


import copy
import os
from typing import Union

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


lowerCAmelCase__      		= logging.get_logger(__name__)

lowerCAmelCase__      		= {
    'microsoft/git-base': 'https://huggingface.co/microsoft/git-base/resolve/main/config.json',
}







class      lowerCAmelCase__       (				a):




     '''simple docstring'''
     __SCREAMING_SNAKE_CASE  			= "git_vision_model"


     def __init__(						self ,						__lowerCamelCase=7_6_8 ,						__lowerCamelCase=3_0_7_2 ,						__lowerCamelCase=1_2 ,						__lowerCamelCase=1_2 ,						__lowerCamelCase=3 ,						__lowerCamelCase=2_2_4 ,						__lowerCamelCase=1_6 ,						__lowerCamelCase="quick_gelu" ,						__lowerCamelCase=1e-5 ,						__lowerCamelCase=0.0 ,						__lowerCamelCase=0.0_2 ,						**__lowerCamelCase ,						)			->				Any:
            super().__init__(**__lowerCamelCase)

            _A      :       int				    = hidden_size
            _A      :       int				    = intermediate_size
            _A      :       int				    = num_hidden_layers
            _A      :       Dict				    = num_attention_heads
            _A      :       Dict				    = num_channels
            _A      :       List[Any]				    = patch_size
            _A      :       str				    = image_size
            _A      :       str				    = initializer_range
            _A      :       int				    = attention_dropout
            _A      :       Tuple				    = layer_norm_eps
            _A      :       Dict				    = hidden_act


     @classmethod
     def  _lowerCamelCase (						cls ,						__lowerCamelCase ,						**__lowerCamelCase)			->				"PretrainedConfig":
            cls._set_token_in_kwargs(__lowerCamelCase)

            _A    ,			_A      :       Union[str, Any]				    = cls.get_config_dict(__lowerCamelCase ,						**__lowerCamelCase)

            # get the vision config dict if we are loading from GITConfig
            if config_dict.get("model_type") == "git":
                   _A      :       Optional[int]				    = 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      lowerCAmelCase__       (				a):




     '''simple docstring'''
     __SCREAMING_SNAKE_CASE  			= "git"


     def __init__(						self ,						__lowerCamelCase=None ,						__lowerCamelCase=3_0_5_2_2 ,						__lowerCamelCase=7_6_8 ,						__lowerCamelCase=6 ,						__lowerCamelCase=1_2 ,						__lowerCamelCase=3_0_7_2 ,						__lowerCamelCase="gelu" ,						__lowerCamelCase=0.1 ,						__lowerCamelCase=0.1 ,						__lowerCamelCase=1_0_2_4 ,						__lowerCamelCase=0.0_2 ,						__lowerCamelCase=1e-12 ,						__lowerCamelCase=0 ,						__lowerCamelCase="absolute" ,						__lowerCamelCase=True ,						__lowerCamelCase=False ,						__lowerCamelCase=1_0_1 ,						__lowerCamelCase=1_0_2 ,						__lowerCamelCase=None ,						**__lowerCamelCase ,						)			->				Optional[Any]:
            super().__init__(bos_token_id=__lowerCamelCase ,						eos_token_id=__lowerCamelCase ,						pad_token_id=__lowerCamelCase ,						**__lowerCamelCase)

            if vision_config is None:
                   _A      :       List[str]				    = {}
                   logger.info("vision_config is None. initializing the GitVisionConfig with default values.")

            _A      :       str				    = GitVisionConfig(**__lowerCamelCase)
            _A      :       Tuple				    = vocab_size
            _A      :       str				    = hidden_size
            _A      :       Optional[int]				    = num_hidden_layers
            _A      :       List[str]				    = num_attention_heads
            _A      :       Optional[Any]				    = hidden_act
            _A      :       str				    = intermediate_size
            _A      :       Tuple				    = hidden_dropout_prob
            _A      :       Any				    = attention_probs_dropout_prob
            _A      :       int				    = max_position_embeddings
            _A      :       List[Any]				    = initializer_range
            _A      :       List[Any]				    = layer_norm_eps
            _A      :       Union[str, Any]				    = position_embedding_type
            _A      :       Union[str, Any]				    = use_cache
            _A      :       int				    = tie_word_embeddings
            _A      :       int				    = num_image_with_embedding

            _A      :       Optional[Any]				    = bos_token_id
            _A      :       str				    = eos_token_id


     def  _lowerCamelCase (						self)			->				Dict:
            _A      :       str				    = copy.deepcopy(self.__dict__)
            _A      :       Any				    = self.vision_config.to_dict()
            _A      :       Tuple				    = self.__class__.model_type
            return output







'''simple docstring'''




def 	UpperCAmelCase_							(					__lowercase							:      int       )		->       int:


     '''simple docstring'''



     if not isinstance(__lowercase			,     __lowercase       ) or number < 0:
          raise ValueError("Input must be a non-negative integer"       )

     _UpperCAmelCase     							=   0
     while number:
          # This way we arrive at next set bit (next 1) instead of looping
          # through each bit and checking for 1s hence the
          # loop won't run 32 times it will only run the number of `1` times
          number &= number - 1
          count += 1
     return count


if __name__ == "__main__":
  import doctest

  doctest.testmod()




