from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase							   =      {'configuration_levit': ['LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LevitConfig', 'LevitOnnxConfig']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase							   =      ['LevitFeatureExtractor']
		UpperCAmelCase							   =      ['LevitImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase							   =      [
		    'LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'LevitForImageClassification',
		    'LevitForImageClassificationWithTeacher',
		    'LevitModel',
		    'LevitPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_levit import LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, LevitConfig, LevitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_levit import LevitFeatureExtractor
				from .image_processing_levit import LevitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_levit import (
				    LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LevitForImageClassification,
				    LevitForImageClassificationWithTeacher,
				    LevitModel,
				    LevitPreTrainedModel,
				)
else:
		import sys

		UpperCAmelCase							   =      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property






class 							_SCREAMING_SNAKE_CASE(   unittest.TestCase	):
   @cached_property
   def _lowercase(    self    )	->List[str]:
        return BlenderbotTokenizer.from_pretrained('''facebook/blenderbot-3B'''    )
   @cached_property
   def _lowercase(    self    )	->str:
        return BlenderbotTokenizerFast.from_pretrained('''facebook/blenderbot-3B'''    )
   def _lowercase(    self    )	->str:
        a  :    Optional[int]				=						self.tokenizer_ab
        a  :    List[Any]				=						''' I am a small frog.'''
        a  :    Optional[Any]				=						tok([src_text]							,     padding=lowerCAmelCase_							,     truncation=lowerCAmelCase_    )['''input_ids''']
        a  :    int				=						tok.batch_decode(lowerCAmelCase_							,     skip_special_tokens=lowerCAmelCase_							,     clean_up_tokenization_spaces=lowerCAmelCase_    )[0]
        assert src_text == decoded
   def _lowercase(    self    )	->Dict:
        a  :    List[Any]				=						self.rust_tokenizer_ab
        a  :    str				=						''' I am a small frog.'''
        a  :    Tuple				=						tok([src_text]							,     padding=lowerCAmelCase_							,     truncation=lowerCAmelCase_    )['''input_ids''']
        a  :    Optional[Any]				=						tok.batch_decode(lowerCAmelCase_							,     skip_special_tokens=lowerCAmelCase_							,     clean_up_tokenization_spaces=lowerCAmelCase_    )[0]
        assert src_text == decoded
   def _lowercase(    self    )	->Tuple:
        assert self.tokenizer_ab.add_prefix_space
        assert self.tokenizer_ab([''' Sam''', '''Sam''']    ).input_ids == [[55_02, 2], [55_02, 2]]


   def _lowercase(    self    )	->Optional[Any]:
        assert self.rust_tokenizer_ab.add_prefix_space
        assert self.rust_tokenizer_ab([''' Sam''', '''Sam''']    ).input_ids == [[55_02, 2], [55_02, 2]]