'''simple docstring'''

import copy
import os
from typing import Union

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


lowerCAmelCase_ : Tuple						  =      logging.get_logger(__name__)

lowerCAmelCase_ : List[str]						  =      {
    "BridgeTower/bridgetower-base": "https://huggingface.co/BridgeTower/bridgetower-base/blob/main/config.json",
    "BridgeTower/bridgetower-base-itm-mlm": (
        "https://huggingface.co/BridgeTower/bridgetower-base-itm-mlm/blob/main/config.json"
    ),
}





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='bridgetower_vision_model'


   def __init__(   self				:	Tuple   ,		__lowerCAmelCase				:	Any=768   ,		__lowerCAmelCase				:	Tuple=12   ,		__lowerCAmelCase				:	Optional[int]=3   ,		__lowerCAmelCase				:	Dict=16   ,		__lowerCAmelCase				:	Optional[Any]=288   ,		__lowerCAmelCase				:	Tuple=1   ,		__lowerCAmelCase				:	Tuple=1e-05   ,		__lowerCAmelCase				:	Any=False   ,		__lowerCAmelCase				:	Optional[Any]=True   ,		__lowerCAmelCase				:	List[Any]=False   ,		**__lowerCAmelCase				:	Tuple   ,		)      ->					List[str]:
         super().__init__(**__lowerCAmelCase)
         lowercase_     =      hidden_size
         lowercase_     =      num_hidden_layers
         lowercase_     =      num_channels
         lowercase_     =      patch_size
         lowercase_     =      image_size
         lowercase_     =      initializer_factor
         lowercase_     =      layer_norm_eps
         lowercase_     =      stop_gradient
         lowercase_     =      share_layernorm
         lowercase_     =      remove_last_layer


   @classmethod
   def __UpperCAmelCase       (   cls				:	Union[str, Any]   ,		__lowerCAmelCase				:	Union[str, os.PathLike]   ,		**__lowerCAmelCase				:	Dict)      ->					"PretrainedConfig":
         lowercase_ ,							lowercase_     =      cls.get_config_dict(__lowerCAmelCase   ,		**__lowerCAmelCase)

         if config_dict.get("model_type") == "bridgetower":
               lowercase_     =      config_dict["text_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(__lowerCAmelCase   ,		**__lowerCAmelCase)





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='bridgetower_text_model'


   def __init__(   self				:	int   ,		__lowerCAmelCase				:	Optional[int]=5_0265   ,		__lowerCAmelCase				:	Union[str, Any]=768   ,		__lowerCAmelCase				:	str=12   ,		__lowerCAmelCase				:	Optional[Any]=12   ,		__lowerCAmelCase				:	str=1   ,		__lowerCAmelCase				:	Dict=3072   ,		__lowerCAmelCase				:	Any="gelu"   ,		__lowerCAmelCase				:	Optional[int]=0.1   ,		__lowerCAmelCase				:	Tuple=0.1   ,		__lowerCAmelCase				:	Any=514   ,		__lowerCAmelCase				:	Union[str, Any]=1   ,		__lowerCAmelCase				:	Tuple=1e-05   ,		__lowerCAmelCase				:	int=1   ,		__lowerCAmelCase				:	Optional[Any]=0   ,		__lowerCAmelCase				:	Optional[Any]=2   ,		__lowerCAmelCase				:	List[Any]="absolute"   ,		__lowerCAmelCase				:	Union[str, Any]=True   ,		**__lowerCAmelCase				:	Any   ,		)      ->					Union[str, Any]:
         super().__init__(**__lowerCAmelCase)

         lowercase_     =      vocab_size
         lowercase_     =      hidden_size
         lowercase_     =      num_hidden_layers
         lowercase_     =      num_attention_heads
         lowercase_     =      hidden_act
         lowercase_     =      initializer_factor
         lowercase_     =      intermediate_size
         lowercase_     =      hidden_dropout_prob
         lowercase_     =      attention_probs_dropout_prob
         lowercase_     =      max_position_embeddings
         lowercase_     =      type_vocab_size
         lowercase_     =      layer_norm_eps
         lowercase_     =      position_embedding_type
         lowercase_     =      use_cache
         lowercase_     =      pad_token_id
         lowercase_     =      bos_token_id
         lowercase_     =      eos_token_id


