


'''simple docstring'''





import copy
from typing import Dict, Optional

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


__lowerCamelCase       				=	logging.get_logger(__name__)

__lowerCamelCase       				=	{
    '''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 ( _snake_case	):
 UpperCAmelCase				=				"oneformer"
 UpperCAmelCase				=				{"hidden_size": "hidden_dim"}


 def __init__(			self       :  Optional[Any] ,					__lowerCamelCase       :  Optional[Dict] = None ,					__lowerCamelCase       :  int = 2_5_5 ,					__lowerCamelCase       :  int = 1_5_0 ,					__lowerCamelCase       :  int = 0.1 ,					__lowerCamelCase       :  float = 2.0 ,					__lowerCamelCase       :  float = 5.0 ,					__lowerCamelCase       :  float = 5.0 ,					__lowerCamelCase       :  float = 0.5 ,					__lowerCamelCase       :  float = 0.07 ,					__lowerCamelCase       :  int = 1_2_5_4_4 ,					__lowerCamelCase       :  float = 3.0 ,					__lowerCamelCase       :  float = 0.75 ,					__lowerCamelCase       :  float = 0.02 ,					__lowerCamelCase       :  float = 1.0 ,					__lowerCamelCase       :  float = 1e-05 ,					__lowerCamelCase       :  bool = False ,					__lowerCamelCase       :  bool = True ,					__lowerCamelCase       :  bool = True ,					__lowerCamelCase       :  Optional[list] = [4, 8, 1_6, 3_2] ,					__lowerCamelCase       :  int = 7_7 ,					__lowerCamelCase       :  int = 2_5_6 ,					__lowerCamelCase       :  int = 7_7 ,					__lowerCamelCase       :  int = 6 ,					__lowerCamelCase       :  int = 4_9_4_0_8 ,					__lowerCamelCase       :  int = 2 ,					__lowerCamelCase       :  int = 1_6 ,					__lowerCamelCase       :  int = 2_5_6 ,					__lowerCamelCase       :  int = 2_5_6 ,					__lowerCamelCase       :  int = 2_5_6 ,					__lowerCamelCase       :  int = 1_0_2_4 ,					__lowerCamelCase       :  str = "GN" ,					__lowerCamelCase       :  int = 6 ,					__lowerCamelCase       :  int = 1_0 ,					__lowerCamelCase       :  bool = True ,					__lowerCamelCase       :  int = 8 ,					__lowerCamelCase       :  float = 0.1 ,					__lowerCamelCase       :  int = 2_0_4_8 ,					__lowerCamelCase       :  bool = False ,					__lowerCamelCase       :  bool = False ,					__lowerCamelCase       :  int = 2 ,					__lowerCamelCase       :  int = 4 ,					**__lowerCamelCase       :  Union[str, Any] ,					):
    if backbone_config is None:
       logger.info('''`backbone_config` is unset. Initializing the config with the default `Swin` backbone.'''   )
       UpperCAmelCase__  :Tuple            =			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=__lowerCamelCase ,					out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4'''] ,					)
    elif isinstance(__lowerCamelCase ,					__lowerCamelCase   ):
       UpperCAmelCase__  :List[Any]            =			backbone_config.get('''model_type'''   )
       UpperCAmelCase__  :Union[str, Any]            =			CONFIG_MAPPING[backbone_model_type]
       UpperCAmelCase__  :List[Any]            =			config_class.from_dict(__lowerCamelCase   )

    UpperCAmelCase__  :Optional[Any]            =			backbone_config

    UpperCAmelCase__  :Union[str, Any]            =			ignore_value
    UpperCAmelCase__  :Tuple            =			num_queries
    UpperCAmelCase__  :int            =			no_object_weight
    UpperCAmelCase__  :Dict            =			class_weight
    UpperCAmelCase__  :Optional[int]            =			mask_weight
    UpperCAmelCase__  :Dict            =			dice_weight
    UpperCAmelCase__  :Union[str, Any]            =			contrastive_weight
    UpperCAmelCase__  :List[Any]            =			contrastive_temperature
    UpperCAmelCase__  :str            =			train_num_points
    UpperCAmelCase__  :Tuple            =			oversample_ratio
    UpperCAmelCase__  :Optional[int]            =			importance_sample_ratio
    UpperCAmelCase__  :List[Any]            =			init_std
    UpperCAmelCase__  :Union[str, Any]            =			init_xavier_std
    UpperCAmelCase__  :Tuple            =			layer_norm_eps
    UpperCAmelCase__  :Optional[int]            =			is_training
    UpperCAmelCase__  :Union[str, Any]            =			use_auxiliary_loss
    UpperCAmelCase__  :str            =			output_auxiliary_logits
    UpperCAmelCase__  :Tuple            =			strides
    UpperCAmelCase__  :str            =			task_seq_len
    UpperCAmelCase__  :Optional[Any]            =			text_encoder_width
    UpperCAmelCase__  :Any            =			text_encoder_context_length
    UpperCAmelCase__  :Optional[Any]            =			text_encoder_num_layers
    UpperCAmelCase__  :str            =			text_encoder_vocab_size
    UpperCAmelCase__  :Optional[int]            =			text_encoder_proj_layers
    UpperCAmelCase__  :str            =			text_encoder_n_ctx
    UpperCAmelCase__  :List[Any]            =			conv_dim
    UpperCAmelCase__  :Dict            =			mask_dim
    UpperCAmelCase__  :Union[str, Any]            =			hidden_dim
    UpperCAmelCase__  :List[Any]            =			encoder_feedforward_dim
    UpperCAmelCase__  :Any            =			norm
    UpperCAmelCase__  :List[str]            =			encoder_layers
    UpperCAmelCase__  :List[Any]            =			decoder_layers
    UpperCAmelCase__  :Union[str, Any]            =			use_task_norm
    UpperCAmelCase__  :Optional[Any]            =			num_attention_heads
    UpperCAmelCase__  :int            =			dropout
    UpperCAmelCase__  :Any            =			dim_feedforward
    UpperCAmelCase__  :Any            =			pre_norm
    UpperCAmelCase__  :Dict            =			enforce_input_proj
    UpperCAmelCase__  :Optional[int]            =			query_dec_layers
    UpperCAmelCase__  :int            =			common_stride
    UpperCAmelCase__  :List[str]            =			decoder_layers

    super().__init__(**__lowerCamelCase   )





 def 					__SCREAMING_SNAKE_CASE				(			self       :  Optional[Any]   ):
    UpperCAmelCase__  :List[Any]            =			copy.deepcopy(self.__dict__   )
    UpperCAmelCase__  :str            =			self.backbone_config.to_dict()
    UpperCAmelCase__  :Tuple            =			self.__class__.model_type
    return output







'''simple docstring'''





from scipy.constants import g


def 					a__    (				UpperCamelCase_	:			float,      UpperCamelCase_	:			float	):
   if mass < 0:
      # handling of negative values of mass
      raise ValueError('''The mass of a body cannot be negative'''	)
   if height < 0:
      # handling of negative values of height
      raise ValueError('''The height above the ground cannot be negative'''	)
   return mass * g * height


if __name__ == "__main__":
    from doctest import testmod

    testmod(name='''potential_energy''')



