



"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

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


__a           =							logging.get_logger(__name__)

__a           =							{
    "google/mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json"
}
class 							lowerCamelCase    (     _lowerCAmelCase							):






					'''simple docstring'''





					_A						:     int		=	MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
					_A						:     Optional[int]		=	"""mobilebert"""






					def __init__(			self:				int		,	snake_case:				str=30_522		,	snake_case:				List[Any]=512		,	snake_case:				Any=24		,	snake_case:				List[str]=4		,	snake_case:				Optional[Any]=512		,	snake_case:				List[str]="relu"		,	snake_case:				Optional[Any]=0.0		,	snake_case:				Tuple=0.1		,	snake_case:				Tuple=512		,	snake_case:				int=2		,	snake_case:				List[Any]=0.0_2		,	snake_case:				List[Any]=1E-12		,	snake_case:				int=0		,	snake_case:				List[str]=128		,	snake_case:				str=True		,	snake_case:				Any=True		,	snake_case:				Optional[int]=128		,	snake_case:				List[Any]=False		,	snake_case:				Optional[int]=True		,	snake_case:				List[Any]=4		,	snake_case:				List[str]="no_norm"		,	snake_case:				List[str]=True		,	snake_case:				Any=None		,	**snake_case:				Tuple		,	)  ->      str:
											super().__init__(pad_token_id=snake_case		,	**snake_case		)

											snake_case_					:Tuple		=     vocab_size
											snake_case_					:int		=     hidden_size
											snake_case_					:Optional[int]		=     num_hidden_layers
											snake_case_					:Optional[int]		=     num_attention_heads
											snake_case_					:Union[str, Any]		=     hidden_act
											snake_case_					:Optional[int]		=     intermediate_size
											snake_case_					:List[str]		=     hidden_dropout_prob
											snake_case_					:List[str]		=     attention_probs_dropout_prob
											snake_case_					:Dict		=     max_position_embeddings
											snake_case_					:int		=     type_vocab_size
											snake_case_					:Optional[Any]		=     initializer_range
											snake_case_					:str		=     layer_norm_eps
											snake_case_					:int		=     embedding_size
											snake_case_					:Any		=     trigram_input
											snake_case_					:List[str]		=     use_bottleneck
											snake_case_					:Any		=     intra_bottleneck_size
											snake_case_					:List[str]		=     use_bottleneck_attention
											snake_case_					:Union[str, Any]		=     key_query_shared_bottleneck
											snake_case_					:Optional[Any]		=     num_feedforward_networks
											snake_case_					:List[Any]		=     normalization_type
											snake_case_					:List[str]		=     classifier_activation

											if self.use_bottleneck:
																	snake_case_					:Optional[int]		=     intra_bottleneck_size
											else:
																	snake_case_					:Optional[int]		=     hidden_size

											snake_case_					:Any		=     classifier_dropout

class 							lowerCamelCase    (     _lowerCAmelCase							):






					'''simple docstring'''





					@property
					def   lowerCAmelCase_							(			self:				Optional[int]		)  ->      Mapping[str, Mapping[int, str]]:
											if self.task == "multiple-choice":
																	snake_case_					:List[Any]		=     {0: """batch""", 1: """choice""", 2: """sequence"""}
											else:
																	snake_case_					:List[str]		=     {0: """batch""", 1: """sequence"""}
											return OrderedDict(
											    [
											        ("""input_ids""", dynamic_axis),
											        ("""attention_mask""", dynamic_axis),
											        ("""token_type_ids""", dynamic_axis),
											    ]		)








import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute

def   SCREAMING_SNAKE_CASE_				(				__magic_name__   :    float = np.pi / 2      ,     __magic_name__   :    float = np.pi / 2      ,     __magic_name__   :    float = np.pi / 2   )						->     qiskit.result.counts.Counts:






	"""simple docstring"""



	UpperCamelCase	:Optional[int]		=      QuantumRegister(3      ,     """qr"""   )  # Define the number of quantum bits
	UpperCamelCase	:Optional[Any]		=      ClassicalRegister(1      ,     """cr"""   )  # Define the number of classical bits

	UpperCamelCase	:List[Any]		=      QuantumCircuit(__magic_name__      ,     __magic_name__   )  # Define the quantum circuit.

	# Build the circuit
	quantum_circuit.u(__magic_name__      ,     __magic_name__      ,     __magic_name__      ,     0   )  # Quantum State to teleport
	quantum_circuit.h(1   )  # add hadamard gate
	quantum_circuit.cx(
	    1      ,     2   )  # add control gate with qubit 1 as control and 2 as target.
	quantum_circuit.cx(0      ,     1   )
	quantum_circuit.h(0   )
	quantum_circuit.cz(0      ,     2   )  # add control z gate.
	quantum_circuit.cx(1      ,     2   )

	quantum_circuit.measure([2]      ,     [0]   )  # measure the qubit.

	# Simulate the circuit using qasm simulator
	UpperCamelCase	:Union[str, Any]		=      Aer.get_backend("""aer_simulator"""   )
	UpperCamelCase	:Dict		=      execute(__magic_name__      ,     __magic_name__      ,     shots=1000   )

	return job.result().get_counts(__magic_name__   )


if __name__ == "__main__":
	print(
	    '''Total count for teleported state is: '''
	    F'''{quantum_teleportation(np.pi/2, np.pi/2, np.pi/2)}'''
	)
