

import copy
import os
from typing import Union

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


__A      :   Tuple          =	logging.get_logger(__name__)

__A      :   int          =	{
    'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/blip-vqa-base/resolve/main/config.json',
    'Salesforce/blip-vqa-capfit-large': (
        'https://huggingface.co/Salesforce/blip-vqa-base-capfit/resolve/main/config.json'
    ),
    'Salesforce/blip-image-captioning-base': (
        'https://huggingface.co/Salesforce/blip-image-captioning-base/resolve/main/config.json'
    ),
    'Salesforce/blip-image-captioning-large': (
        'https://huggingface.co/Salesforce/blip-image-captioning-large/resolve/main/config.json'
    ),
    'Salesforce/blip-itm-base-coco': 'https://huggingface.co/Salesforce/blip-itm-base-coco/resolve/main/config.json',
    'Salesforce/blip-itm-large-coco': 'https://huggingface.co/Salesforce/blip-itm-large-coco/resolve/main/config.json',
    'Salesforce/blip-itm-base-flikr': 'https://huggingface.co/Salesforce/blip-itm-base-flikr/resolve/main/config.json',
    'Salesforce/blip-itm-large-flikr': (
        'https://huggingface.co/Salesforce/blip-itm-large-flikr/resolve/main/config.json'
    ),
}






class       __A (							_SCREAMING_SNAKE_CASE       ):
    lowerCAmelCase_							:						Union[str, Any]						 =							"blip_text_model"






    def __init__(		self	:			Optional[Any]			, UpperCAmelCase_	:			Dict=30524			, UpperCAmelCase_	:			int=768			, UpperCAmelCase_	:			List[str]=768			, UpperCAmelCase_	:			Any=3072			, UpperCAmelCase_	:			Optional[Any]=768			, UpperCAmelCase_	:			List[str]=12			, UpperCAmelCase_	:			Dict=8			, UpperCAmelCase_	:			Optional[int]=512			, UpperCAmelCase_	:			Union[str, Any]="gelu"			, UpperCAmelCase_	:			Union[str, Any]=1E-12			, UpperCAmelCase_	:			int=0.0			, UpperCAmelCase_	:			List[str]=0.0			, UpperCAmelCase_	:			Dict=0.02			, UpperCAmelCase_	:			int=30522			, UpperCAmelCase_	:			Optional[int]=2			, UpperCAmelCase_	:			List[str]=0			, UpperCAmelCase_	:			List[str]=102			, UpperCAmelCase_	:			List[Any]=True			, UpperCAmelCase_	:			Any=True			, **UpperCAmelCase_	:			int			, ):
        super().__init__(
            pad_token_id=_lowerCAmelCase			, bos_token_id=_lowerCAmelCase			, eos_token_id=_lowerCAmelCase			, sep_token_id=_lowerCAmelCase			, **_lowerCAmelCase			, )

        lowerCAmelCase :	Union[str, Any]				=					vocab_size
        lowerCAmelCase :	Union[str, Any]				=					hidden_size
        lowerCAmelCase :	Optional[Any]				=					encoder_hidden_size
        lowerCAmelCase :	List[str]				=					intermediate_size
        lowerCAmelCase :	List[Any]				=					projection_dim
        lowerCAmelCase :	str				=					hidden_dropout_prob
        lowerCAmelCase :	str				=					num_hidden_layers
        lowerCAmelCase :	Union[str, Any]				=					num_attention_heads
        lowerCAmelCase :	List[str]				=					max_position_embeddings
        lowerCAmelCase :	Union[str, Any]				=					layer_norm_eps
        lowerCAmelCase :	Optional[Any]				=					hidden_act
        lowerCAmelCase :	List[Any]				=					initializer_range
        lowerCAmelCase :	List[Any]				=					attention_probs_dropout_prob
        lowerCAmelCase :	Tuple				=					is_decoder
        lowerCAmelCase :	Optional[Any]				=					use_cache






    @classmethod
    def 		lowercase__       (		cls	:			List[str]			, UpperCAmelCase_	:			Union[str, os.PathLike]			, **UpperCAmelCase_	:			int			):
        cls._set_token_in_kwargs(_lowerCAmelCase			)

        lowerCAmelCase	,     lowerCAmelCase :	List[Any]				=					cls.get_config_dict(_lowerCAmelCase			, **_lowerCAmelCase			)

        # get the text config dict if we are loading from BlipConfig
        if config_dict.get('model_type'			) == "blip":
            lowerCAmelCase :	Optional[int]				=					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       __A (							_SCREAMING_SNAKE_CASE       ):
    lowerCAmelCase_							:						Optional[Any]						 =							"blip_vision_model"






    def __init__(		self	:			Union[str, Any]			, UpperCAmelCase_	:			Optional[int]=768			, UpperCAmelCase_	:			Optional[int]=3072			, UpperCAmelCase_	:			str=512			, UpperCAmelCase_	:			Optional[int]=12			, UpperCAmelCase_	:			Tuple=12			, UpperCAmelCase_	:			Tuple=384			, UpperCAmelCase_	:			Optional[int]=16			, UpperCAmelCase_	:			Dict="gelu"			, UpperCAmelCase_	:			Dict=1E-5			, UpperCAmelCase_	:			List[Any]=0.0			, UpperCAmelCase_	:			Any=1E-10			, **UpperCAmelCase_	:			List[str]			, ):
        super().__init__(**_lowerCAmelCase			)

        lowerCAmelCase :	Optional[Any]				=					hidden_size
        lowerCAmelCase :	Optional[int]				=					intermediate_size
        lowerCAmelCase :	Tuple				=					projection_dim
        lowerCAmelCase :	List[str]				=					num_hidden_layers
        lowerCAmelCase :	Any				=					num_attention_heads
        lowerCAmelCase :	Union[str, Any]				=					patch_size
        lowerCAmelCase :	int				=					image_size
        lowerCAmelCase :	List[Any]				=					initializer_range
        lowerCAmelCase :	List[str]				=					attention_dropout
        lowerCAmelCase :	List[Any]				=					layer_norm_eps
        lowerCAmelCase :	Optional[Any]				=					hidden_act






