





from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE :					Union[str, Any]			=	{"configuration_levit": ["LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LevitConfig", "LevitOnnxConfig"]}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					int			=	["LevitFeatureExtractor"]
   _SCREAMING_SNAKE_CASE :					str			=	["LevitImageProcessor"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					Optional[int]			=	[
       "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

   _SCREAMING_SNAKE_CASE :					str			=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE :					str			=	{
    """configuration_donut_swin""": ["""DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DonutSwinConfig"""],
    """processing_donut""": ["""DonutProcessor"""],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					List[Any]			=	[
       """DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """DonutSwinModel""",
       """DonutSwinPreTrainedModel""",
   ]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					List[Any]			=	["""DonutFeatureExtractor"""]
   _SCREAMING_SNAKE_CASE :					Tuple			=	["""DonutImageProcessor"""]


if TYPE_CHECKING:
   from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
   from .processing_donut import DonutProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_donut_swin import (
          DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          DonutSwinModel,
          DonutSwinPreTrainedModel,
      )

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_donut import DonutFeatureExtractor
      from .image_processing_donut import DonutImageProcessor

else:
   import sys

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




