





'''simple docstring'''






import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig


A__				:   List[str]      ={
    '''facebook/maskformer-swin-base-ade''': (
        '''https://huggingface.co/facebook/maskformer-swin-base-ade/blob/main/config.json'''
    )
    # See all MaskFormer models at https://huggingface.co/models?filter=maskformer
}

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




class  UpperCAmelCase     (			snake_case_   ):
      _lowercase:			Tuple						     =   '''maskformer'''
      _lowercase:			List[Any]						     =   {'''hidden_size''': '''mask_feature_size'''}
      _lowercase:			List[str]						     =   ['''resnet''', '''swin''']
      _lowercase:			int						     =   ['''detr''']




      def __init__(			self			: List[str]			,			__snake_case			: int = 2_56			,			__snake_case			: int = 2_56			,			__snake_case			: float = 0.1			,			__snake_case			: bool = False			,			__snake_case			: Optional[Dict] = None			,			__snake_case			: Optional[Dict] = None			,			__snake_case			: float = 0.02			,			__snake_case			: float = 1.0			,			__snake_case			: float = 1.0			,			__snake_case			: float = 1.0			,			__snake_case			: float = 20.0			,			__snake_case			: Optional[bool] = None			,			**__snake_case			: List[Any]			,			)				->      int:
            if backbone_config is None:
                  # fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
                  _lowerCAmelCase							     =							SwinConfig(
                      image_size=3_84			,			in_channels=3			,			patch_size=4			,			embed_dim=1_28			,			depths=[2, 2, 18, 2]			,			num_heads=[4, 8, 16, 32]			,			window_size=12			,			drop_path_rate=0.3			,			out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]			,			)

            if isinstance(__snake_case			,			__snake_case  ):
                  _lowerCAmelCase							     =							backbone_config.pop("""model_type"""  )
                  _lowerCAmelCase							     =							CONFIG_MAPPING[backbone_model_type]
                  _lowerCAmelCase							     =							config_class.from_dict(__snake_case  )

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

            if decoder_config is None:
                  # fall back to https://huggingface.co/facebook/detr-resnet-50
                  _lowerCAmelCase							     =							DetrConfig()
            else:
                  # verify that the decoder is supported
                  _lowerCAmelCase							     =							(
                      decoder_config.pop("""model_type"""  ) if isinstance(__snake_case			,			__snake_case  ) else decoder_config.model_type
                  )
                  if decoder_type not in self.decoders_supported:
                        raise ValueError(
                            f"Transformer Decoder {decoder_type} not supported, please use one of"
                            f" {','.join(self.decoders_supported  )}"  )
                  if isinstance(__snake_case			,			__snake_case  ):
                        _lowerCAmelCase							     =							CONFIG_MAPPING[decoder_type]
                        _lowerCAmelCase							     =							config_class.from_dict(__snake_case  )

            _lowerCAmelCase							     =							backbone_config
            _lowerCAmelCase							     =							decoder_config
            # main feature dimension for the model
            _lowerCAmelCase							     =							fpn_feature_size
            _lowerCAmelCase							     =							mask_feature_size
            # initializer
            _lowerCAmelCase							     =							init_std
            _lowerCAmelCase							     =							init_xavier_std
            # Hungarian matcher && loss
            _lowerCAmelCase							     =							cross_entropy_weight
            _lowerCAmelCase							     =							dice_weight
            _lowerCAmelCase							     =							mask_weight
            _lowerCAmelCase							     =							use_auxiliary_loss
            _lowerCAmelCase							     =							no_object_weight
            _lowerCAmelCase							     =							output_auxiliary_logits

            _lowerCAmelCase							     =							self.decoder_config.encoder_attention_heads
            _lowerCAmelCase							     =							self.decoder_config.num_hidden_layers
            super().__init__(**__snake_case  )




      @classmethod
      def 				lowercase__    (			cls			: Optional[int]			,			__snake_case			: PretrainedConfig			,			__snake_case			: PretrainedConfig			,			**__snake_case			: int  )				->      Union[str, Any]:
            return cls(
                backbone_config=__snake_case			,			decoder_config=__snake_case			,			**__snake_case			,			)




