






'''simple docstring'''






import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


__A    	=   logging.get_logger(__name__)




class a_    (    UpperCamelCase_							):







   def __init__(self					,   *__a					,   **__a)			->      None:
      """simple docstring"""






      warnings.warn(
          'The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
          ' use FlavaImageProcessor instead.'					,   __a					,   )
      super().__init__(*__a					,   **__a)







'''simple docstring'''






from typing import TYPE_CHECKING

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


__A    	=   {
    '''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
    '''tokenization_biogpt''': ['''BioGptTokenizer'''],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __A    	=   [
          '''BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''BioGptForCausalLM''',
          '''BioGptForTokenClassification''',
          '''BioGptForSequenceClassification''',
          '''BioGptModel''',
          '''BioGptPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
      from .tokenization_biogpt import BioGptTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_biogpt import (
                BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                BioGptForCausalLM,
                BioGptForSequenceClassification,
                BioGptForTokenClassification,
                BioGptModel,
                BioGptPreTrainedModel,
            )


else:
      import sys

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