


'''simple docstring'''






import copy
from typing import Dict, List, Optional

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


__A   :    Optional[Any]											= {
    "facebook/mask2former-swin-small-coco-instance": (
        "https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json"
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

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






class   __snake_case			(  _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase  					=   'mask2former'
    lowercase  					=   ['swin']
    lowercase  					=   {'hidden_size': 'hidden_dim'}

    def __init__(  self       :    int       ,		lowerCamelCase       :    Optional[Dict] = None       ,		lowerCamelCase       :    int = 2_56       ,		lowerCamelCase       :    int = 2_56       ,		lowerCamelCase       :    int = 2_56       ,		lowerCamelCase       :    int = 10_24       ,		lowerCamelCase       :    str = "relu"       ,		lowerCamelCase       :    int = 6       ,		lowerCamelCase       :    int = 10       ,		lowerCamelCase       :    int = 8       ,		lowerCamelCase       :    float = 0.0       ,		lowerCamelCase       :    int = 20_48       ,		lowerCamelCase       :    bool = False       ,		lowerCamelCase       :    bool = False       ,		lowerCamelCase       :    int = 4       ,		lowerCamelCase       :    int = 2_55       ,		lowerCamelCase       :    int = 1_00       ,		lowerCamelCase       :    float = 0.1       ,		lowerCamelCase       :    float = 2.0       ,		lowerCamelCase       :    float = 5.0       ,		lowerCamelCase       :    float = 5.0       ,		lowerCamelCase       :    int = 1_25_44       ,		lowerCamelCase       :    float = 3.0       ,		lowerCamelCase       :    float = 0.75       ,		lowerCamelCase       :    float = 0.02       ,		lowerCamelCase       :    float = 1.0       ,		lowerCamelCase       :    bool = True       ,		lowerCamelCase       :    List[int] = [4, 8, 16, 32]       ,		lowerCamelCase       :    bool = None       ,		**lowerCamelCase       :    str       ,		)  ->    Optional[int]:
      if backbone_config is None:
        logger.info("""`backbone_config` is `None`. Initializing the config with the default `Swin` backbone."""						)
        lowerCAmelCase_     : List[str]     =  CONFIG_MAPPING["""swin"""](
            image_size=2_24       ,		in_channels=3       ,		patch_size=4       ,		embed_dim=96       ,		depths=[2, 2, 18, 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"""]       ,		)

      if isinstance(lowerCamelCase       ,		lowerCamelCase						):
        lowerCAmelCase_     : List[Any]     =  backbone_config.pop("""model_type"""						)
        lowerCAmelCase_     : Dict     =  CONFIG_MAPPING[backbone_model_type]
        lowerCAmelCase_     : int     =  config_class.from_dict(lowerCamelCase						)

      # 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 Mask2Former. '
            F'Supported model types: {",".join(self.backbones_supported						)}'						)

      lowerCAmelCase_     : Optional[Any]     =  backbone_config
      lowerCAmelCase_     : Optional[Any]     =  feature_size
      lowerCAmelCase_     : Dict     =  mask_feature_size
      lowerCAmelCase_     : int     =  hidden_dim
      lowerCAmelCase_     : Optional[int]     =  encoder_feedforward_dim
      lowerCAmelCase_     : int     =  activation_function
      lowerCAmelCase_     : Union[str, Any]     =  encoder_layers
      lowerCAmelCase_     : Union[str, Any]     =  decoder_layers
      lowerCAmelCase_     : int     =  num_attention_heads
      lowerCAmelCase_     : Optional[Any]     =  dropout
      lowerCAmelCase_     : Dict     =  dim_feedforward
      lowerCAmelCase_     : Dict     =  pre_norm
      lowerCAmelCase_     : int     =  enforce_input_projection
      lowerCAmelCase_     : Optional[Any]     =  common_stride
      lowerCAmelCase_     : int     =  ignore_value
      lowerCAmelCase_     : str     =  num_queries
      lowerCAmelCase_     : List[Any]     =  no_object_weight
      lowerCAmelCase_     : Optional[int]     =  class_weight
      lowerCAmelCase_     : str     =  mask_weight
      lowerCAmelCase_     : List[str]     =  dice_weight
      lowerCAmelCase_     : List[Any]     =  train_num_points
      lowerCAmelCase_     : Union[str, Any]     =  oversample_ratio
      lowerCAmelCase_     : List[Any]     =  importance_sample_ratio
      lowerCAmelCase_     : Dict     =  init_std
      lowerCAmelCase_     : List[Any]     =  init_xavier_std
      lowerCAmelCase_     : int     =  use_auxiliary_loss
      lowerCAmelCase_     : str     =  feature_strides
      lowerCAmelCase_     : List[Any]     =  output_auxiliary_logits
      lowerCAmelCase_     : int     =  decoder_layers

