

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     snake_case_			(				_a			, unittest.TestCase							):


							"""simple docstring"""





							__UpperCAmelCase       =BartphoTokenizer
							__UpperCAmelCase       =False
							__UpperCAmelCase       =True




							def        A__  ( self							):
												super().setUp()

												__lowerCAmelCase					=							['▁This', '▁is', '▁a', '▁t', 'est']
												__lowerCAmelCase					=							dict(zip(_A					,						range(len(_A							)							)							)							)
												__lowerCAmelCase					=							{'unk_token': '<unk>'}

												__lowerCAmelCase					=							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					=							BartphoTokenizer(_A					,						self.monolingual_vocab_file					,						**self.special_tokens_map							)
												tokenizer.save_pretrained(self.tmpdirname							)




							def        A__  ( self					,						**_A							):
												kwargs.update(self.special_tokens_map							)
												return BartphoTokenizer.from_pretrained(self.tmpdirname					,						**_A							)




							def        A__  ( self					,						_A							):
												__lowerCAmelCase					=							'This is a là test'
												__lowerCAmelCase					=							'This is a<unk><unk> test'
												return input_text, output_text




							def        A__  ( self							):
												__lowerCAmelCase					=							BartphoTokenizer(_A					,						self.monolingual_vocab_file					,						**self.special_tokens_map							)
												__lowerCAmelCase					=							'This is a là test'
												__lowerCAmelCase					=							'▁This ▁is ▁a ▁l à ▁t est'.split()
												__lowerCAmelCase					=							tokenizer.tokenize(_A							)
												self.assertListEqual(_A					,						_A							)

												__lowerCAmelCase					=							tokens + [tokenizer.unk_token]
												__lowerCAmelCase					=							[4, 5, 6, 3, 3, 7, 8, 3]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(_A							)					,						_A							)









from typing import TYPE_CHECKING

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


lowerCamelCase      				=     {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase      				=     [
		    '''UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''UniSpeechForCTC''',
		    '''UniSpeechForPreTraining''',
		    '''UniSpeechForSequenceClassification''',
		    '''UniSpeechModel''',
		    '''UniSpeechPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_unispeech import (
				    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
				    UniSpeechForCTC,
				    UniSpeechForPreTraining,
				    UniSpeechForSequenceClassification,
				    UniSpeechModel,
				    UniSpeechPreTrainedModel,
				)

else:
		import sys

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






