




import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig


lowerCamelCase    :		List[Any]			   =       {
    "facebook/maskformer-swin-base-ade": (
        "https://huggingface.co/facebook/maskformer-swin-base-ade/blob/main/config.json"
    )
    # See all MaskFormer models at https://huggingface.co/models?filter=maskformer
}

lowerCamelCase    :		Any			   =       logging.get_logger(__name__)







class   A(						__lowercase       ):



 '''simple docstring'''


 UpperCamelCase						       =						'''maskformer'''
 UpperCamelCase						       =						{'''hidden_size''': '''mask_feature_size'''}
 UpperCamelCase						       =						['''resnet''', '''swin''']
 UpperCamelCase						       =						['''detr''']

 def __init__(    self :  Optional[int]						,							A_ :  int = 256						,							A_ :  int = 256						,							A_ :  float = 0.1						,							A_ :  bool = False						,							A_ :  Optional[Dict] = None						,							A_ :  Optional[Dict] = None						,							A_ :  float = 0.02						,							A_ :  float = 1.0						,							A_ :  float = 1.0						,							A_ :  float = 1.0						,							A_ :  float = 20.0						,							A_ :  Optional[bool] = None						,							**A_ :  Optional[Any]						,							)       ->     int:

       """simple docstring"""






       if backbone_config is None:
             # fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
             lowerCamelCase_							=   SwinConfig(
                 image_size=384						,							in_channels=3						,							patch_size=4						,							embed_dim=128						,							depths=[2, 2, 18, 2]						,							num_heads=[4, 8, 16, 32]						,							window_size=12						,							drop_path_rate=0.3						,							out_features=['stage1', 'stage2', 'stage3', 'stage4']						,							)

       if isinstance(UpperCAmelCase__						,							UpperCAmelCase__  ):
             lowerCamelCase_							=   backbone_config.pop('model_type'  )
             lowerCamelCase_							=   CONFIG_MAPPING[backbone_model_type]
             lowerCamelCase_							=   config_class.from_dict(UpperCAmelCase__  )

       # verify that the backbone is supported
       if backbone_config.model_type not in self.backbones_supported:
             logger.warning_once(
                 f"""Backbone {backbone_config.model_type} is not a supported model and may not be compatible with MaskFormer. """
                 f"""Supported model types: {",".join(self.backbones_supported  )}"""  )

       if decoder_config is None:
             # fall back to https://huggingface.co/facebook/detr-resnet-50
             lowerCamelCase_							=   DetrConfig()
       else:
             # verify that the decoder is supported
             lowerCamelCase_							=   (
                 decoder_config.pop('model_type'  ) if isinstance(UpperCAmelCase__						,							UpperCAmelCase__  ) else decoder_config.model_type
             )
             if decoder_type not in self.decoders_supported:
                   raise ValueError(
                       f"""Transformer Decoder {decoder_type} not supported, please use one of"""
                       f""" {",".join(self.decoders_supported  )}"""  )
             if isinstance(UpperCAmelCase__						,							UpperCAmelCase__  ):
                   lowerCamelCase_							=   CONFIG_MAPPING[decoder_type]
                   lowerCamelCase_							=   config_class.from_dict(UpperCAmelCase__  )

       lowerCamelCase_							=   backbone_config
       lowerCamelCase_							=   decoder_config
       # main feature dimension for the model
       lowerCamelCase_							=   fpn_feature_size
       lowerCamelCase_							=   mask_feature_size
       # initializer
       lowerCamelCase_							=   init_std
       lowerCamelCase_							=   init_xavier_std
       # Hungarian matcher && loss
       lowerCamelCase_							=   cross_entropy_weight
       lowerCamelCase_							=   dice_weight
       lowerCamelCase_							=   mask_weight
       lowerCamelCase_							=   use_auxiliary_loss
       lowerCamelCase_							=   no_object_weight
       lowerCamelCase_							=   output_auxiliary_logits

       lowerCamelCase_							=   self.decoder_config.encoder_attention_heads
       lowerCamelCase_							=   self.decoder_config.num_hidden_layers
       super().__init__(**UpperCAmelCase__  )

 @classmethod
 def     a__			(    cls :  Tuple						,							A_ :  PretrainedConfig						,							A_ :  PretrainedConfig						,							**A_ :  List[str]  )       ->     Union[str, Any]:

       """simple docstring"""






       return cls(
           backbone_config=UpperCAmelCase__						,							decoder_config=UpperCAmelCase__						,							**UpperCAmelCase__						,							)





 def     a__			(    self :  Optional[int]  )       ->     Dict[str, any]:

       """simple docstring"""






       lowerCamelCase_							=   copy.deepcopy(self.__dict__  )
       lowerCamelCase_							=   self.backbone_config.to_dict()
       lowerCamelCase_							=   self.decoder_config.to_dict()
       lowerCamelCase_							=   self.__class__.model_type
       return output









import math

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	int					):


      '''simple docstring'''



      lowerCamelCase_							=   0
      lowerCamelCase_							=   0
      while num > 0:
            lowerCamelCase_							=   num % 8
            lowerCamelCase_							=   octal + (remainder * math.floor(math.pow(10     ,							lowercase					)					))
            counter += 1
            lowerCamelCase_							=   math.floor(num / 8					)  # basically /= 8 without remainder if any
            # This formatting removes trailing '.0' from `octal`.
      return f"""0o{int(lowercase					)}"""

def       _SCREAMING_SNAKE_CASE      (							):


      '''simple docstring'''



      print('\n2 in octal is:'					)
      print(decimal_to_octal(2					)					)  # = 2
      print('\n8 in octal is:'					)
      print(decimal_to_octal(8					)					)  # = 10
      print('\n65 in octal is:'					)
      print(decimal_to_octal(65					)					)  # = 101
      print('\n216 in octal is:'					)
      print(decimal_to_octal(2_16					)					)  # = 330
      print('\n512 in octal is:'					)
      print(decimal_to_octal(5_12					)					)  # = 1000
      print('\n'					)


if __name__ == "__main__":
 main()