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













'''simple docstring'''
import copy
import os
from typing import Union

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


a__							:							List[Any] =logging.get_logger(__name__)

a__							:							List[Any] ={
    '''BAAI/AltCLIP''': '''https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json''',
    # See all AltCLIP models at https://huggingface.co/models?filter=altclip
}

class      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					Tuple					="altclip_text_model"






 def __init__(       self       :							str							,	__A       :							List[Any]=2_5_0_0_0_2							,	__A       :							Any=1_0_2_4							,	__A       :							int=2_4							,	__A       :							Dict=1_6							,	__A       :							Optional[Any]=4_0_9_6							,	__A       :							Union[str, Any]="gelu"							,	__A       :							Dict=0.1							,	__A       :							Dict=0.1							,	__A       :							List[str]=5_1_4							,	__A       :							Optional[int]=1							,	__A       :							int=0.02							,	__A       :							Optional[Any]=0.02							,	__A       :							Optional[Any]=1e-05							,	__A       :							Dict=1							,	__A       :							List[Any]=0							,	__A       :							int=2							,	__A       :							Tuple="absolute"							,	__A       :							Optional[Any]=True							,	__A       :							Optional[int]=7_6_8							,	**__A       :							List[str]							,	):
        super().__init__(pad_token_id=__A							,	bos_token_id=__A							,	eos_token_id=__A							,	**__A	)

        __UpperCamelCase       =  vocab_size
        __UpperCamelCase       =  hidden_size
        __UpperCamelCase       =  num_hidden_layers
        __UpperCamelCase       =  num_attention_heads
        __UpperCamelCase       =  hidden_act
        __UpperCamelCase       =  intermediate_size
        __UpperCamelCase       =  hidden_dropout_prob
        __UpperCamelCase       =  attention_probs_dropout_prob
        __UpperCamelCase       =  max_position_embeddings
        __UpperCamelCase       =  type_vocab_size
        __UpperCamelCase       =  initializer_range
        __UpperCamelCase       =  initializer_factor
        __UpperCamelCase       =  layer_norm_eps
        __UpperCamelCase       =  position_embedding_type
        __UpperCamelCase       =  use_cache
        __UpperCamelCase       =  project_dim






class      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					Tuple					="altclip_vision_model"






 def __init__(       self       :							List[Any]							,	__A       :							Union[str, Any]=7_6_8							,	__A       :							Optional[int]=3_0_7_2							,	__A       :							Optional[Any]=5_1_2							,	__A       :							Tuple=1_2							,	__A       :							Union[str, Any]=1_2							,	__A       :							Optional[int]=3							,	__A       :							Dict=2_2_4							,	__A       :							Tuple=3_2							,	__A       :							str="quick_gelu"							,	__A       :							Dict=1e-5							,	__A       :							Optional[int]=0.0							,	__A       :							List[Any]=0.02							,	__A       :							int=1.0							,	**__A       :							Optional[int]							,	):
        super().__init__(**__A	)

        __UpperCamelCase       =  hidden_size
        __UpperCamelCase       =  intermediate_size
        __UpperCamelCase       =  projection_dim
        __UpperCamelCase       =  num_hidden_layers
        __UpperCamelCase       =  num_attention_heads
        __UpperCamelCase       =  num_channels
        __UpperCamelCase       =  patch_size
        __UpperCamelCase       =  image_size
        __UpperCamelCase       =  initializer_range
        __UpperCamelCase       =  initializer_factor
        __UpperCamelCase       =  attention_dropout
        __UpperCamelCase       =  layer_norm_eps
        __UpperCamelCase       =  hidden_act






 @classmethod
 def        _lowerCamelCase					(       cls       :							Optional[Any]							,	__A       :							Union[str, os.PathLike]							,	**__A       :							Optional[Any]	):
        cls._set_token_in_kwargs(__A	)

        __UpperCamelCase       ,						__UpperCamelCase       =  cls.get_config_dict(__A							,	**__A	)

        # get the vision config dict if we are loading from AltCLIPConfig
        if config_dict.get('model_type'	) == "altclip":
               __UpperCamelCase       =  config_dict['vision_config']

        if "model_type" in config_dict and hasattr(cls							,	'model_type'	) and config_dict["model_type"] != cls.model_type:
               logger.warning(
                   f'''You are using a model of type {config_dict['model_type']} to instantiate a model of type '''
                   f'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''	)

        return cls.from_dict(__A							,	**__A	)






class      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					List[str]					="altclip"
 SCREAMING_SNAKE_CASE_	:					Optional[int]					=True






 def __init__(       self       :							Any							,	__A       :							List[str]=None							,	__A       :							List[Any]=None							,	__A       :							List[str]=7_6_8							,	__A       :							List[str]=2.6592							,	**__A       :							Dict	):
        # If `_config_dict` exist, we use them for the backward compatibility.
        # We pop out these 2 attributes before calling `super().__init__` to avoid them being saved (which causes a lot
        # of confusion!).
        __UpperCamelCase       =  kwargs.pop('text_config_dict'							,	__A	)
        __UpperCamelCase       =  kwargs.pop('vision_config_dict'							,	__A	)

        super().__init__(**__A	)

