




from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE			:      Optional[Any]      			={
    """configuration_mobilenet_v1""": [
        """MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MobileNetV1Config""",
        """MobileNetV1OnnxConfig""",
    ],
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __SCREAMING_SNAKE_CASE			:      Any      			=["""MobileNetV1FeatureExtractor"""]
      __SCREAMING_SNAKE_CASE			:      Dict      			=["""MobileNetV1ImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __SCREAMING_SNAKE_CASE			:      List[str]      			=[
          """MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """MobileNetV1ForImageClassification""",
          """MobileNetV1Model""",
          """MobileNetV1PreTrainedModel""",
          """load_tf_weights_in_mobilenet_v1""",
      ]


if TYPE_CHECKING:
      from .configuration_mobilenet_va import (
          MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
          MobileNetVaConfig,
          MobileNetVaOnnxConfig,
      )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
            from .image_processing_mobilenet_va import MobileNetVaImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mobilenet_va import (
                MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
                MobileNetVaForImageClassification,
                MobileNetVaModel,
                MobileNetVaPreTrainedModel,
                load_tf_weights_in_mobilenet_va,
            )


else:
      import sys

      __SCREAMING_SNAKE_CASE			:      Any      			=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





import unittest

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






class 	A	(						unittest.TestCase						):
     """simple docstring"""

     @cached_property
     def        __snake_case      (			self     :      Union[str, Any]	) ->				str:
           return BlenderbotTokenizer.from_pretrained('facebook/blenderbot-3B'	)




     @cached_property
     def        __snake_case      (			self     :      Tuple	) ->				Dict:
           return BlenderbotTokenizerFast.from_pretrained('facebook/blenderbot-3B'	)




     def        __snake_case      (			self     :      List[str]	) ->				int:
           lowerCamelCase__					     = self.tokenizer_ab
           lowerCamelCase__					     = ' I am a small frog.'
           lowerCamelCase__					     = tok([src_text]		,     padding=A__		,     truncation=A__	)['input_ids']
           lowerCamelCase__					     = tok.batch_decode(A__		,     skip_special_tokens=A__		,     clean_up_tokenization_spaces=A__	)[0]
           assert src_text == decoded




     def        __snake_case      (			self     :      List[str]	) ->				str:
           lowerCamelCase__					     = self.rust_tokenizer_ab
           lowerCamelCase__					     = ' I am a small frog.'
           lowerCamelCase__					     = tok([src_text]		,     padding=A__		,     truncation=A__	)['input_ids']
           lowerCamelCase__					     = tok.batch_decode(A__		,     skip_special_tokens=A__		,     clean_up_tokenization_spaces=A__	)[0]
           assert src_text == decoded




     def        __snake_case      (			self     :      Any	) ->				str:
           assert self.tokenizer_ab.add_prefix_space
           assert self.tokenizer_ab([' Sam', 'Sam']	).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]




     def        __snake_case      (			self     :      str	) ->				Union[str, Any]:
           assert self.rust_tokenizer_ab.add_prefix_space
           assert self.rust_tokenizer_ab([' Sam', 'Sam']	).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]