





"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__   	=	logging.get_logger(__name__)

lowerCAmelCase__   	=	{
    '''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
    '''uclanlp/visualbert-vqa-pre''': '''https://huggingface.co/uclanlp/visualbert-vqa-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-vqa-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-vqa-coco-pre/resolve/main/config.json'''
    ),
    '''uclanlp/visualbert-vcr''': '''https://huggingface.co/uclanlp/visualbert-vcr/resolve/main/config.json''',
    '''uclanlp/visualbert-vcr-pre''': '''https://huggingface.co/uclanlp/visualbert-vcr-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-vcr-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-vcr-coco-pre/resolve/main/config.json'''
    ),
    '''uclanlp/visualbert-nlvr2''': '''https://huggingface.co/uclanlp/visualbert-nlvr2/resolve/main/config.json''',
    '''uclanlp/visualbert-nlvr2-pre''': '''https://huggingface.co/uclanlp/visualbert-nlvr2-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-nlvr2-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-nlvr2-coco-pre/resolve/main/config.json'''
    )
    # See all VisualBERT models at https://huggingface.co/models?filter=visual_bert
}





class 				_lowerCamelCase					(				lowerCamelCase__       ):
						UpperCAmelCase_       =	'visual_bert'


						def __init__(self      ,							__a=3_05_22      ,							__a=7_68      ,							__a=5_12      ,							__a=12      ,							__a=12      ,							__a=30_72      ,							__a="gelu"      ,							__a=0.1      ,							__a=0.1      ,							__a=5_12      ,							__a=2      ,							__a=0.02      ,							__a=1e-1_2      ,							__a=False      ,							__a=True      ,							__a=1      ,							__a=0      ,							__a=2      ,							**__a      ,							)       ->      Optional[Any]:
								super().__init__(pad_token_id=lowercase_      ,							bos_token_id=lowercase_      ,							eos_token_id=lowercase_      ,							**lowercase_						)

								UpperCamelCase      =		vocab_size
								UpperCamelCase      =		max_position_embeddings
								UpperCamelCase      =		hidden_size
								UpperCamelCase      =		visual_embedding_dim
								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      =		type_vocab_size
								UpperCamelCase      =		layer_norm_eps
								UpperCamelCase      =		bypass_transformer
								UpperCamelCase      =		special_visual_initialize









import math

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




def 			UpperCAmelCase__				(			_A      : int = 3							):





  '''simple docstring'''







  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).'''							)

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

  a__  =QuantumCircuit(_A	,      _A							)

  a__  =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
  a__  =Aer.get_backend('''qasm_simulator'''							)
  a__  =execute(_A	,      _A	,      shots=1_00_00							)

  return job.result().get_counts(_A							)


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