






'''simple docstring'''

import copy
import os
from typing import Union

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


__lowerCamelCase : str											=			logging.get_logger(__name__)

__lowerCamelCase : List[str]											=			{
    "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       UpperCAmelCase (						__a  ):
		UpperCAmelCase					:	Any 			=		'''bridgetower_vision_model'''




		def __init__(self      :	Tuple							,			A__      :	str=7_6_8							,			A__      :	Union[str, Any]=1_2							,			A__      :	List[str]=3							,			A__      :	Optional[int]=1_6							,			A__      :	List[Any]=2_8_8							,			A__      :	Optional[Any]=1							,			A__      :	Any=1e-05							,			A__      :	Dict=False							,			A__      :	Any=True							,			A__      :	int=False							,			**A__      :	int							,			)					-> Dict:
						super().__init__(**a_				)
						lowercase         = hidden_size
						lowercase         = num_hidden_layers
						lowercase         = num_channels
						lowercase         = patch_size
						lowercase         = image_size
						lowercase         = initializer_factor
						lowercase         = layer_norm_eps
						lowercase         = stop_gradient
						lowercase         = share_layernorm
						lowercase         = remove_last_layer





		@classmethod
		def 				UpperCAmelCase__   (cls      :	Union[str, Any]							,			A__      :	Union[str, os.PathLike]							,			**A__      :	Optional[Any]				)					-> List[Any]:
						lowercase         = cls.get_config_dict(a_							,			**a_				)

						if config_dict.get("model_type"				) == "bridgetower":
										lowercase         = 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(a_							,			**a_				)




class       UpperCAmelCase (						__a  ):
		UpperCAmelCase					:	str 			=		'''bridgetower_text_model'''




		def __init__(self      :	str							,			A__      :	Dict=5_0_2_6_5							,			A__      :	List[Any]=7_6_8							,			A__      :	Union[str, Any]=1_2							,			A__      :	List[str]=1_2							,			A__      :	str=1							,			A__      :	Optional[Any]=3_0_7_2							,			A__      :	int="gelu"							,			A__      :	int=0.1							,			A__      :	int=0.1							,			A__      :	Optional[int]=5_1_4							,			A__      :	Tuple=1							,			A__      :	Tuple=1e-05							,			A__      :	Optional[int]=1							,			A__      :	Union[str, Any]=0							,			A__      :	str=2							,			A__      :	Any="absolute"							,			A__      :	List[Any]=True							,			**A__      :	Union[str, Any]							,			)					-> List[str]:
						super().__init__(**a_				)

						lowercase         = vocab_size
						lowercase         = hidden_size
						lowercase         = num_hidden_layers
						lowercase         = num_attention_heads
						lowercase         = hidden_act
						lowercase         = initializer_factor
						lowercase         = intermediate_size
						lowercase         = hidden_dropout_prob
						lowercase         = attention_probs_dropout_prob
						lowercase         = max_position_embeddings
						lowercase         = type_vocab_size
						lowercase         = layer_norm_eps
						lowercase         = position_embedding_type
						lowercase         = use_cache
						lowercase         = pad_token_id
						lowercase         = bos_token_id
						lowercase         = eos_token_id





		@classmethod
		def 				UpperCAmelCase__   (cls      :	str							,			A__      :	Union[str, os.PathLike]							,			**A__      :	int				)					-> str:
						lowercase         = cls.get_config_dict(a_							,			**a_				)

						if config_dict.get("model_type"				) == "bridgetower":
										lowercase         = 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(a_							,			**a_				)




class       UpperCAmelCase (						__a  ):
		UpperCAmelCase					:	List[str] 			=		'''bridgetower'''




		def __init__(self      :	int							,			A__      :	List[str]=True							,			A__      :	Any="gelu"							,			A__      :	List[Any]=7_6_8							,			A__      :	int=1							,			A__      :	Optional[int]=1e-05							,			A__      :	Tuple=False							,			A__      :	Optional[Any]="add"							,			A__      :	List[str]=1_2							,			A__      :	Union[str, Any]=6							,			A__      :	int=False							,			A__      :	Any=False							,			A__      :	Dict=None							,			A__      :	Any=None							,			**A__      :	str							,			)					-> Dict:
						lowercase         = kwargs.pop("text_config_dict"							,			a_				)
						lowercase         = kwargs.pop("vision_config_dict"							,			a_				)

						super().__init__(**a_				)
						lowercase         = share_cross_modal_transformer_layers
						lowercase         = hidden_act
						lowercase         = hidden_size
						lowercase         = initializer_factor
						lowercase         = layer_norm_eps
						lowercase         = share_link_tower_layers
						lowercase         = link_tower_type
						lowercase         = num_attention_heads
						lowercase         = num_hidden_layers
						lowercase         = tie_word_embeddings
						lowercase         = init_layernorm_from_vision_encoder

						if text_config is None:
										lowercase         = {}
										logger.info("`text_config` is `None`. Initializing the `BridgeTowerTextConfig` with default values."				)

						if vision_config is None:
										lowercase         = {}
										logger.info("`vision_config` is `None`. Initializing the `BridgeTowerVisionConfig` with default values."				)

						lowercase         = BridgeTowerTextConfig(**a_				)
						lowercase         = BridgeTowerVisionConfig(**a_				)




		@classmethod
		def 				UpperCAmelCase__   (cls      :	Union[str, Any]							,			A__      :	BridgeTowerTextConfig							,			A__      :	BridgeTowerVisionConfig							,			**A__      :	Optional[Any]				)					-> List[str]:
						return cls(text_config=text_config.to_dict()							,			vision_config=vision_config.to_dict()							,			**a_				)





		def 				UpperCAmelCase__   (self      :	int				)					-> Any:
						lowercase         = copy.deepcopy(self.__dict__				)
						lowercase         = self.text_config.to_dict()
						lowercase         = self.vision_config.to_dict()
						lowercase         = self.__class__.model_type
						return output











'''simple docstring'''

__lowerCamelCase : str											=			8.314_4598







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				if temperature < 0:
								raise Exception("Temperature cannot be less than 0 K"							)
				if molar_mass <= 0:
								raise Exception("Molar mass cannot be less than or equal to 0 kg/mol"							)
				else:
								return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
			import doctest

			# run doctest
			doctest.testmod()

			# example
			__lowerCamelCase : Optional[Any]											=			300
			__lowerCamelCase : Tuple											=			28
			__lowerCamelCase : str											=			rms_speed_of_molecule(temperature, molar_mass)
			print(f"Vrms of Nitrogen gas at 300 K is {vrms} m/s")




