

'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE							:				Union[str, Any]     	=			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							:				Optional[Any]     	=			{
    "camembert-base": "https://huggingface.co/camembert-base/resolve/main/config.json",
    "umberto-commoncrawl-cased-v1": (
        "https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"
    ),
    "umberto-wikipedia-uncased-v1": (
        "https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"
    ),
}






class    snake_case     (      lowercase_		):






				"""simple docstring"""
				_a    	=     """camembert"""



				def __init__(    self,     _lowercase=30522,     _lowercase=768,     _lowercase=12,     _lowercase=12,     _lowercase=3072,     _lowercase="gelu",     _lowercase=0.1,     _lowercase=0.1,     _lowercase=512,     _lowercase=2,     _lowercase=0.02,     _lowercase=1E-12,     _lowercase=1,     _lowercase=0,     _lowercase=2,     _lowercase="absolute",     _lowercase=True,     _lowercase=None,     **_lowercase,     )     ->							List[str]:
											super().__init__(pad_token_id=_lowercase,     bos_token_id=_lowercase,     eos_token_id=_lowercase,     **_lowercase       )

											SCREAMING_SNAKE_CASE_				=				vocab_size
											SCREAMING_SNAKE_CASE_				=				hidden_size
											SCREAMING_SNAKE_CASE_				=				num_hidden_layers
											SCREAMING_SNAKE_CASE_				=				num_attention_heads
											SCREAMING_SNAKE_CASE_				=				hidden_act
											SCREAMING_SNAKE_CASE_				=				intermediate_size
											SCREAMING_SNAKE_CASE_				=				hidden_dropout_prob
											SCREAMING_SNAKE_CASE_				=				attention_probs_dropout_prob
											SCREAMING_SNAKE_CASE_				=				max_position_embeddings
											SCREAMING_SNAKE_CASE_				=				type_vocab_size
											SCREAMING_SNAKE_CASE_				=				initializer_range
											SCREAMING_SNAKE_CASE_				=				layer_norm_eps
											SCREAMING_SNAKE_CASE_				=				position_embedding_type
											SCREAMING_SNAKE_CASE_				=				use_cache
											SCREAMING_SNAKE_CASE_				=				classifier_dropout






class    snake_case     (      lowercase_		):






				"""simple docstring"""



				@property
				def   a__					(    self       )     ->							Mapping[str, Mapping[int, str]]:
											if self.task == "multiple-choice":
																		SCREAMING_SNAKE_CASE_				=				{0: 'batch', 1: 'choice', 2: 'sequence'}
											else:
																		SCREAMING_SNAKE_CASE_				=				{0: 'batch', 1: 'sequence'}
											return OrderedDict(
											    [
											        ('input_ids', dynamic_axis),
											        ('attention_mask', dynamic_axis),
											    ]       )








'''simple docstring'''

SCREAMING_SNAKE_CASE							:				int     	=			8.3_1_4_4_5_9_8




def 							_UpperCamelCase				(   lowerCAmelCase__:					float		,lowerCAmelCase__:					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
							SCREAMING_SNAKE_CASE							:				List[str]     	=			300
							SCREAMING_SNAKE_CASE							:				List[Any]     	=			28
							SCREAMING_SNAKE_CASE							:				Optional[Any]     	=			rms_speed_of_molecule(temperature, molar_mass)
							print(f"Vrms of Nitrogen gas at 300 K is {vrms} m/s")





