

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


snake_case_			  = {
    '''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
}

snake_case_			  = logging.get_logger(__name__)


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):
    __lowerCamelCase						:       Any														=     """maskformer"""
    __lowerCamelCase						:       Tuple														=     {"""hidden_size""": """mask_feature_size"""}
    __lowerCamelCase						:       Union[str, Any]														=     ["""resnet""", """swin"""]
    __lowerCamelCase						:       List[Any]														=     ["""detr"""]





    def __init__(      self						,   a = 256						,   a = 256						,   a = 0.1						,   a = False						,   a = None						,   a = None						,   a = 0.02						,   a = 1.0						,   a = 1.0						,   a = 1.0						,   a = 20.0						,   a = None						,   **a						,   ):
         if backbone_config is None:
              # fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
              lowercase__    :   str      =       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(a						,   a):
              lowercase__    :   List[str]      =       backbone_config.pop('model_type')
              lowercase__    :   Optional[Any]      =       CONFIG_MAPPING[backbone_model_type]
              lowercase__    :   Optional[Any]      =       config_class.from_dict(a)

         # 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
              lowercase__    :   List[Any]      =       DetrConfig()
         else:
              # verify that the decoder is supported
              lowercase__    :   Optional[int]      =       (
                  decoder_config.pop('model_type') if isinstance(a						,   a) 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(a						,   a):
                   lowercase__    :   Optional[int]      =       CONFIG_MAPPING[decoder_type]
                   lowercase__    :   Optional[int]      =       config_class.from_dict(a)

         lowercase__    :   List[Any]      =       backbone_config
         lowercase__    :   str      =       decoder_config
         # main feature dimension for the model
         lowercase__    :   str      =       fpn_feature_size
         lowercase__    :   Optional[Any]      =       mask_feature_size
         # initializer
         lowercase__    :   List[str]      =       init_std
         lowercase__    :   str      =       init_xavier_std
         # Hungarian matcher && loss
         lowercase__    :   Any      =       cross_entropy_weight
         lowercase__    :   str      =       dice_weight
         lowercase__    :   Tuple      =       mask_weight
         lowercase__    :   List[str]      =       use_auxiliary_loss
         lowercase__    :   Optional[int]      =       no_object_weight
         lowercase__    :   Optional[int]      =       output_auxiliary_logits

         lowercase__    :   Optional[int]      =       self.decoder_config.encoder_attention_heads
         lowercase__    :   Union[str, Any]      =       self.decoder_config.num_hidden_layers
         super().__init__(**a)





    @classmethod
    def       snake_case_				(      cls						,   a						,   a						,   **a):
         return cls(
             backbone_config=a						,   decoder_config=a						,   **a						,   )





    def       snake_case_				(      self):
         lowercase__    :   Optional[int]      =       copy.deepcopy(self.__dict__)
         lowercase__    :   List[str]      =       self.backbone_config.to_dict()
         lowercase__    :   List[str]      =       self.decoder_config.to_dict()
         lowercase__    :   List[Any]      =       self.__class__.model_type
         return output




def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str	,     SCREAMING_SNAKE_CASE_		:    str			):



     '''simple docstring'''





     if len(SCREAMING_SNAKE_CASE_			) != len(SCREAMING_SNAKE_CASE_			):
          raise ValueError('String lengths must match!'			)

     lowercase__    :   Union[str, Any]      =       0

     for chara, chara in zip(SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_			):
          if chara != chara:
               count += 1

     return count


if __name__ == "__main__":
       import doctest

       doctest.testmod()

