




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


UpperCAmelCase_						=logging.get_logger(__name__)

UpperCAmelCase_						={
    """facebook/data2vec-vision-base-ft""": (
        """https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json"""
    ),
}


class 							__UpperCamelCase			( __UpperCAmelCase  ):





				'''simple docstring'''



				__a							: Optional[int]										="""data2vec-vision"""



				def __init__( self       , UpperCAmelCase_=7_68       , UpperCAmelCase_=12       , UpperCAmelCase_=12       , UpperCAmelCase_=30_72       , UpperCAmelCase_="gelu"       , UpperCAmelCase_=0.0       , UpperCAmelCase_=0.0       , UpperCAmelCase_=0.02       , UpperCAmelCase_=1E-1_2       , UpperCAmelCase_=2_24       , UpperCAmelCase_=16       , UpperCAmelCase_=3       , UpperCAmelCase_=False       , UpperCAmelCase_=False       , UpperCAmelCase_=False       , UpperCAmelCase_=False       , UpperCAmelCase_=0.1       , UpperCAmelCase_=0.1       , UpperCAmelCase_=True       , UpperCAmelCase_=[3, 5, 7, 11]       , UpperCAmelCase_=[1, 2, 3, 6]       , UpperCAmelCase_=True       , UpperCAmelCase_=0.4       , UpperCAmelCase_=2_56       , UpperCAmelCase_=1       , UpperCAmelCase_=False       , UpperCAmelCase_=2_55       , **UpperCAmelCase_       , ):
											super().__init__(**UpperCAmelCase_						)

											lowerCAmelCase   =		hidden_size
											lowerCAmelCase   =		num_hidden_layers
											lowerCAmelCase   =		num_attention_heads
											lowerCAmelCase   =		intermediate_size
											lowerCAmelCase   =		hidden_act
											lowerCAmelCase   =		hidden_dropout_prob
											lowerCAmelCase   =		attention_probs_dropout_prob
											lowerCAmelCase   =		initializer_range
											lowerCAmelCase   =		layer_norm_eps

											lowerCAmelCase   =		image_size
											lowerCAmelCase   =		patch_size
											lowerCAmelCase   =		num_channels
											lowerCAmelCase   =		use_mask_token
											lowerCAmelCase   =		use_absolute_position_embeddings
											lowerCAmelCase   =		use_relative_position_bias
											lowerCAmelCase   =		use_shared_relative_position_bias
											lowerCAmelCase   =		layer_scale_init_value
											lowerCAmelCase   =		drop_path_rate
											lowerCAmelCase   =		use_mean_pooling
											# decode head attributes (semantic segmentation)
											lowerCAmelCase   =		out_indices
											lowerCAmelCase   =		pool_scales
											# auxiliary head attributes (semantic segmentation)
											lowerCAmelCase   =		use_auxiliary_head
											lowerCAmelCase   =		auxiliary_loss_weight
											lowerCAmelCase   =		auxiliary_channels
											lowerCAmelCase   =		auxiliary_num_convs
											lowerCAmelCase   =		auxiliary_concat_input
											lowerCAmelCase   =		semantic_loss_ignore_index




class 							__UpperCamelCase			( __UpperCAmelCase  ):





				'''simple docstring'''



				__a							: Optional[Any]										=version.parse("""1.11"""  )



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






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









import math

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



def       UpperCAmelCase       (     _snake_case = 3							):
							if isinstance(_snake_case						, _snake_case							):
														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(_snake_case							) != 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(_snake_case						, '''qr'''							)
							lowerCAmelCase   =		ClassicalRegister(_snake_case						, '''cr'''							)

							lowerCAmelCase   =		QuantumCircuit(_snake_case						, _snake_case							)

							lowerCAmelCase   =		number_of_qubits

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

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

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

							return job.result().get_counts(_snake_case							)


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