   @classmethod
   def __UpperCAmelCase       (   cls				:	Optional[Any]   ,		__lowerCAmelCase				:	Union[str, os.PathLike]   ,		**__lowerCAmelCase				:	int)      ->					"PretrainedConfig":
         lowercase_ ,							lowercase_     =      cls.get_config_dict(__lowerCAmelCase   ,		**__lowerCAmelCase)

         if config_dict.get("model_type") == "bridgetower":
               lowercase_     =      config_dict["text_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(__lowerCAmelCase   ,		**__lowerCAmelCase)





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='bridgetower'


   def __init__(   self				:	Any   ,		__lowerCAmelCase				:	List[Any]=True   ,		__lowerCAmelCase				:	Union[str, Any]="gelu"   ,		__lowerCAmelCase				:	Optional[int]=768   ,		__lowerCAmelCase				:	str=1   ,		__lowerCAmelCase				:	Tuple=1e-05   ,		__lowerCAmelCase				:	int=False   ,		__lowerCAmelCase				:	List[str]="add"   ,		__lowerCAmelCase				:	Optional[int]=12   ,		__lowerCAmelCase				:	Optional[Any]=6   ,		__lowerCAmelCase				:	str=False   ,		__lowerCAmelCase				:	str=False   ,		__lowerCAmelCase				:	Optional[Any]=None   ,		__lowerCAmelCase				:	List[Any]=None   ,		**__lowerCAmelCase				:	Optional[int]   ,		)      ->					str:
         # TODO: remove this once the Hub files are updated.
         lowercase_     =      kwargs.pop("text_config_dict"   ,		__lowerCAmelCase)
         lowercase_     =      kwargs.pop("vision_config_dict"   ,		__lowerCAmelCase)

         super().__init__(**__lowerCAmelCase)
         lowercase_     =      share_cross_modal_transformer_layers
         lowercase_     =      hidden_act
         lowercase_     =      hidden_size
         lowercase_     =      initializer_factor
         lowercase_     =      layer_norm_eps
         lowercase_     =      share_link_tower_layers
         lowercase_     =      link_tower_type
         lowercase_     =      num_attention_heads
         lowercase_     =      num_hidden_layers
         lowercase_     =      tie_word_embeddings
         lowercase_     =      init_layernorm_from_vision_encoder

         if text_config is None:
               lowercase_     =      {}
               logger.info("`text_config` is `None`. Initializing the `BridgeTowerTextConfig` with default values.")

         if vision_config is None:
               lowercase_     =      {}
               logger.info("`vision_config` is `None`. Initializing the `BridgeTowerVisionConfig` with default values.")

         lowercase_     =      BridgeTowerTextConfig(**__lowerCAmelCase)
         lowercase_     =      BridgeTowerVisionConfig(**__lowerCAmelCase)


   @classmethod
   def __UpperCAmelCase       (   cls				:	List[str]   ,		__lowerCAmelCase				:	BridgeTowerTextConfig   ,		__lowerCAmelCase				:	BridgeTowerVisionConfig   ,		**__lowerCAmelCase				:	List[str])      ->					Any:
         return cls(text_config=text_config.to_dict()   ,		vision_config=vision_config.to_dict()   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Optional[Any])      ->					Tuple:
         lowercase_     =      copy.deepcopy(self.__dict__)
         lowercase_     =      self.text_config.to_dict()
         lowercase_     =      self.vision_config.to_dict()
         lowercase_     =      self.__class__.model_type
         return output







'''simple docstring'''

def __a (	__lowerCamelCase			:						list[int] ,		__lowerCamelCase			:						int				)	->							bool:
      '''simple docstring'''


      lowercase_     =      len(__lowerCamelCase				)
      lowercase_     =      [[False] * (required_sum + 1) for _ in range(arr_len + 1				)]

      # for each arr value, a sum of zero(0) can be formed by not taking any element
      # hence True/1
      for i in range(arr_len + 1				):
            lowercase_     =      True

      # sum is not zero and set is empty then false
      for i in range(1 ,		required_sum + 1				):
            lowercase_     =      False

      for i in range(1 ,		arr_len + 1				):
            for j in range(1 ,		required_sum + 1				):
                  if arr[i - 1] > j:
                        lowercase_     =      subset[i - 1][j]
                  if arr[i - 1] <= j:
                        lowercase_     =      subset[i - 1][j] or subset[i - 1][j - arr[i - 1]]

      return subset[arr_len][required_sum]


if __name__ == "__main__":
       import doctest

       doctest.testmod()






