


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



def 						_UpperCamelCase							( UpperCamelCase__ = np.pi / 2     ,   UpperCamelCase__ = np.pi / 2     ,   UpperCamelCase__ = np.pi / 2		):






				"""simple docstring"""



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

				__magic_name__				:					str						       =       QuantumCircuit(UpperCamelCase__     ,   UpperCamelCase__		)  # Define the quantum circuit.

				# Build the circuit
				quantum_circuit.u(UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__     ,   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
				__magic_name__				:					int						       =       Aer.get_backend("aer_simulator"		)
				__magic_name__				:					Dict						       =       execute(UpperCamelCase__     ,   UpperCamelCase__     ,   shots=1000		)

				return job.result().get_counts(UpperCamelCase__		)


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



'''simple docstring'''







import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property






class 		_snake_case    (				unittest.TestCase		):






						'''simple docstring'''







						@cached_property
						def lowerCAmelCase__ (  self:	Optional[Any]     )							->	List[Any]:
										return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B"     )







						@cached_property
						def lowerCAmelCase__ (  self:	Optional[Any]     )							->	Optional[int]:
										return BlenderbotTokenizerFast.from_pretrained("facebook/blenderbot-3B"     )







						def lowerCAmelCase__ (  self:	Optional[Any]     )							->	Optional[int]:
										__magic_name__				:					Tuple						       =       self.tokenizer_ab
										__magic_name__				:					Optional[int]						       =       " I am a small frog."
										__magic_name__				:					Optional[int]						       =       tok([src_text]      ,							padding=__UpperCamelCase      ,							truncation=__UpperCamelCase     )["input_ids"]
										__magic_name__				:					int						       =       tok.batch_decode(__UpperCamelCase      ,							skip_special_tokens=__UpperCamelCase      ,							clean_up_tokenization_spaces=__UpperCamelCase     )[0]
										assert src_text == decoded







						def lowerCAmelCase__ (  self:	Optional[int]     )							->	Any:
										__magic_name__				:					Tuple						       =       self.rust_tokenizer_ab
										__magic_name__				:					str						       =       " I am a small frog."
										__magic_name__				:					Union[str, Any]						       =       tok([src_text]      ,							padding=__UpperCamelCase      ,							truncation=__UpperCamelCase     )["input_ids"]
										__magic_name__				:					Any						       =       tok.batch_decode(__UpperCamelCase      ,							skip_special_tokens=__UpperCamelCase      ,							clean_up_tokenization_spaces=__UpperCamelCase     )[0]
										assert src_text == decoded







						def lowerCAmelCase__ (  self:	Optional[Any]     )							->	str:
										assert self.tokenizer_ab.add_prefix_space
										assert self.tokenizer_ab([" Sam", "Sam"]     ).input_ids == [[5502, 2], [5502, 2]]







						def lowerCAmelCase__ (  self:	List[str]     )							->	List[Any]:
										assert self.rust_tokenizer_ab.add_prefix_space
										assert self.rust_tokenizer_ab([" Sam", "Sam"]     ).input_ids == [[5502, 2], [5502, 2]]