        # Instead of simply assigning `[text|vision]_config_dict` to `[text|vision]_config`, we use the values in
        # `[text|vision]_config_dict` to update the values in `[text|vision]_config`. The values should be same in most
        # cases, but we don't want to break anything regarding `_config_dict` that existed before commit `8827e1b2`.
        if text_config_dict is not None:
               if text_config is None:
                      __UpperCamelCase       =  {}

               # This is the complete result when using `text_config_dict`.
               __UpperCamelCase       =  AltCLIPTextConfig(**__A	).to_dict()

               # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
               for key, value in _text_config_dict.items():
                      if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
                             # If specified in `text_config_dict`
                             if key in text_config_dict:
                                    __UpperCamelCase       =  (
                                        f'''`{key}` is found in both `text_config_dict` and `text_config` but with different values. '''
                                        f'''The value `text_config_dict["{key}"]` will be used instead.'''
                                    )
                             # If inferred from default argument values (just to be super careful)
                             else:
                                    __UpperCamelCase       =  (
                                        f'''`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The '''
                                        f'''value `text_config["{key}"]` will be overriden.'''
                                    )
                             logger.warning(__A	)

            # Update all values in `text_config` with the ones in `_text_config_dict`.
               text_config.update(_text_config_dict	)

        if vision_config_dict is not None:
               if vision_config is None:
                      __UpperCamelCase       =  {}

               # This is the complete result when using `vision_config_dict`.
               __UpperCamelCase       =  AltCLIPVisionConfig(**__A	).to_dict()
               # convert keys to string instead of integer
               if "id2label" in _vision_config_dict:
                      __UpperCamelCase       =  {
                          str(__A	): value for key, value in _vision_config_dict['id2label'].items()
                      }

               # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
               for key, value in _vision_config_dict.items():
                      if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
                             # If specified in `vision_config_dict`
                             if key in vision_config_dict:
                                    __UpperCamelCase       =  (
                                        f'''`{key}` is found in both `vision_config_dict` and `vision_config` but with different '''
                                        f'''values. The value `vision_config_dict["{key}"]` will be used instead.'''
                                    )
                             # If inferred from default argument values (just to be super careful)
                             else:
                                    __UpperCamelCase       =  (
                                        f'''`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. '''
                                        f'''The value `vision_config["{key}"]` will be overriden.'''
                                    )
                             logger.warning(__A	)

            # Update all values in `vision_config` with the ones in `_vision_config_dict`.
               vision_config.update(_vision_config_dict	)

        if text_config is None:
               __UpperCamelCase       =  {}
               logger.info('`text_config` is `None`. Initializing the `AltCLIPTextConfig` with default values.'	)

        if vision_config is None:
               __UpperCamelCase       =  {}
               logger.info('`vision_config` is `None`. initializing the `AltCLIPVisionConfig` with default values.'	)

        __UpperCamelCase       =  AltCLIPTextConfig(**__A	)
        __UpperCamelCase       =  AltCLIPVisionConfig(**__A	)

        __UpperCamelCase       =  projection_dim
        __UpperCamelCase       =  logit_scale_init_value
        __UpperCamelCase       =  1.0






 @classmethod
 def        _lowerCamelCase					(       cls       :							Union[str, Any]							,	__A       :							AltCLIPTextConfig							,	__A       :							AltCLIPVisionConfig							,	**__A       :							Optional[Any]	):
        return cls(text_config=text_config.to_dict()							,	vision_config=vision_config.to_dict()							,	**__A	)






 def        _lowerCamelCase					(       self       :							List[Any]	):
        __UpperCamelCase       =  copy.deepcopy(self.__dict__	)
        __UpperCamelCase       =  self.text_config.to_dict()
        __UpperCamelCase       =  self.vision_config.to_dict()
        __UpperCamelCase       =  self.__class__.model_type
        return output
