



import math

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




def 	UpperCAmelCase   (						_lowerCamelCase = 3    ):
			if isinstance(_lowerCamelCase ,    _lowerCamelCase    ):
						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(_lowerCamelCase    ) != 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)."    )

			A							:					Union[str, Any]              =						QuantumRegister(_lowerCamelCase ,    "qr"    )
			A							:					int              =						ClassicalRegister(_lowerCamelCase ,    "cr"    )

			A							:					Optional[Any]              =						QuantumCircuit(_lowerCamelCase ,    _lowerCamelCase    )

			A							:					List[str]              =						number_of_qubits

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

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

			# measure all the qubits
			quantum_circuit.measure(_lowerCamelCase ,    _lowerCamelCase    )
			# simulate with 10000 shots
			A							:					List[Any]              =						Aer.get_backend("qasm_simulator"    )
			A							:					Tuple              =						execute(_lowerCamelCase ,    _lowerCamelCase ,    shots=1_0000    )

			return job.result().get_counts(_lowerCamelCase    )


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




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE           =  {
    """configuration_instructblip""": [
        """INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """InstructBlipConfig""",
        """InstructBlipQFormerConfig""",
        """InstructBlipVisionConfig""",
    ],
    """processing_instructblip""": ["""InstructBlipProcessor"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE           =  [
							    """INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """InstructBlipQFormerModel""",
							    """InstructBlipPreTrainedModel""",
							    """InstructBlipForConditionalGeneration""",
							    """InstructBlipVisionModel""",
							]

if TYPE_CHECKING:
							from .configuration_instructblip import (
							    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    InstructBlipConfig,
							    InstructBlipQFormerConfig,
							    InstructBlipVisionConfig,
							)
							from .processing_instructblip import InstructBlipProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_instructblip import (
														    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    InstructBlipForConditionalGeneration,
														    InstructBlipPreTrainedModel,
														    InstructBlipQFormerModel,
														    InstructBlipVisionModel,
														)

else:
							import sys

							__SCREAMING_SNAKE_CASE           =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)