




import copy
import os
from typing import Union

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


lowerCamelCase    :		Optional[int]			   =       logging.get_logger(__name__)

lowerCamelCase    :		List[str]			   =       {
    "microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/config.json",
}







class   A(						UpperCamelCase       ):



 '''simple docstring'''


 UpperCamelCase						       =						'''git_vision_model'''

 def __init__(    self :  Optional[Any]						,							A_ :  str=768						,							A_ :  Any=3072						,							A_ :  str=12						,							A_ :  List[Any]=12						,							A_ :  List[str]=3						,							A_ :  Dict=224						,							A_ :  Dict=16						,							A_ :  Tuple="quick_gelu"						,							A_ :  List[str]=1E-5						,							A_ :  List[Any]=0.0						,							A_ :  Any=0.02						,							**A_ :  Dict						,							)       ->     Optional[int]:

       """simple docstring"""






       super().__init__(**A_  )

       lowerCamelCase_							=   hidden_size
       lowerCamelCase_							=   intermediate_size
       lowerCamelCase_							=   num_hidden_layers
       lowerCamelCase_							=   num_attention_heads
       lowerCamelCase_							=   num_channels
       lowerCamelCase_							=   patch_size
       lowerCamelCase_							=   image_size
       lowerCamelCase_							=   initializer_range
       lowerCamelCase_							=   attention_dropout
       lowerCamelCase_							=   layer_norm_eps
       lowerCamelCase_							=   hidden_act





 @classmethod
 def     a__			(    cls :  Any						,							A_ :  Union[str, os.PathLike]						,							**A_ :  List[Any]  )       ->     "PretrainedConfig":

       """simple docstring"""






       cls._set_token_in_kwargs(A_  )

       lowerCamelCase_					,    lowerCamelCase_							=   cls.get_config_dict(A_						,							**A_  )

       # get the vision config dict if we are loading from GITConfig
       if config_dict.get('model_type'  ) == "git":
             lowerCamelCase_							=   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   A(						UpperCamelCase       ):



 '''simple docstring'''


 UpperCamelCase						       =						'''git'''

 def __init__(    self :  Dict						,							A_ :  Union[str, Any]=None						,							A_ :  int=30522						,							A_ :  List[Any]=768						,							A_ :  Dict=6						,							A_ :  Union[str, Any]=12						,							A_ :  Dict=3072						,							A_ :  int="gelu"						,							A_ :  Optional[int]=0.1						,							A_ :  List[str]=0.1						,							A_ :  Tuple=1024						,							A_ :  Optional[Any]=0.02						,							A_ :  str=1E-12						,							A_ :  Union[str, Any]=0						,							A_ :  Dict="absolute"						,							A_ :  Union[str, Any]=True						,							A_ :  Dict=False						,							A_ :  Union[str, Any]=101						,							A_ :  str=102						,							A_ :  Union[str, Any]=None						,							**A_ :  str						,							)       ->     Union[str, Any]:

       """simple docstring"""






       super().__init__(bos_token_id=A_						,							eos_token_id=A_						,							pad_token_id=A_						,							**A_  )

       if vision_config is None:
             lowerCamelCase_							=   {}
             logger.info('vision_config is None. initializing the GitVisionConfig with default values.'  )

       lowerCamelCase_							=   GitVisionConfig(**A_  )
       lowerCamelCase_							=   vocab_size
       lowerCamelCase_							=   hidden_size
       lowerCamelCase_							=   num_hidden_layers
       lowerCamelCase_							=   num_attention_heads
       lowerCamelCase_							=   hidden_act
       lowerCamelCase_							=   intermediate_size
       lowerCamelCase_							=   hidden_dropout_prob
       lowerCamelCase_							=   attention_probs_dropout_prob
       lowerCamelCase_							=   max_position_embeddings
       lowerCamelCase_							=   initializer_range
       lowerCamelCase_							=   layer_norm_eps
       lowerCamelCase_							=   position_embedding_type
       lowerCamelCase_							=   use_cache
       lowerCamelCase_							=   tie_word_embeddings
       lowerCamelCase_							=   num_image_with_embedding

       lowerCamelCase_							=   bos_token_id
       lowerCamelCase_							=   eos_token_id





 def     a__			(    self :  Union[str, Any]  )       ->     Dict:

       """simple docstring"""






       lowerCamelCase_							=   copy.deepcopy(self.__dict__  )
       lowerCamelCase_							=   self.vision_config.to_dict()
       lowerCamelCase_							=   self.__class__.model_type
       return output









def       _SCREAMING_SNAKE_CASE      (							lowercase     :	str     ,							lowercase     :	int					):


      '''simple docstring'''



      return [sentence[i : i + ngram_size] for i in range(len(lowercase					) - ngram_size + 1					)]


if __name__ == "__main__":
 from doctest import testmod

 testmod()