      super().__init__(**lowerCamelCase						)

    @classmethod
    def __lowercase  (  cls       :    List[str]       ,		lowerCamelCase       :    PretrainedConfig       ,		**lowerCamelCase       :    Dict						)  ->    List[Any]:
      return cls(
          backbone_config=lowerCamelCase       ,		**lowerCamelCase       ,		)





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







'''simple docstring'''






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


__A   :    str											= logging.get_logger(__name__)

__A   :    int											= {
    "weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}






class   __snake_case			(  _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase  					=   'roc_bert'

    def __init__(  self       :    str       ,		lowerCamelCase       :    Optional[Any]=3_05_22       ,		lowerCamelCase       :    List[Any]=7_68       ,		lowerCamelCase       :    int=12       ,		lowerCamelCase       :    str=12       ,		lowerCamelCase       :    Any=30_72       ,		lowerCamelCase       :    List[Any]="gelu"       ,		lowerCamelCase       :    Optional[int]=0.1       ,		lowerCamelCase       :    List[str]=0.1       ,		lowerCamelCase       :    int=5_12       ,		lowerCamelCase       :    List[Any]=2       ,		lowerCamelCase       :    int=0.02       ,		lowerCamelCase       :    str=1E-12       ,		lowerCamelCase       :    int=True       ,		lowerCamelCase       :    Optional[Any]=0       ,		lowerCamelCase       :    List[Any]="absolute"       ,		lowerCamelCase       :    str=None       ,		lowerCamelCase       :    str=True       ,		lowerCamelCase       :    Tuple=True       ,		lowerCamelCase       :    str=7_68       ,		lowerCamelCase       :    str=9_10       ,		lowerCamelCase       :    Tuple=5_12       ,		lowerCamelCase       :    List[str]=2_48_58       ,		lowerCamelCase       :    Dict=True       ,		**lowerCamelCase       :    Tuple       ,		)  ->    Optional[int]:
      lowerCAmelCase_     : Optional[Any]     =  vocab_size
      lowerCAmelCase_     : Any     =  max_position_embeddings
      lowerCAmelCase_     : Any     =  hidden_size
      lowerCAmelCase_     : int     =  num_hidden_layers
      lowerCAmelCase_     : Tuple     =  num_attention_heads
      lowerCAmelCase_     : List[Any]     =  intermediate_size
      lowerCAmelCase_     : Tuple     =  hidden_act
      lowerCAmelCase_     : List[Any]     =  hidden_dropout_prob
      lowerCAmelCase_     : Dict     =  attention_probs_dropout_prob
      lowerCAmelCase_     : Any     =  initializer_range
      lowerCAmelCase_     : Any     =  type_vocab_size
      lowerCAmelCase_     : Optional[int]     =  layer_norm_eps
      lowerCAmelCase_     : Tuple     =  use_cache
      lowerCAmelCase_     : List[Any]     =  enable_pronunciation
      lowerCAmelCase_     : List[Any]     =  enable_shape
      lowerCAmelCase_     : List[str]     =  pronunciation_embed_dim
      lowerCAmelCase_     : List[str]     =  pronunciation_vocab_size
      lowerCAmelCase_     : Dict     =  shape_embed_dim
      lowerCAmelCase_     : Optional[Any]     =  shape_vocab_size
      lowerCAmelCase_     : List[Any]     =  concat_input
      lowerCAmelCase_     : Any     =  position_embedding_type
      lowerCAmelCase_     : List[str]     =  classifier_dropout
      super().__init__(pad_token_id=lowerCamelCase       ,		**lowerCamelCase						)



