




from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest


@require_tokenizers
class 				__UpperCamelCase      (			__UpperCAmelCase	):





				'''simple docstring'''



				__a				:			Union[str, Any]					    =SqueezeBertTokenizer
				__a				:			List[str]					    =SqueezeBertTokenizerFast
				__a				:			Dict					    =True



				def    __snake_case		(			self							,			**UpperCAmelCase_    ):
											return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname							,			**UpperCAmelCase_    )






				@slow
				def    __snake_case		(			self    ):
											lowerCAmelCase =		SqueezeBertTokenizer.from_pretrained('''squeezebert/squeezebert-mnli-headless'''    )

											lowerCAmelCase =		tokenizer.encode('''sequence builders'''							,			add_special_tokens=UpperCAmelCase_    )
											lowerCAmelCase =		tokenizer.encode('''multi-sequence build'''							,			add_special_tokens=UpperCAmelCase_    )

											lowerCAmelCase =		tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_    )
											lowerCAmelCase =		tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_							,			UpperCAmelCase_    )

											assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
											assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
											    tokenizer.sep_token_id
											]









from typing import TYPE_CHECKING

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


UpperCAmelCase_    ={
    """configuration_bark""": [
        """BARK_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BarkCoarseConfig""",
        """BarkConfig""",
        """BarkFineConfig""",
        """BarkSemanticConfig""",
    ],
    """processing_bark""": ["""BarkProcessor"""],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase_    =[
		    """BARK_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """BarkFineModel""",
		    """BarkSemanticModel""",
		    """BarkCoarseModel""",
		    """BarkModel""",
		    """BarkPreTrainedModel""",
		    """BarkCausalModel""",
		]

if TYPE_CHECKING:
		from .configuration_bark import (
		    BARK_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BarkCoarseConfig,
		    BarkConfig,
		    BarkFineConfig,
		    BarkSemanticConfig,
		)
		from .processing_bark import BarkProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bark import (
				    BARK_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BarkCausalModel,
				    BarkCoarseModel,
				    BarkFineModel,
				    BarkModel,
				    BarkPreTrainedModel,
				    BarkSemanticModel,
				)

else:
		import sys

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



