

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 	lowercase    (				_a    ,							unittest.TestCase							):


		"""simple docstring"""




		a__					       =  BartphoTokenizer
		a__					       =  False
		a__					       =  True


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

			_UpperCamelCase   :		List[Any]			=						['▁This', '▁is', '▁a', '▁t', 'est']
			_UpperCamelCase   :		Optional[Any]			=						dict(zip(snake_case_	,       range(len(snake_case_))))
			_UpperCamelCase   :		Tuple			=						{'unk_token': '<unk>'}

			_UpperCamelCase   :		List[Any]			=						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''')

			_UpperCamelCase   :		Optional[Any]			=						BartphoTokenizer(snake_case_	,       self.monolingual_vocab_file	,       **self.special_tokens_map)
			tokenizer.save_pretrained(self.tmpdirname)


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


		def 		A__					(				self	,       __snake_case):
			_UpperCamelCase   :		Optional[Any]			=						'This is a là test'
			_UpperCamelCase   :		Any			=						'This is a<unk><unk> test'
			return input_text, output_text






		def 		A__					(				self):
			_UpperCamelCase   :		List[str]			=						BartphoTokenizer(snake_case_	,       self.monolingual_vocab_file	,       **self.special_tokens_map)
			_UpperCamelCase   :		Any			=						'This is a là test'
			_UpperCamelCase   :		Optional[int]			=						'▁This ▁is ▁a ▁l à ▁t est'.split()
			_UpperCamelCase   :		Tuple			=						tokenizer.tokenize(snake_case_)
			self.assertListEqual(snake_case_	,       snake_case_)

			_UpperCamelCase   :		Union[str, Any]			=						tokens + [tokenizer.unk_token]
			_UpperCamelCase   :		List[str]			=						[4, 5, 6, 3, 3, 7, 8, 3]
			self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case_)	,       snake_case_)







from typing import TYPE_CHECKING

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


lowerCAmelCase__								=		{
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		["""BlipImageProcessor"""]


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		[
							    """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """BlipModel""",
							    """BlipPreTrainedModel""",
							    """BlipForConditionalGeneration""",
							    """BlipForQuestionAnswering""",
							    """BlipVisionModel""",
							    """BlipTextModel""",
							    """BlipForImageTextRetrieval""",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		[
							    """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFBlipModel""",
							    """TFBlipPreTrainedModel""",
							    """TFBlipForConditionalGeneration""",
							    """TFBlipForQuestionAnswering""",
							    """TFBlipVisionModel""",
							    """TFBlipTextModel""",
							    """TFBlipForImageTextRetrieval""",
							]

if TYPE_CHECKING:
							from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
							from .processing_blip import BlipProcessor

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_blip import BlipImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_blip import (
														    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BlipForConditionalGeneration,
														    BlipForImageTextRetrieval,
														    BlipForQuestionAnswering,
														    BlipModel,
														    BlipPreTrainedModel,
														    BlipTextModel,
														    BlipVisionModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_blip import (
														    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFBlipForConditionalGeneration,
														    TFBlipForImageTextRetrieval,
														    TFBlipForQuestionAnswering,
														    TFBlipModel,
														    TFBlipPreTrainedModel,
														    TFBlipTextModel,
														    TFBlipVisionModel,
														)

else:
							import sys

							lowerCAmelCase__								=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




