

import copy
import os
from typing import Union

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


UpperCAmelCase_							:					Dict		 =   logging.get_logger(__name__)

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






class      lowerCamelCase_      (	_lowercase	):
	_lowercase		:   Union[str, Any]     					=				'''git_vision_model'''




	def __init__(     self						:     Tuple					,      __A						:     str=768					,      __A						:     Union[str, Any]=3072					,      __A						:     int=12					,      __A						:     str=12					,      __A						:     str=3					,      __A						:     Union[str, Any]=224					,      __A						:     Any=16					,      __A						:     Any="quick_gelu"					,      __A						:     Union[str, Any]=1e-5					,      __A						:     List[str]=0.0					,      __A						:     Dict=0.0_2					,      **__A						:     Union[str, Any]					,      ):
		super().__init__(**__A							)

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




	@classmethod
	def        lowerCAmelCase_       (     cls						:     Dict					,      __A						:     Union[str, os.PathLike]					,      **__A						:     str							):
		cls._set_token_in_kwargs(__A							)

		__A    ,				__A :			Optional[int]		    =			cls.get_config_dict(__A					,      **__A							)

		# get the vision config dict if we are loading from GITConfig
		if config_dict.get("""model_type"""							) == "git":
			__A :			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(__A					,      **__A							)






class      lowerCamelCase_      (	_lowercase	):
	_lowercase		:   Dict     					=				'''git'''




	def __init__(     self						:     str					,      __A						:     int=None					,      __A						:     Any=3_0522					,      __A						:     Any=768					,      __A						:     str=6					,      __A						:     List[Any]=12					,      __A						:     Dict=3072					,      __A						:     List[str]="gelu"					,      __A						:     Tuple=0.1					,      __A						:     Any=0.1					,      __A						:     str=1024					,      __A						:     List[Any]=0.0_2					,      __A						:     str=1e-1_2					,      __A						:     Union[str, Any]=0					,      __A						:     Any="absolute"					,      __A						:     str=True					,      __A						:     int=False					,      __A						:     List[Any]=101					,      __A						:     Union[str, Any]=102					,      __A						:     Tuple=None					,      **__A						:     Tuple					,      ):
		super().__init__(bos_token_id=__A					,      eos_token_id=__A					,      pad_token_id=__A					,      **__A							)

		if vision_config is None:
			__A :			Optional[int]		    =			{}
			logger.info("""vision_config is None. initializing the GitVisionConfig with default values."""							)

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

		__A :			Optional[int]		    =			bos_token_id
		__A :			Dict		    =			eos_token_id




	def        lowerCAmelCase_       (     self						:     Union[str, Any]							):
		__A :			Union[str, Any]		    =			copy.deepcopy(self.__dict__							)
		__A :			Optional[int]		    =			self.vision_config.to_dict()
		__A :			int		    =			self.__class__.model_type
		return output








def 							__SCREAMING_SNAKE_CASE     (   a__    :   int       )					->				int:
	if not isinstance(a__			,a__       ):
		raise TypeError("""Input value must be an 'int' type"""       )

	__A :			Union[str, Any]		    =			0
	while number:
		position += 1
		number >>= 1

	return position


if __name__ == "__main__":
			import doctest

			doctest.testmod()





