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

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


a=  logging.get_logger(__name__)

a=  {
    '''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						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						'''bridgetower_vision_model'''







     def __init__(		self     ,			_lowerCamelCase=7_6_8     ,			_lowerCamelCase=1_2     ,			_lowerCamelCase=3     ,			_lowerCamelCase=1_6     ,			_lowerCamelCase=2_8_8     ,			_lowerCamelCase=1     ,			_lowerCamelCase=1E-0_5     ,			_lowerCamelCase=False     ,			_lowerCamelCase=True     ,			_lowerCamelCase=False     ,			**_lowerCamelCase     ,			):
         super().__init__(**_lowerCamelCase    )
         __UpperCamelCase	:	str		    =  hidden_size
         __UpperCamelCase	:	Union[str, Any]		    =  num_hidden_layers
         __UpperCamelCase	:	Dict		    =  num_channels
         __UpperCamelCase	:	Tuple		    =  patch_size
         __UpperCamelCase	:	Tuple		    =  image_size
         __UpperCamelCase	:	int		    =  initializer_factor
         __UpperCamelCase	:	Optional[Any]		    =  layer_norm_eps
         __UpperCamelCase	:	List[Any]		    =  stop_gradient
         __UpperCamelCase	:	List[str]		    =  share_layernorm
         __UpperCamelCase	:	List[str]		    =  remove_last_layer







     @classmethod
     def lowerCAmelCase     (		cls     ,			_lowerCamelCase     ,			**_lowerCamelCase    ):
         __UpperCamelCase	:	int		    =  cls.get_config_dict(_lowerCamelCase     ,			**_lowerCamelCase    )

         if config_dict.get('model_type'    ) == "bridgetower":
             __UpperCamelCase	:	Any		    =  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						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						'''bridgetower_text_model'''







     def __init__(		self     ,			_lowerCamelCase=5_0_2_6_5     ,			_lowerCamelCase=7_6_8     ,			_lowerCamelCase=1_2     ,			_lowerCamelCase=1_2     ,			_lowerCamelCase=1     ,			_lowerCamelCase=3_0_7_2     ,			_lowerCamelCase="gelu"     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=5_1_4     ,			_lowerCamelCase=1     ,			_lowerCamelCase=1E-0_5     ,			_lowerCamelCase=1     ,			_lowerCamelCase=0     ,			_lowerCamelCase=2     ,			_lowerCamelCase="absolute"     ,			_lowerCamelCase=True     ,			**_lowerCamelCase     ,			):
         super().__init__(**_lowerCamelCase    )

         __UpperCamelCase	:	Optional[int]		    =  vocab_size
         __UpperCamelCase	:	Any		    =  hidden_size
         __UpperCamelCase	:	Dict		    =  num_hidden_layers
         __UpperCamelCase	:	int		    =  num_attention_heads
         __UpperCamelCase	:	Optional[int]		    =  hidden_act
         __UpperCamelCase	:	str		    =  initializer_factor
         __UpperCamelCase	:	Optional[Any]		    =  intermediate_size
         __UpperCamelCase	:	Dict		    =  hidden_dropout_prob
         __UpperCamelCase	:	str		    =  attention_probs_dropout_prob
         __UpperCamelCase	:	Any		    =  max_position_embeddings
         __UpperCamelCase	:	List[str]		    =  type_vocab_size
         __UpperCamelCase	:	Tuple		    =  layer_norm_eps
         __UpperCamelCase	:	int		    =  position_embedding_type
         __UpperCamelCase	:	Optional[Any]		    =  use_cache
         __UpperCamelCase	:	Optional[Any]		    =  pad_token_id
         __UpperCamelCase	:	Optional[Any]		    =  bos_token_id
         __UpperCamelCase	:	List[str]		    =  eos_token_id







