

"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase					:     Any				 =		logging.get_logger(__name__)

_lowercase					:     List[str]				 =		{
    'google/vit-base-patch16-224': 'https://huggingface.co/vit-base-patch16-224/resolve/main/config.json',
    # See all ViT models at https://huggingface.co/models?filter=vit
}
class 			_UpperCAmelCase					(				__UpperCAmelCase    ):
	a__						:      str						       = "vit"



	def __init__(   self			:    Dict       ,  _lowercase			:    Optional[int]=7_68       ,  _lowercase			:    Dict=12       ,  _lowercase			:    Tuple=12       ,  _lowercase			:    List[Any]=30_72       ,  _lowercase			:    Any="gelu"       ,  _lowercase			:    Tuple=0.0       ,  _lowercase			:    Any=0.0       ,  _lowercase			:    int=0.02       ,  _lowercase			:    Tuple=1E-12       ,  _lowercase			:    Optional[Any]=2_24       ,  _lowercase			:    Optional[int]=16       ,  _lowercase			:    List[Any]=3       ,  _lowercase			:    List[str]=True       ,  _lowercase			:    List[str]=16       ,  **_lowercase			:    List[str]       ,  ):
		super().__init__(**UpperCamelCase__		)

		__UpperCAmelCase							=      hidden_size
		__UpperCAmelCase							=      num_hidden_layers
		__UpperCAmelCase							=      num_attention_heads
		__UpperCAmelCase							=      intermediate_size
		__UpperCAmelCase							=      hidden_act
		__UpperCAmelCase							=      hidden_dropout_prob
		__UpperCAmelCase							=      attention_probs_dropout_prob
		__UpperCAmelCase							=      initializer_range
		__UpperCAmelCase							=      layer_norm_eps
		__UpperCAmelCase							=      image_size
		__UpperCAmelCase							=      patch_size
		__UpperCAmelCase							=      num_channels
		__UpperCAmelCase							=      qkv_bias
		__UpperCAmelCase							=      encoder_stride






class 			_UpperCAmelCase					(				__UpperCAmelCase    ):
	a__						:      Any						       = version.parse("1.11"    )



	@property
	def     a   (   self			:    Optional[Any]		):
		return OrderedDict(
		    [
		        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
		    ]		)



	@property
	def     a   (   self			:    Dict		):
		return 1E-4






import math

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





def __UpperCamelCase			(       _A = 3  ):
						if isinstance(_A ,  _A  ):
												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(_A  ) != 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).'''  )

						lowerCAmelCase_      			=  QuantumRegister(_A ,  '''qr'''  )
						lowerCAmelCase_      			=  ClassicalRegister(_A ,  '''cr'''  )

						lowerCAmelCase_      			=  QuantumCircuit(_A ,  _A  )

						lowerCAmelCase_      			=  number_of_qubits

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

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

						# measure all the qubits
						quantum_circuit.measure(_A ,  _A  )
						# simulate with 10000 shots
						lowerCAmelCase_      			=  Aer.get_backend('''qasm_simulator'''  )
						lowerCAmelCase_      			=  execute(_A ,  _A ,  shots=10000  )

						return job.result().get_counts(_A  )


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




