



'''simple docstring'''






import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


lowerCAmelCase: Optional[Any]							=						logging.get_logger(__name__)

class 							a__( lowerCamelCase__     ):







    def __init__(				self			:  Any						,      *__snake_case			:  Tuple						,      **__snake_case			:  Union[str, Any]     ):
      warnings.warn(
          'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
          ' use DonutImageProcessor instead.'						,      __snake_case						,      )
      super().__init__(*__snake_case						,      **__snake_case     )




'''simple docstring'''






from typing import TYPE_CHECKING

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


lowerCAmelCase: Optional[int]							=						{
    'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase: int							=						[
         'GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'GraphormerForGraphClassification',
         'GraphormerModel',
         'GraphormerPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_graphormer import (
              GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              GraphormerForGraphClassification,
              GraphormerModel,
              GraphormerPreTrainedModel,
          )


else:
     import sys

     lowerCAmelCase: str							=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)