     @classmethod
     def lowerCAmelCase     (		cls     ,			_lowerCamelCase     ,			**_lowerCamelCase    ):
         __UpperCamelCase	:	Tuple		    =  cls.get_config_dict(_lowerCamelCase     ,			**_lowerCamelCase    )

         if config_dict.get('model_type'    ) == "bridgetower":
             __UpperCamelCase	:	Dict		    =  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						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						'''bridgetower'''







     def __init__(		self     ,			_lowerCamelCase=True     ,			_lowerCamelCase="gelu"     ,			_lowerCamelCase=7_6_8     ,			_lowerCamelCase=1     ,			_lowerCamelCase=1E-0_5     ,			_lowerCamelCase=False     ,			_lowerCamelCase="add"     ,			_lowerCamelCase=1_2     ,			_lowerCamelCase=6     ,			_lowerCamelCase=False     ,			_lowerCamelCase=False     ,			_lowerCamelCase=None     ,			_lowerCamelCase=None     ,			**_lowerCamelCase     ,			):
         # TODO: remove this once the Hub files are updated.
         __UpperCamelCase	:	Any		    =  kwargs.pop('text_config_dict'     ,			_lowerCamelCase    )
         __UpperCamelCase	:	Tuple		    =  kwargs.pop('vision_config_dict'     ,			_lowerCamelCase    )

         super().__init__(**_lowerCamelCase    )
         __UpperCamelCase	:	List[str]		    =  share_cross_modal_transformer_layers
         __UpperCamelCase	:	Optional[Any]		    =  hidden_act
         __UpperCamelCase	:	Optional[int]		    =  hidden_size
         __UpperCamelCase	:	Dict		    =  initializer_factor
         __UpperCamelCase	:	int		    =  layer_norm_eps
         __UpperCamelCase	:	Any		    =  share_link_tower_layers
         __UpperCamelCase	:	int		    =  link_tower_type
         __UpperCamelCase	:	int		    =  num_attention_heads
         __UpperCamelCase	:	Dict		    =  num_hidden_layers
         __UpperCamelCase	:	Optional[int]		    =  tie_word_embeddings
         __UpperCamelCase	:	List[str]		    =  init_layernorm_from_vision_encoder

         if text_config is None:
             __UpperCamelCase	:	List[str]		    =  {}
             logger.info('`text_config` is `None`. Initializing the `BridgeTowerTextConfig` with default values.'    )

         if vision_config is None:
             __UpperCamelCase	:	Union[str, Any]		    =  {}
             logger.info('`vision_config` is `None`. Initializing the `BridgeTowerVisionConfig` with default values.'    )

         __UpperCamelCase	:	Dict		    =  BridgeTowerTextConfig(**_lowerCamelCase    )
         __UpperCamelCase	:	Union[str, Any]		    =  BridgeTowerVisionConfig(**_lowerCamelCase    )







     @classmethod
     def lowerCAmelCase     (		cls     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			**_lowerCamelCase    ):
         return cls(text_config=text_config.to_dict()     ,			vision_config=vision_config.to_dict()     ,			**_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  copy.deepcopy(self.__dict__    )
         __UpperCamelCase	:	Optional[int]		    =  self.text_config.to_dict()
         __UpperCamelCase	:	List[Any]		    =  self.vision_config.to_dict()
         __UpperCamelCase	:	List[str]		    =  self.__class__.model_type
         return output




'''simple docstring'''
class 			__lowercase		:







     """simple docstring"""






     def __init__(		self    ):
         __UpperCamelCase	:	Any		    =  0
         __UpperCamelCase	:	Any		    =  0
         __UpperCamelCase	:	Any		    =  {}







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         if vertex not in self.adjacency:
             __UpperCamelCase	:	Tuple		    =  {}
             self.num_vertices += 1







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase    ):
         self.add_vertex(_lowerCamelCase    )
         self.add_vertex(_lowerCamelCase    )

         if head == tail:
             return

         __UpperCamelCase	:	List[Any]		    =  weight
         __UpperCamelCase	:	Optional[int]		    =  weight







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  self.get_edges()
         for edge in edges:
             __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Optional[int]		    =  edge
             edges.remove((tail, head, weight)    )
         for i in range(len(_lowerCamelCase    )    ):
             __UpperCamelCase	:	Union[str, Any]		    =  list(edges[i]    )

         edges.sort(key=lambda _lowerCamelCase    : e[2]    )
         for i in range(len(_lowerCamelCase    ) - 1    ):
             if edges[i][2] >= edges[i + 1][2]:
                 __UpperCamelCase	:	Optional[int]		    =  edges[i][2] + 1
         for edge in edges:
             __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Optional[int]		    =  edge
             __UpperCamelCase	:	Tuple		    =  weight
             __UpperCamelCase	:	Optional[Any]		    =  weight







