code: 
  
  
  
  '''simple docstring'''
  
  
  
  import copy
  from typing import Dict, Optional
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  from ..auto import CONFIG_MAPPING
  
  
  a__						:			Any										=			logging.get_logger(__name__)
  
  a__						:			Union[str, Any]										=			{
      'shi-labs/oneformer_ade20k_swin_tiny': (
          'https://huggingface.co/shi-labs/oneformer_ade20k_swin_tiny/blob/main/config.json'
      ),
      # See all OneFormer models at https://huggingface.co/models?filter=oneformer
  }
  class        UpperCAmelCase__  (    UpperCAmelCase_):
   __SCREAMING_SNAKE_CASE					      =				'''oneformer'''
   __SCREAMING_SNAKE_CASE					      =				{'''hidden_size''': '''hidden_dim'''}
  
  
  
   def __init__(  self		,	lowercase = None		,	lowercase = 2_5_5		,	lowercase = 1_5_0		,	lowercase = 0.1		,	lowercase = 2.0		,	lowercase = 5.0		,	lowercase = 5.0		,	lowercase = 0.5		,	lowercase = 0.07		,	lowercase = 1_2_5_4_4		,	lowercase = 3.0		,	lowercase = 0.75		,	lowercase = 0.02		,	lowercase = 1.0		,	lowercase = 1E-05		,	lowercase = False		,	lowercase = True		,	lowercase = True		,	lowercase = [4, 8, 1_6, 3_2]		,	lowercase = 7_7		,	lowercase = 2_5_6		,	lowercase = 7_7		,	lowercase = 6		,	lowercase = 4_9_4_0_8		,	lowercase = 2		,	lowercase = 1_6		,	lowercase = 2_5_6		,	lowercase = 2_5_6		,	lowercase = 2_5_6		,	lowercase = 1_0_2_4		,	lowercase = "GN"		,	lowercase = 6		,	lowercase = 1_0		,	lowercase = True		,	lowercase = 8		,	lowercase = 0.1		,	lowercase = 2_0_4_8		,	lowercase = False		,	lowercase = False		,	lowercase = 2		,	lowercase = 4		,	**lowercase		,	)  ->							Dict:
    if backbone_config is None:
     logger.info("""`backbone_config` is unset. Initializing the config with the default `Swin` backbone."""			)
     __UpperCamelCase				      =  CONFIG_MAPPING["""swin"""](
         image_size=2_2_4		,	in_channels=3		,	patch_size=4		,	embed_dim=9_6		,	depths=[2, 2, 6, 2]		,	num_heads=[3, 6, 1_2, 2_4]		,	window_size=7		,	drop_path_rate=0.3		,	use_absolute_embeddings=lowercase		,	out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]		,	)
    elif isinstance(lowercase		,	lowercase			):
     __UpperCamelCase				      =  backbone_config.get("""model_type"""			)
     __UpperCamelCase				      =  CONFIG_MAPPING[backbone_model_type]
     __UpperCamelCase				      =  config_class.from_dict(lowercase			)
  
    __UpperCamelCase				      =  backbone_config
  
    __UpperCamelCase				      =  ignore_value
    __UpperCamelCase				      =  num_queries
    __UpperCamelCase				      =  no_object_weight
    __UpperCamelCase				      =  class_weight
    __UpperCamelCase				      =  mask_weight
    __UpperCamelCase				      =  dice_weight
    __UpperCamelCase				      =  contrastive_weight
    __UpperCamelCase				      =  contrastive_temperature
    __UpperCamelCase				      =  train_num_points
    __UpperCamelCase				      =  oversample_ratio
    __UpperCamelCase				      =  importance_sample_ratio
    __UpperCamelCase				      =  init_std
    __UpperCamelCase				      =  init_xavier_std
    __UpperCamelCase				      =  layer_norm_eps
    __UpperCamelCase				      =  is_training
    __UpperCamelCase				      =  use_auxiliary_loss
    __UpperCamelCase				      =  output_auxiliary_logits
    __UpperCamelCase				      =  strides
    __UpperCamelCase				      =  task_seq_len
    __UpperCamelCase				      =  text_encoder_width
    __UpperCamelCase				      =  text_encoder_context_length
    __UpperCamelCase				      =  text_encoder_num_layers
    __UpperCamelCase				      =  text_encoder_vocab_size
    __UpperCamelCase				      =  text_encoder_proj_layers
    __UpperCamelCase				      =  text_encoder_n_ctx
    __UpperCamelCase				      =  conv_dim
    __UpperCamelCase				      =  mask_dim
    __UpperCamelCase				      =  hidden_dim
    __UpperCamelCase				      =  encoder_feedforward_dim
    __UpperCamelCase				      =  norm
    __UpperCamelCase				      =  encoder_layers
    __UpperCamelCase				      =  decoder_layers
    __UpperCamelCase				      =  use_task_norm
    __UpperCamelCase				      =  num_attention_heads
    __UpperCamelCase				      =  dropout
    __UpperCamelCase				      =  dim_feedforward
    __UpperCamelCase				      =  pre_norm
    __UpperCamelCase				      =  enforce_input_proj
    __UpperCamelCase				      =  query_dec_layers
    __UpperCamelCase				      =  common_stride
    __UpperCamelCase				      =  decoder_layers
  
    super().__init__(**lowercase			)
  
  
  
  
   def    __lowerCamelCase				(  self			)  ->							Dict[str, any]:
    __UpperCamelCase				      =  copy.deepcopy(self.__dict__			)
    __UpperCamelCase				      =  self.backbone_config.to_dict()
    __UpperCamelCase				      =  self.__class__.model_type
    return output
  
  
  
  
  
  
style_context: 
  
  
  
  '''simple docstring'''
  
  
  
  def _lowercase   (  __A							,__A       ):
  
  
  
   '''simple docstring'''
  
  
  
   __UpperCamelCase				      =  1
   while b > 0:
    if b & 1:
     res *= a
  
    a *= a
    b >>= 1
  
   return res
  
  
  
  
  
  
  
  def _lowercase   (  __A							,__A							,__A       ):
  
  
  
   '''simple docstring'''
  
  
  
   __UpperCamelCase				      =  1
   while b > 0:
    if b & 1:
     __UpperCamelCase				      =  ((res % c) * (a % c)) % c
  
    a *= a
    b >>= 1
  
   return res
  
  
  
  
  
  