






"""simple docstring"""

import copy
from typing import Dict, Optional

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


lowercase           =							logging.get_logger(__name__)

lowercase           =							{
    '''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     A_				(   snake_case_	):
				UpperCAmelCase__										=					'''oneformer'''
				UpperCAmelCase__										=					{'''hidden_size''': '''hidden_dim'''}







				def __init__(				self				:    List[str]    ,     __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				:    List[Any]    ,     )					->       Union[str, Any]:
										if backbone_config is None:
																logger.info("`backbone_config` is unset. Initializing the config with the default `Swin` backbone."						)
																__magic_name__      =  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						):
																__magic_name__      =  backbone_config.get("model_type"						)
																__magic_name__      =  CONFIG_MAPPING[backbone_model_type]
																__magic_name__      =  config_class.from_dict(__lowerCamelCase						)

										__magic_name__      =  backbone_config

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

										super().__init__(**__lowerCamelCase						)







				def      _snake_case       (				self				:    List[str]						)					->       Dict[str, any]:
										__magic_name__      =  copy.deepcopy(self.__dict__						)
										__magic_name__      =  self.backbone_config.to_dict()
										__magic_name__      =  self.__class__.model_type
										return output











"""simple docstring"""

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase           =							logging.get_logger(__name__)

lowercase           =							{
    '''facebook/sam-vit-huge''': '''https://huggingface.co/facebook/sam-vit-huge/resolve/main/config.json''',
    '''facebook/sam-vit-large''': '''https://huggingface.co/facebook/sam-vit-large/resolve/main/config.json''',
    '''facebook/sam-vit-base''': '''https://huggingface.co/facebook/sam-vit-base/resolve/main/config.json''',
}

class     A_				(   snake_case_	):







				def __init__(				self				:    List[Any]    ,     __lowerCamelCase				:    str=2_5_6    ,     __lowerCamelCase				:    str=1_0_2_4    ,     __lowerCamelCase				:    Optional[Any]=1_6    ,     __lowerCamelCase				:    Union[str, Any]=1_6    ,     __lowerCamelCase				:    str=4    ,     __lowerCamelCase				:    Union[str, Any]="gelu"    ,     __lowerCamelCase				:    Optional[int]=1e-6    ,     **__lowerCamelCase				:    str    ,     )					->       List[Any]:
										super().__init__(**__lowerCamelCase						)
										__magic_name__      =  hidden_size
										__magic_name__      =  image_size
										__magic_name__      =  patch_size
										__magic_name__      =  image_size // patch_size
										__magic_name__      =  mask_input_channels
										__magic_name__      =  num_point_embeddings
										__magic_name__      =  hidden_act
										__magic_name__      =  layer_norm_eps





class     A_				(   snake_case_	):







				def __init__(				self				:    List[str]    ,     __lowerCamelCase				:    Optional[Any]=2_5_6    ,     __lowerCamelCase				:    int="relu"    ,     __lowerCamelCase				:    List[str]=2_0_4_8    ,     __lowerCamelCase				:    Optional[Any]=2    ,     __lowerCamelCase				:    Optional[Any]=8    ,     __lowerCamelCase				:    Optional[Any]=2    ,     __lowerCamelCase				:    Dict=3    ,     __lowerCamelCase				:    Optional[int]=3    ,     __lowerCamelCase				:    Tuple=2_5_6    ,     __lowerCamelCase				:    List[str]=1e-6    ,     **__lowerCamelCase				:    Any    ,     )					->       str:
										super().__init__(**__lowerCamelCase						)
										__magic_name__      =  hidden_size
										__magic_name__      =  hidden_act
										__magic_name__      =  mlp_dim
										__magic_name__      =  num_hidden_layers
										__magic_name__      =  num_attention_heads
										__magic_name__      =  attention_downsample_rate
										__magic_name__      =  num_multimask_outputs
										__magic_name__      =  iou_head_depth
										__magic_name__      =  iou_head_hidden_dim
										__magic_name__      =  layer_norm_eps





class     A_				(   snake_case_	):