    @classmethod
    def 		lowercase__       (		cls	:			str			, UpperCAmelCase_	:			Union[str, os.PathLike]			, **UpperCAmelCase_	:			Union[str, Any]			):
        cls._set_token_in_kwargs(_lowerCAmelCase			)

        lowerCAmelCase	,     lowerCAmelCase :	Tuple				=					cls.get_config_dict(_lowerCAmelCase			, **_lowerCAmelCase			)

        # get the vision config dict if we are loading from BlipConfig
        if config_dict.get('model_type'			) == "blip":
            lowerCAmelCase :	Tuple				=					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(_lowerCAmelCase			, **_lowerCAmelCase			)






class       __A (							_SCREAMING_SNAKE_CASE       ):
    lowerCAmelCase_							:						Optional[Any]						 =							"blip"
    lowerCAmelCase_							:						str						 =							True






    def __init__(		self	:			List[str]			, UpperCAmelCase_	:			int=None			, UpperCAmelCase_	:			Optional[int]=None			, UpperCAmelCase_	:			str=512			, UpperCAmelCase_	:			List[str]=2.65_92			, UpperCAmelCase_	:			Optional[Any]=256			, **UpperCAmelCase_	:			Tuple			, ):
        super().__init__(**_lowerCAmelCase			)

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

        if vision_config is None:
            lowerCAmelCase :	Dict				=					{}
            logger.info('`vision_config` is `None`. Initializing the `BlipVisionConfig` with default values.'			)

        lowerCAmelCase :	Dict				=					BlipTextConfig(**_lowerCAmelCase			)
        lowerCAmelCase :	List[str]				=					BlipVisionConfig(**_lowerCAmelCase			)

        lowerCAmelCase :	Any				=					self.vision_config.hidden_size

        lowerCAmelCase :	List[Any]				=					projection_dim
        lowerCAmelCase :	Optional[int]				=					logit_scale_init_value
        lowerCAmelCase :	Union[str, Any]				=					1.0
        lowerCAmelCase :	List[str]				=					0.02
        lowerCAmelCase :	str				=					image_text_hidden_size






    @classmethod
    def 		lowercase__       (		cls	:			int			, UpperCAmelCase_	:			BlipTextConfig			, UpperCAmelCase_	:			BlipVisionConfig			, **UpperCAmelCase_	:			Optional[Any]			):
        return cls(text_config=text_config.to_dict()			, vision_config=vision_config.to_dict()			, **_lowerCAmelCase			)






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











class        lowerCamelCase_							:


 '''simple docstring'''







 def __init__(							self  :		List[Any]						):
       SCREAMING_SNAKE_CASE_							=			{}



 def       lowerCAmelCase_  (							self  :		List[str]						):
       print(self.vertex						)
       for i in self.vertex:
             print(_lowerCAmelCase				,				' -> '				,				' -> '.join([str(_lowerCAmelCase						) for j in self.vertex[i]]						)						)



 def       lowerCAmelCase_  (							self  :		List[Any]				,				_lowerCAmelCase  :		int				,				_lowerCAmelCase  :		int						):
       # check if vertex is already present,
       if from_vertex in self.vertex:
             self.vertex[from_vertex].append(_lowerCAmelCase						)
       else:
             # else make a new vertex
             SCREAMING_SNAKE_CASE_							=			[to_vertex]



 def       lowerCAmelCase_  (							self  :		Dict						):
       # visited array for storing already visited nodes
       SCREAMING_SNAKE_CASE_							=			[False] * len(self.vertex						)

       # call the recursive helper function
       for i in range(len(self.vertex						)						):
             if not visited[i]:
                   self.dfs_recursive(_lowerCAmelCase				,				_lowerCAmelCase						)




 def       lowerCAmelCase_  (							self  :		Union[str, Any]				,				_lowerCAmelCase  :		int				,				_lowerCAmelCase  :		list						):
       # mark start vertex as visited
       SCREAMING_SNAKE_CASE_							=			True

       print(_lowerCAmelCase				,				end=' '						)

       # Recur for all the vertices that are adjacent to this node
       for i in self.vertex:
             if not visited[i]:
                   self.dfs_recursive(_lowerCAmelCase				,				_lowerCAmelCase						)


if __name__ == "__main__":
   lowerCamelCase__ :   List[Any]					=							Graph()
   g.add_edge(0, 1)
   g.add_edge(0, 2)
   g.add_edge(1, 2)
   g.add_edge(2, 0)
   g.add_edge(2, 3)
   g.add_edge(3, 3)

   g.print_graph()
   print('DFS:')
   g.dfs()

   # OUTPUT:
   # 0  ->  1 -> 2
   # 1  ->  2
   # 2  ->  0 -> 3
   # 3  ->  3
   # DFS:
   #  0 1 2 3