




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


__UpperCamelCase      : Optional[Any]					      =   logging.get_logger(__name__)

__UpperCamelCase      : Tuple					      =   {
    '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json''',
}

class 	__lowerCAmelCase			(			lowercase__				):
       UpperCamelCase__        =						"""mpnet"""
       def __init__(		self		:Optional[Any]	,   __magic_name__		:List[str]=3_0527	,   __magic_name__		:Optional[int]=768	,   __magic_name__		:List[str]=12	,   __magic_name__		:Dict=12	,   __magic_name__		:Dict=3072	,   __magic_name__		:Dict="gelu"	,   __magic_name__		:Dict=0.1	,   __magic_name__		:Tuple=0.1	,   __magic_name__		:Dict=512	,   __magic_name__		:List[Any]=0.02	,   __magic_name__		:List[Any]=1E-1_2	,   __magic_name__		:List[Any]=32	,   __magic_name__		:str=1	,   __magic_name__		:Dict=0	,   __magic_name__		:Optional[Any]=2	,   **__magic_name__		:str	,   ):







        '''simple docstring'''







        super().__init__(pad_token_id=_A	,   bos_token_id=_A	,   eos_token_id=_A	,   **_A       )

        a		       =							vocab_size
        a		       =							hidden_size
        a		       =							num_hidden_layers
        a		       =							num_attention_heads
        a		       =							hidden_act
        a		       =							intermediate_size
        a		       =							hidden_dropout_prob
        a		       =							attention_probs_dropout_prob
        a		       =							max_position_embeddings
        a		       =							initializer_range
        a		       =							layer_norm_eps
        a		       =							relative_attention_num_buckets







import doctest

import projectq
from projectq.ops import H, Measure





def 	__A	(			__lowerCamelCase					)   -> int:
	a		       =							quantum_engine.allocate_qubit()
	H | qubit
	Measure | qubit
	return int(__lowerCamelCase					)


if __name__ == "__main__":
		doctest.testmod()

		# initialises a new quantum backend
		__UpperCamelCase      : List[Any]					      =   projectq.MainEngine()

		# Generate a list of 10 random numbers
		__UpperCamelCase      : Optional[int]					      =   [get_random_number(quantum_engine) for _ in range(10)]

		# Flushes the quantum engine from memory
		quantum_engine.flush()

		print("Random numbers", random_numbers_list)