				def __init__(				self				:    Union[str, Any]    ,     __lowerCamelCase				:    str=7_6_8    ,     __lowerCamelCase				:    Optional[int]=2_5_6    ,     __lowerCamelCase				:    Tuple=1_2    ,     __lowerCamelCase				:    int=1_2    ,     __lowerCamelCase				:    int=3    ,     __lowerCamelCase				:    int=1_0_2_4    ,     __lowerCamelCase				:    Any=1_6    ,     __lowerCamelCase				:    Tuple="gelu"    ,     __lowerCamelCase				:    Dict=1e-06    ,     __lowerCamelCase				:    List[Any]=0.0    ,     __lowerCamelCase				:    Optional[Any]=1e-10    ,     __lowerCamelCase				:    str=True    ,     __lowerCamelCase				:    List[str]=4.0    ,     __lowerCamelCase				:    Union[str, Any]=True    ,     __lowerCamelCase				:    str=True    ,     __lowerCamelCase				:    Optional[Any]=1_4    ,     __lowerCamelCase				:    str=[2, 5, 8, 1_1]    ,     __lowerCamelCase				:    List[Any]=1_2_8    ,     __lowerCamelCase				:    Dict=None    ,     **__lowerCamelCase				:    List[str]    ,     )					->       Optional[int]:
										super().__init__(**__lowerCamelCase						)

										__magic_name__      =  hidden_size
										__magic_name__      =  output_channels
										__magic_name__      =  num_hidden_layers
										__magic_name__      =  num_attention_heads
										__magic_name__      =  num_channels
										__magic_name__      =  image_size
										__magic_name__      =  patch_size
										__magic_name__      =  hidden_act
										__magic_name__      =  layer_norm_eps
										__magic_name__      =  attention_dropout
										__magic_name__      =  initializer_range
										__magic_name__      =  qkv_bias
										__magic_name__      =  mlp_ratio
										__magic_name__      =  use_abs_pos
										__magic_name__      =  use_rel_pos
										__magic_name__      =  window_size
										__magic_name__      =  global_attn_indexes
										__magic_name__      =  num_pos_feats
										__magic_name__      =  int(hidden_size * mlp_ratio						) if mlp_dim is None else mlp_dim





class     A_				(   snake_case_	):
				UpperCAmelCase__										=					'''sam'''
				UpperCAmelCase__										=					True







				def __init__(				self				:    Optional[Any]    ,     __lowerCamelCase				:    Dict=None    ,     __lowerCamelCase				:    Dict=None    ,     __lowerCamelCase				:    Optional[Any]=None    ,     __lowerCamelCase				:    int=0.02    ,     **__lowerCamelCase				:    List[Any]    ,     )					->       List[str]:
										super().__init__(**__lowerCamelCase						)
										__magic_name__      =  vision_config if vision_config is not None else {}
										__magic_name__      =  prompt_encoder_config if prompt_encoder_config is not None else {}
										__magic_name__      =  mask_decoder_config if mask_decoder_config is not None else {}

										if isinstance(__lowerCamelCase    ,     __lowerCamelCase						):
																__magic_name__      =  vision_config.to_dict()
										if isinstance(__lowerCamelCase    ,     __lowerCamelCase						):
																__magic_name__      =  prompt_encoder_config.to_dict()
										if isinstance(__lowerCamelCase    ,     __lowerCamelCase						):
																__magic_name__      =  mask_decoder_config.to_dict()

										__magic_name__      =  SamVisionConfig(**__lowerCamelCase						)
										__magic_name__      =  SamPromptEncoderConfig(**__lowerCamelCase						)
										__magic_name__      =  SamMaskDecoderConfig(**__lowerCamelCase						)
										__magic_name__      =  initializer_range







				def      _snake_case       (				self				:    Optional[int]						)					->       str:
										__magic_name__      =  copy.deepcopy(self.__dict__						)
										__magic_name__      =  self.vision_config.to_dict()
										__magic_name__      =  self.prompt_encoder_config.to_dict()
										__magic_name__      =  self.mask_decoder_config.to_dict()
										__magic_name__      =  self.__class__.model_type
										return output



