



"""simple docstring"""





import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


SCREAMING_SNAKE_CASE				:     List[str]          =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE				:     int          =	{
    '''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       __lowerCamelCase	(   __lowercase    ):
   __UpperCamelCase									=   'oneformer'
   __UpperCamelCase									=   {'hidden_size': 'hidden_dim'}







   def __init__(self       ,	lowerCamelCase = None       ,	lowerCamelCase = 255       ,	lowerCamelCase = 150       ,	lowerCamelCase = 0.1       ,	lowerCamelCase = 2.0       ,	lowerCamelCase = 5.0       ,	lowerCamelCase = 5.0       ,	lowerCamelCase = 0.5       ,	lowerCamelCase = 0.07       ,	lowerCamelCase = 12_544       ,	lowerCamelCase = 3.0       ,	lowerCamelCase = 0.75       ,	lowerCamelCase = 0.02       ,	lowerCamelCase = 1.0       ,	lowerCamelCase = 1e-05       ,	lowerCamelCase = False       ,	lowerCamelCase = True       ,	lowerCamelCase = True       ,	lowerCamelCase = [4, 8, 16, 32]       ,	lowerCamelCase = 77       ,	lowerCamelCase = 256       ,	lowerCamelCase = 77       ,	lowerCamelCase = 6       ,	lowerCamelCase = 49_408       ,	lowerCamelCase = 2       ,	lowerCamelCase = 16       ,	lowerCamelCase = 256       ,	lowerCamelCase = 256       ,	lowerCamelCase = 256       ,	lowerCamelCase = 1_024       ,	lowerCamelCase = "GN"       ,	lowerCamelCase = 6       ,	lowerCamelCase = 10       ,	lowerCamelCase = True       ,	lowerCamelCase = 8       ,	lowerCamelCase = 0.1       ,	lowerCamelCase = 2_048       ,	lowerCamelCase = False       ,	lowerCamelCase = False       ,	lowerCamelCase = 2       ,	lowerCamelCase = 4       ,	**lowerCamelCase       ,	):




      '''simple docstring'''




      if backbone_config is None:
         logger.info("""`backbone_config` is unset. Initializing the config with the default `Swin` backbone."""				)
         _lowerCAmelCase					     =		CONFIG_MAPPING["""swin"""](
             image_size=224       ,	in_channels=3       ,	patch_size=4       ,	embed_dim=96       ,	depths=[2, 2, 6, 2]       ,	num_heads=[3, 6, 12, 24]       ,	window_size=7       ,	drop_path_rate=0.3       ,	use_absolute_embeddings=lowerCamelCase       ,	out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]       ,	)
      elif isinstance(lowerCamelCase       ,	lowerCamelCase				):
         _lowerCAmelCase					     =		backbone_config.get("""model_type"""				)
         _lowerCAmelCase					     =		CONFIG_MAPPING[backbone_model_type]
         _lowerCAmelCase					     =		config_class.from_dict(lowerCamelCase				)

      _lowerCAmelCase					     =		backbone_config

      _lowerCAmelCase					     =		ignore_value
      _lowerCAmelCase					     =		num_queries
      _lowerCAmelCase					     =		no_object_weight
      _lowerCAmelCase					     =		class_weight
      _lowerCAmelCase					     =		mask_weight
      _lowerCAmelCase					     =		dice_weight
      _lowerCAmelCase					     =		contrastive_weight
      _lowerCAmelCase					     =		contrastive_temperature
      _lowerCAmelCase					     =		train_num_points
      _lowerCAmelCase					     =		oversample_ratio
      _lowerCAmelCase					     =		importance_sample_ratio
      _lowerCAmelCase					     =		init_std
      _lowerCAmelCase					     =		init_xavier_std
      _lowerCAmelCase					     =		layer_norm_eps
      _lowerCAmelCase					     =		is_training
      _lowerCAmelCase					     =		use_auxiliary_loss
      _lowerCAmelCase					     =		output_auxiliary_logits
      _lowerCAmelCase					     =		strides
      _lowerCAmelCase					     =		task_seq_len
      _lowerCAmelCase					     =		text_encoder_width
      _lowerCAmelCase					     =		text_encoder_context_length
      _lowerCAmelCase					     =		text_encoder_num_layers
      _lowerCAmelCase					     =		text_encoder_vocab_size
      _lowerCAmelCase					     =		text_encoder_proj_layers
      _lowerCAmelCase					     =		text_encoder_n_ctx
      _lowerCAmelCase					     =		conv_dim
      _lowerCAmelCase					     =		mask_dim
      _lowerCAmelCase					     =		hidden_dim
      _lowerCAmelCase					     =		encoder_feedforward_dim
      _lowerCAmelCase					     =		norm
      _lowerCAmelCase					     =		encoder_layers
      _lowerCAmelCase					     =		decoder_layers
      _lowerCAmelCase					     =		use_task_norm
      _lowerCAmelCase					     =		num_attention_heads
      _lowerCAmelCase					     =		dropout
      _lowerCAmelCase					     =		dim_feedforward
      _lowerCAmelCase					     =		pre_norm
      _lowerCAmelCase					     =		enforce_input_proj
      _lowerCAmelCase					     =		query_dec_layers
      _lowerCAmelCase					     =		common_stride
      _lowerCAmelCase					     =		decoder_layers

      super().__init__(**lowerCamelCase				)







   def 							A__						(self				):




      '''simple docstring'''




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




"""simple docstring"""





def 	__UpperCAmelCase					(       snake_case_  :  float   )							->	int:






   """simple docstring"""


   return int(snake_case_   ) if x - int(snake_case_   ) <= 0 else int(snake_case_   ) + 1


if __name__ == "__main__":
  import doctest

  doctest.testmod()