     def __str__(		self    ):
         __UpperCamelCase	:	Optional[Any]		    =  ''
         for tail in self.adjacency:
             for head in self.adjacency[tail]:
                 __UpperCamelCase	:	Tuple		    =  self.adjacency[head][tail]
                 string += f"""{head} -> {tail} == {weight}\n"""
         return string.rstrip('\n'    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  []
         for tail in self.adjacency:
             for head in self.adjacency[tail]:
                 output.append((tail, head, self.adjacency[head][tail])    )
         return output







     def lowerCAmelCase     (		self    ):
         return self.adjacency.keys()







     @staticmethod
     def lowerCAmelCase     (		_lowerCamelCase=None     ,			_lowerCamelCase=None    ):
         __UpperCamelCase	:	Tuple		    =  Graph()
         if vertices is None:
             __UpperCamelCase	:	List[Any]		    =  []
         if edges is None:
             __UpperCamelCase	:	Optional[int]		    =  []
         for vertex in vertices:
             g.add_vertex(_lowerCamelCase    )
         for edge in edges:
             g.add_edge(*_lowerCamelCase    )
         return g






     class 			__lowercase		:







          """simple docstring"""






          def __init__(		self    ):
              __UpperCamelCase	:	Union[str, Any]		    =  {}
              __UpperCamelCase	:	int		    =  {}







          def __len__(		self    ):
              return len(self.parent    )







          def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
              if item in self.parent:
                  return self.find(_lowerCamelCase    )

              __UpperCamelCase	:	Optional[Any]		    =  item
              __UpperCamelCase	:	List[str]		    =  0
              return item







          def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
              if item not in self.parent:
                  return self.make_set(_lowerCamelCase    )
              if item != self.parent[item]:
                  __UpperCamelCase	:	int		    =  self.find(self.parent[item]    )
              return self.parent[item]







          def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase    ):
              __UpperCamelCase	:	Tuple		    =  self.find(_lowerCamelCase    )
              __UpperCamelCase	:	Any		    =  self.find(_lowerCamelCase    )

              if roota == roota:
                  return roota

              if self.rank[roota] > self.rank[roota]:
                  __UpperCamelCase	:	Dict		    =  roota
                  return roota

              if self.rank[roota] < self.rank[roota]:
                  __UpperCamelCase	:	Optional[Any]		    =  roota
                  return roota

              if self.rank[roota] == self.rank[roota]:
                  self.rank[roota] += 1
                  __UpperCamelCase	:	Dict		    =  roota
                  return roota
              return None







     @staticmethod
     def lowerCAmelCase     (		_lowerCamelCase    ):
         __UpperCamelCase	:	int		    =  graph.num_vertices

         __UpperCamelCase	:	str		    =  Graph.UnionFind()
         __UpperCamelCase	:	Tuple		    =  []
         while num_components > 1:
             __UpperCamelCase	:	Dict		    =  {}
             for vertex in graph.get_vertices():
                 __UpperCamelCase	:	str		    =  -1

             __UpperCamelCase	:	int		    =  graph.get_edges()
             for edge in edges:
                 __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	List[str]		    =  edge
                 edges.remove((tail, head, weight)    )
             for edge in edges:
                 __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Dict		    =  edge
                 __UpperCamelCase	:	List[Any]		    =  union_find.find(_lowerCamelCase    )
                 __UpperCamelCase	:	str		    =  union_find.find(_lowerCamelCase    )
                 if seta != seta:
                     if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                         __UpperCamelCase	:	str		    =  [head, tail, weight]

                     if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                         __UpperCamelCase	:	str		    =  [head, tail, weight]
             for vertex in cheap_edge:
                 if cheap_edge[vertex] != -1:
                     __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	List[str]		    =  cheap_edge[vertex]
                     if union_find.find(_lowerCamelCase    ) != union_find.find(_lowerCamelCase    ):
                         union_find.union(_lowerCamelCase     ,			_lowerCamelCase    )
                         mst_edges.append(cheap_edge[vertex]    )
                         __UpperCamelCase	:	int		    =  num_components - 1
         __UpperCamelCase	:	Union[str, Any]		    =  Graph.build(edges=_lowerCamelCase    )
         return mst



