






from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding

class        _SCREAMING_SNAKE_CASE			(     _a ):
	snake_case__				:	str	      =    ["""image_processor""", """tokenizer"""]
	snake_case__				:	Optional[Any]	      =    """EfficientNetImageProcessor"""
	snake_case__				:	Union[str, Any]	      =    ("""BertTokenizer""", """BertTokenizerFast""")





	def __init__(						self							:   Dict					,    __lowerCamelCase							:   Optional[Any]					,    __lowerCamelCase							:   Optional[int]      ):
		super().__init__(__lowerCamelCase					,    __lowerCamelCase      )





	def __call__(						self							:   Optional[Any]					,    __lowerCamelCase							:   List[str]=None					,    __lowerCamelCase							:   List[str]=None					,    __lowerCamelCase							:   Optional[int]="max_length"					,    __lowerCamelCase							:   Any=64					,    __lowerCamelCase							:   Union[str, Any]=None					,    **__lowerCamelCase							:   Any      ):
		if text is None and images is None:
			raise ValueError("""You have to specify either text or images. Both cannot be none."""      )

		if text is not None:
			UpperCamelCase	:List[Any]		=      self.tokenizer(
			    __lowerCamelCase					,    padding=__lowerCamelCase					,    max_length=__lowerCamelCase					,    return_tensors=__lowerCamelCase					,    **__lowerCamelCase      )

		if images is not None:
			UpperCamelCase	:Any		=      self.image_processor(__lowerCamelCase					,    return_tensors=__lowerCamelCase					,    **__lowerCamelCase      )

		if text is not None and images is not None:
			UpperCamelCase	:int		=      image_features.pixel_values
			return encoding
		elif text is not None:
			return encoding
		else:
			return BatchEncoding(data=dict(**__lowerCamelCase      )					,    tensor_type=__lowerCamelCase      )





	def 		_A					(						self							:   Optional[Any]					,    *__lowerCamelCase							:   Any					,    **__lowerCamelCase							:   Union[str, Any]      ):
		return self.tokenizer.batch_decode(*__lowerCamelCase					,    **__lowerCamelCase      )





	def 		_A					(						self							:   Optional[int]					,    *__lowerCamelCase							:   List[str]					,    **__lowerCamelCase							:   Any      ):
		return self.tokenizer.decode(*__lowerCamelCase					,    **__lowerCamelCase      )





	@property
	def 		_A					(						self							:   Dict      ):
		UpperCamelCase	:Tuple		=      self.tokenizer.model_input_names
		UpperCamelCase	:List[Any]		=      self.image_processor.model_input_names
		return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names      )      )








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)}'''
	)
