from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__     :	Union[str, Any]				=			logging.get_logger(__name__)

UpperCamelCase__     :	Dict				=			{
    'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
    # See all Donut models at https://huggingface.co/models?filter=donut-swin
}


class 				_lowercase	(      a__   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Union[str, Any]      							=   "donut-swin"

      UpperCAmelCase_      :      List[Any]      							=   {
          "num_attention_heads": "num_heads",
          "num_hidden_layers": "num_layers",
      }




      def __init__(				self					,lowerCamelCase_=224					,lowerCamelCase_=4					,lowerCamelCase_=3					,lowerCamelCase_=96					,lowerCamelCase_=[2, 2, 6, 2]					,lowerCamelCase_=[3, 6, 12, 24]					,lowerCamelCase_=7					,lowerCamelCase_=4.0					,lowerCamelCase_=True					,lowerCamelCase_=0.0					,lowerCamelCase_=0.0					,lowerCamelCase_=0.1					,lowerCamelCase_="gelu"					,lowerCamelCase_=False					,lowerCamelCase_=0.02					,lowerCamelCase_=1e-5					,**lowerCamelCase_					,)			->			List[Any]:



         '''simple docstring'''



         super().__init__(**lowerCamelCase_							)

         UpperCAmelCase__							:				Any   				=  image_size
         UpperCAmelCase__							:				List[Any]   				=  patch_size
         UpperCAmelCase__							:				List[str]   				=  num_channels
         UpperCAmelCase__							:				Any   				=  embed_dim
         UpperCAmelCase__							:				Optional[int]   				=  depths
         UpperCAmelCase__							:				Any   				=  len(lowerCamelCase_							)
         UpperCAmelCase__							:				int   				=  num_heads
         UpperCAmelCase__							:				List[Any]   				=  window_size
         UpperCAmelCase__							:				List[Any]   				=  mlp_ratio
         UpperCAmelCase__							:				List[str]   				=  qkv_bias
         UpperCAmelCase__							:				List[Any]   				=  hidden_dropout_prob
         UpperCAmelCase__							:				Optional[int]   				=  attention_probs_dropout_prob
         UpperCAmelCase__							:				Optional[int]   				=  drop_path_rate
         UpperCAmelCase__							:				List[Any]   				=  hidden_act
         UpperCAmelCase__							:				str   				=  use_absolute_embeddings
         UpperCAmelCase__							:				Optional[Any]   				=  layer_norm_eps
         UpperCAmelCase__							:				Union[str, Any]   				=  initializer_range
         # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
         # this indicates the channel dimension after the last stage of the model
         UpperCAmelCase__							:				Optional[Any]   				=  int(embed_dim * 2 ** (len(lowerCamelCase_							) - 1)							)





'''simple docstring'''

from typing import TYPE_CHECKING

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


UpperCamelCase__     :	List[Any]				=			{'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__     :	int				=			['YolosFeatureExtractor']
  UpperCamelCase__     :	int				=			['YolosImageProcessor']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__     :	int				=			[
      'YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST',
      'YolosForObjectDetection',
      'YolosModel',
      'YolosPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig, YolosOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_yolos import YolosFeatureExtractor
    from .image_processing_yolos import YolosImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_yolos import (
        YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST,
        YolosForObjectDetection,
        YolosModel,
        YolosPreTrainedModel,
    )


else:
  import sys

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




