





import math

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






def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							int = 3    ):
		if isinstance(UpperCamelCase__					,   UpperCamelCase__    ):
				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(UpperCamelCase__    ) != number_of_qubits:
				raise ValueError("""number of qubits must be exact integer."""    )
		if number_of_qubits > 10:
				raise ValueError("""number of qubits too large to simulate(>10)."""    )

		SCREAMING_SNAKE_CASE__			=      QuantumRegister(UpperCamelCase__					,   """qr"""    )
		SCREAMING_SNAKE_CASE__			=      ClassicalRegister(UpperCamelCase__					,   """cr"""    )

		SCREAMING_SNAKE_CASE__			=      QuantumCircuit(UpperCamelCase__					,   UpperCamelCase__    )

		SCREAMING_SNAKE_CASE__			=      number_of_qubits

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

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

		# measure all the qubits
		quantum_circuit.measure(UpperCamelCase__					,   UpperCamelCase__    )
		# simulate with 10000 shots
		SCREAMING_SNAKE_CASE__			=      Aer.get_backend("""qasm_simulator"""    )
		SCREAMING_SNAKE_CASE__			=      execute(UpperCamelCase__					,   UpperCamelCase__					,   shots=10_000    )

		return job.result().get_counts(UpperCamelCase__    )


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






import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate




@dataclass(frozen=UpperCamelCase__    )
class   UpperCamelCase_       (     UpperCamelCase__    ):
							lowerCamelCase_           =					field(default="image-classification"				,  metadata={"include_in_asdict_even_if_is_default": True}    )
							lowerCamelCase_           =					Features({"image": Image()}    )
							lowerCamelCase_           =					Features({"labels": ClassLabel}    )
							lowerCamelCase_           =					"image"
							lowerCamelCase_           =					"labels"


							def      _snake_case  (							self    :List[str]							,				__A    :Tuple		)   ->   Tuple:



									"""simple docstring"""



									if self.label_column not in features:
											raise ValueError(f'''Column {self.label_column} is not present in features.'''		)
									if not isinstance(features[self.label_column]							,				__A		):
											raise ValueError(f'''Column {self.label_column} is not a ClassLabel.'''		)
									SCREAMING_SNAKE_CASE__			=      copy.deepcopy(self		)
									SCREAMING_SNAKE_CASE__			=      self.label_schema.copy()
									SCREAMING_SNAKE_CASE__			=      features[self.label_column]
									SCREAMING_SNAKE_CASE__			=      label_schema
									return task_template


							@property
							def      _snake_case  (							self    :Dict		)   ->   Dict[str, str]:



									"""simple docstring"""



									return {
									    self.image_column: "image",
									    self.label_column: "labels",
									}