




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase__			:       Optional[int]         =							{
    'configuration_upernet': ['UperNetConfig'],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__			:       List[str]         =							[
       'UperNetForSemanticSegmentation',
       'UperNetPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_upernet import UperNetConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
   import sys

   lowerCamelCase__			:       int         =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


lowerCamelCase__			:       Dict         =							logging.get_logger(__name__)





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 def __init__(							self  :		List[Any]    ,    *_lowerCAmelCase  :		List[str]    ,    **_lowerCAmelCase  :		Optional[int]						):
       warnings.warn(
           'The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use LayoutLMv2ImageProcessor instead.'    ,    _lowerCAmelCase    ,    )
       super().__init__(*_lowerCAmelCase    ,    **_lowerCAmelCase						)