
				    BeitForMaskedImageModeling,
				    BeitForSemanticSegmentation,
				    BeitModel,
				    BeitPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_beit import (
				    FlaxBeitForImageClassification,
				    FlaxBeitForMaskedImageModeling,
				    FlaxBeitModel,
				    FlaxBeitPreTrainedModel,
				)


else:
		import sys

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




