



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase						    =  logging.get_logger(__name__)

_lowerCamelCase						    =  {
    """hustvl/yolos-small""": """https://huggingface.co/hustvl/yolos-small/resolve/main/config.json""",
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}

class       _SCREAMING_SNAKE_CASE	(_UpperCamelCase ):
     lowerCAmelCase					=			"yolos"





     def __init__(       self :							Dict     ,  UpperCamelCase :							Optional[Any]=7_6_8     ,  UpperCamelCase :							List[Any]=1_2     ,  UpperCamelCase :							Any=1_2     ,  UpperCamelCase :							List[Any]=3_0_7_2     ,  UpperCamelCase :							Optional[int]="gelu"     ,  UpperCamelCase :							Dict=0.0     ,  UpperCamelCase :							Optional[Any]=0.0     ,  UpperCamelCase :							Any=0.0_2     ,  UpperCamelCase :							Optional[int]=1E-12     ,  UpperCamelCase :							List[Any]=[5_1_2, 8_6_4]     ,  UpperCamelCase :							List[str]=1_6     ,  UpperCamelCase :							str=3     ,  UpperCamelCase :							Optional[Any]=True     ,  UpperCamelCase :							Optional[Any]=1_0_0     ,  UpperCamelCase :							List[str]=True     ,  UpperCamelCase :							Any=False     ,  UpperCamelCase :							List[str]=1     ,  UpperCamelCase :							str=5     ,  UpperCamelCase :							Optional[Any]=2     ,  UpperCamelCase :							Tuple=5     ,  UpperCamelCase :							Any=2     ,  UpperCamelCase :							Union[str, Any]=0.1     ,  **UpperCamelCase :							List[str]     ,  )->List[str]:
      super().__init__(**__a				)

      __SCREAMING_SNAKE_CASE       :    Dict       =	hidden_size
      __SCREAMING_SNAKE_CASE       :    Any       =	num_hidden_layers
      __SCREAMING_SNAKE_CASE       :    str       =	num_attention_heads
      __SCREAMING_SNAKE_CASE       :    Dict       =	intermediate_size
      __SCREAMING_SNAKE_CASE       :    List[str]       =	hidden_act
      __SCREAMING_SNAKE_CASE       :    List[str]       =	hidden_dropout_prob
      __SCREAMING_SNAKE_CASE       :    str       =	attention_probs_dropout_prob
      __SCREAMING_SNAKE_CASE       :    Tuple       =	initializer_range
      __SCREAMING_SNAKE_CASE       :    List[str]       =	layer_norm_eps
      __SCREAMING_SNAKE_CASE       :    Tuple       =	image_size
      __SCREAMING_SNAKE_CASE       :    Tuple       =	patch_size
      __SCREAMING_SNAKE_CASE       :    Dict       =	num_channels
      __SCREAMING_SNAKE_CASE       :    Any       =	qkv_bias
      __SCREAMING_SNAKE_CASE       :    str       =	num_detection_tokens
      __SCREAMING_SNAKE_CASE       :    str       =	use_mid_position_embeddings
      __SCREAMING_SNAKE_CASE       :    List[str]       =	auxiliary_loss
      # Hungarian matcher
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	class_cost
      __SCREAMING_SNAKE_CASE       :    int       =	bbox_cost
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	giou_cost
      # Loss coefficients
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	bbox_loss_coefficient
      __SCREAMING_SNAKE_CASE       :    str       =	giou_loss_coefficient
      __SCREAMING_SNAKE_CASE       :    Dict       =	eos_coefficient






class       _SCREAMING_SNAKE_CASE	(_UpperCamelCase ):
     lowerCAmelCase					=			version.parse("""1.11""" )





     @property
     def 	__snake_case    (       self :							str				)->Mapping[str, Mapping[int, str]]:
      return OrderedDict(
          [
              ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
          ]				)





     @property
     def 	__snake_case    (       self :							Optional[Any]				)->float:
      return 1E-4






     @property
     def 	__snake_case    (       self :							Dict				)->int:
      return 1_2











import warnings

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


_lowerCamelCase						    =  logging.get_logger(__name__)

class       _SCREAMING_SNAKE_CASE	(UpperCamelCase ):





     def __init__(       self :							int     ,  *UpperCamelCase :							Optional[int]     ,  **UpperCamelCase :							Optional[int]				)->None:
      warnings.warn(
          "The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
          " Please use LayoutLMv2ImageProcessor instead."     ,  UpperCamelCase     ,  )
      super().__init__(*UpperCamelCase     ,  **UpperCamelCase				)






