
"""simple docstring"""





from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType



class __lowerCAmelCase					(       _lowercase   ):




			"""simple docstring"""







			snake_case						   =					["image_processor", "tokenizer"]
			snake_case						   =					"BridgeTowerImageProcessor"
			snake_case						   =					("RobertaTokenizer", "RobertaTokenizerFast")




			def __init__(					self    :       Tuple							, _snake_case    :       Union[str, Any]							, _snake_case    :       Tuple						)   ->			Dict:







								"""simple docstring"""
								super().__init__(__UpperCamelCase							, __UpperCamelCase						)




			def __call__(					self    :       int							, _snake_case    :       Union[str, Any]							, _snake_case    :       Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None							, _snake_case    :       bool = True							, _snake_case    :       Union[bool, str, PaddingStrategy] = False							, _snake_case    :       Union[bool, str, TruncationStrategy] = None							, _snake_case    :       Optional[int] = None							, _snake_case    :       int = 0							, _snake_case    :       Optional[int] = None							, _snake_case    :       Optional[bool] = None							, _snake_case    :       Optional[bool] = None							, _snake_case    :       bool = False							, _snake_case    :       bool = False							, _snake_case    :       bool = False							, _snake_case    :       bool = False							, _snake_case    :       bool = True							, _snake_case    :       Optional[Union[str, TensorType]] = None							, **_snake_case    :       List[Any]							, )   ->			Optional[Any]:







								"""simple docstring"""
								A_								=    self.tokenizer(
								    text=__UpperCamelCase							, add_special_tokens=__UpperCamelCase							, padding=__UpperCamelCase							, truncation=__UpperCamelCase							, max_length=__UpperCamelCase							, stride=__UpperCamelCase							, pad_to_multiple_of=__UpperCamelCase							, return_token_type_ids=__UpperCamelCase							, return_attention_mask=__UpperCamelCase							, return_overflowing_tokens=__UpperCamelCase							, return_special_tokens_mask=__UpperCamelCase							, return_offsets_mapping=__UpperCamelCase							, return_length=__UpperCamelCase							, verbose=__UpperCamelCase							, return_tensors=__UpperCamelCase							, **__UpperCamelCase							, )
								# add pixel_values + pixel_mask
								A_								=    self.image_processor(
								    __UpperCamelCase							, return_tensors=__UpperCamelCase							, do_normalize=__UpperCamelCase							, do_center_crop=__UpperCamelCase							, **__UpperCamelCase						)
								encoding.update(__UpperCamelCase						)

								return encoding




			def   lowerCamelCase__  (					self    :       int							, *_snake_case    :       Dict							, **_snake_case    :       Optional[Any]						)   ->			Optional[Any]:







								"""simple docstring"""
								return self.tokenizer.batch_decode(*__UpperCamelCase							, **__UpperCamelCase						)




			def   lowerCamelCase__  (					self    :       str							, *_snake_case    :       Dict							, **_snake_case    :       List[Any]						)   ->			int:







								"""simple docstring"""
								return self.tokenizer.decode(*__UpperCamelCase							, **__UpperCamelCase						)






			@property
			def   lowerCamelCase__  (					self    :       str						)   ->			int:







								"""simple docstring"""
								A_								=    self.tokenizer.model_input_names
								A_								=    self.image_processor.model_input_names
								return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)






lowercase   =	8.314_4598



def   __lowerCAmelCase    (				UpperCAmelCase__					:   float      ,					UpperCAmelCase__					:   float							)	->     float:
							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
		lowercase   =	3_0_0
		lowercase   =	2_8
		lowercase   =	rms_speed_of_molecule(temperature, molar_mass)
		print(F"""Vrms of Nitrogen gas at 300 K is {vrms} m/s""")





