






from ..utils import DummyObject, requires_backends





class     SCREAMING_SNAKE_CASE					(			metaclass=snake_case       ):





							"""simple docstring"""

							A_    	=       ["torch", "transformers", "onnx"]

							def __init__(	self: Tuple		,  *__A: str		,  **__A: List[str] )     ->					List[str]:
												requires_backends(self		,  ['''torch''', '''transformers''', '''onnx'''] )

							@classmethod
							def    __A			(	cls: Optional[int]		,  *__A: Any		,  **__A: List[Any] )     ->					Any:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )



							@classmethod
							def    __A			(	cls: List[str]		,  *__A: Any		,  **__A: Tuple )     ->					Optional[Any]:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )





class     SCREAMING_SNAKE_CASE					(			metaclass=snake_case       ):





							"""simple docstring"""

							A_    	=       ["torch", "transformers", "onnx"]

							def __init__(	self: List[str]		,  *__A: List[Any]		,  **__A: Any )     ->					Tuple:
												requires_backends(self		,  ['''torch''', '''transformers''', '''onnx'''] )

							@classmethod
							def    __A			(	cls: Dict		,  *__A: Any		,  **__A: Optional[int] )     ->					Optional[int]:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )



							@classmethod
							def    __A			(	cls: int		,  *__A: Dict		,  **__A: List[Any] )     ->					List[Any]:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )





class     SCREAMING_SNAKE_CASE					(			metaclass=snake_case       ):





							"""simple docstring"""

							A_    	=       ["torch", "transformers", "onnx"]

							def __init__(	self: str		,  *__A: Optional[int]		,  **__A: str )     ->					str:
												requires_backends(self		,  ['''torch''', '''transformers''', '''onnx'''] )

							@classmethod
							def    __A			(	cls: Any		,  *__A: List[str]		,  **__A: Dict )     ->					Dict:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )



							@classmethod
							def    __A			(	cls: str		,  *__A: Dict		,  **__A: Dict )     ->					Any:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )





class     SCREAMING_SNAKE_CASE					(			metaclass=snake_case       ):





							"""simple docstring"""

							A_    	=       ["torch", "transformers", "onnx"]

							def __init__(	self: Any		,  *__A: List[str]		,  **__A: str )     ->					Union[str, Any]:
												requires_backends(self		,  ['''torch''', '''transformers''', '''onnx'''] )

							@classmethod
							def    __A			(	cls: List[str]		,  *__A: List[str]		,  **__A: Optional[Any] )     ->					Optional[Any]:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )



							@classmethod
							def    __A			(	cls: Optional[int]		,  *__A: List[Any]		,  **__A: int )     ->					List[Any]:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )





class     SCREAMING_SNAKE_CASE					(			metaclass=snake_case       ):





							"""simple docstring"""

							A_    	=       ["torch", "transformers", "onnx"]

							def __init__(	self: Any		,  *__A: Optional[int]		,  **__A: Any )     ->					Tuple:
												requires_backends(self		,  ['''torch''', '''transformers''', '''onnx'''] )

							@classmethod
							def    __A			(	cls: Union[str, Any]		,  *__A: str		,  **__A: Optional[Any] )     ->					Any:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )



							@classmethod
							def    __A			(	cls: int		,  *__A: int		,  **__A: Tuple )     ->					Union[str, Any]:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )





class     SCREAMING_SNAKE_CASE					(			metaclass=snake_case       ):





							"""simple docstring"""

							A_    	=       ["torch", "transformers", "onnx"]

							def __init__(	self: List[str]		,  *__A: Tuple		,  **__A: int )     ->					int:
												requires_backends(self		,  ['''torch''', '''transformers''', '''onnx'''] )

							@classmethod
							def    __A			(	cls: Optional[int]		,  *__A: Tuple		,  **__A: Dict )     ->					str:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )



							@classmethod
							def    __A			(	cls: List[str]		,  *__A: Dict		,  **__A: List[Any] )     ->					Tuple:
												requires_backends(cls		,  ['''torch''', '''transformers''', '''onnx'''] )





'''simple docstring'''





import math

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







def snake_case_     (					lowercase__ = 3		):
  if isinstance(lowercase__   ,       lowercase__		):
    raise TypeError("number of qubits must be a integer."		)
  if number_of_qubits <= 0:
    raise ValueError("number of qubits must be > 0."		)
  if math.floor(lowercase__		) != number_of_qubits:
    raise ValueError("number of qubits must be exact integer."		)
  if number_of_qubits > 1_0:
    raise ValueError("number of qubits too large to simulate(>10)."		)

  UpperCAmelCase__      :					Optional[int]				       =							QuantumRegister(lowercase__   ,       "qr"		)
  UpperCAmelCase__      :					List[Any]				       =							ClassicalRegister(lowercase__   ,       "cr"		)

  UpperCAmelCase__      :					List[str]				       =							QuantumCircuit(lowercase__   ,       lowercase__		)

  UpperCAmelCase__      :					Union[str, Any]				       =							number_of_qubits

  for i in range(lowercase__		):
    quantum_circuit.h(number_of_qubits - i - 1		)
    counter -= 1
    for j in range(lowercase__		):
      quantum_circuit.cp(np.pi / 2 ** (counter - j)   ,       lowercase__   ,       lowercase__		)

  for k in range(number_of_qubits // 2		):
    quantum_circuit.swap(lowercase__   ,       number_of_qubits - k - 1		)

  # measure all the qubits
  quantum_circuit.measure(lowercase__   ,       lowercase__		)
  # simulate with 10000 shots
  UpperCAmelCase__      :					Union[str, Any]				       =							Aer.get_backend("qasm_simulator"		)
  UpperCAmelCase__      :					Optional[int]				       =							execute(lowercase__   ,       lowercase__   ,       shots=1_0_0_0_0		)

  return job.result().get_counts(lowercase__		)


if __name__ == "__main__":
      print(
          F'Total count for quantum fourier transform state is: \
    {quantum_fourier_transform(3)}'
      )



