
from collections import OrderedDict
from typing import Mapping

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


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

__snake_case					:							Dict           =							{
    'google/electra-small-generator': 'https://huggingface.co/google/electra-small-generator/resolve/main/config.json',
    'google/electra-base-generator': 'https://huggingface.co/google/electra-base-generator/resolve/main/config.json',
    'google/electra-large-generator': 'https://huggingface.co/google/electra-large-generator/resolve/main/config.json',
    'google/electra-small-discriminator': (
        'https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'
    ),
    'google/electra-base-discriminator': (
        'https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'
    ),
    'google/electra-large-discriminator': (
        'https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'
    ),
}


class 	UpperCamelCase__       (  UpperCAmelCase__):

						'''simple docstring'''



						__a     :    List[str]												=			"""electra"""


						def __init__(  self  , A=3_05_22  , A=1_28  , A=2_56  , A=12  , A=4  , A=10_24  , A="gelu"  , A=0.1  , A=0.1  , A=5_12  , A=2  , A=0.02  , A=1e-12  , A="first"  , A=True  , A="gelu"  , A=0.1  , A=0  , A="absolute"  , A=True  , A=None  , **A  , )  ->Optional[int]:
									super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_  , **SCREAMING_SNAKE_CASE_	)

									UpperCAmelCase__		:Dict 		=    vocab_size
									UpperCAmelCase__		:Optional[Any] 		=    embedding_size
									UpperCAmelCase__		:Optional[Any] 		=    hidden_size
									UpperCAmelCase__		:Tuple 		=    num_hidden_layers
									UpperCAmelCase__		:Union[str, Any] 		=    num_attention_heads
									UpperCAmelCase__		:str 		=    intermediate_size
									UpperCAmelCase__		:Any 		=    hidden_act
									UpperCAmelCase__		:Optional[Any] 		=    hidden_dropout_prob
									UpperCAmelCase__		:Tuple 		=    attention_probs_dropout_prob
									UpperCAmelCase__		:Union[str, Any] 		=    max_position_embeddings
									UpperCAmelCase__		:str 		=    type_vocab_size
									UpperCAmelCase__		:List[Any] 		=    initializer_range
									UpperCAmelCase__		:int 		=    layer_norm_eps

									UpperCAmelCase__		:Any 		=    summary_type
									UpperCAmelCase__		:Tuple 		=    summary_use_proj
									UpperCAmelCase__		:Optional[Any] 		=    summary_activation
									UpperCAmelCase__		:Optional[int] 		=    summary_last_dropout
									UpperCAmelCase__		:List[str] 		=    position_embedding_type
									UpperCAmelCase__		:List[Any] 		=    use_cache
									UpperCAmelCase__		:List[str] 		=    classifier_dropout


class 	UpperCamelCase__       (  UpperCAmelCase__):

						'''simple docstring'''



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







'''simple docstring'''





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

def   A			(							A_				:       float = np.pi / 2     ,				A_				:       float = np.pi / 2     ,				A_				:       float = np.pi / 2							):
						snake_case							:  List[Any]			=     QuantumRegister(3     ,				'''qr'''							)  # Define the number of quantum bits
						snake_case							:  List[Any]			=     ClassicalRegister(1     ,				'''cr'''							)  # Define the number of classical bits

						snake_case							:  Dict			=     QuantumCircuit(A_     ,				A_							)  # Define the quantum circuit.

						# Build the circuit
						quantum_circuit.u(A_     ,				A_     ,				A_     ,				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
						snake_case							:  str			=     Aer.get_backend('''aer_simulator'''							)
						snake_case							:  List[str]			=     execute(A_     ,				A_     ,				shots=1000							)

						return job.result().get_counts(A_							)


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

