code: def predict(model, x_val):
      # Declares validation variable
      x = Variable(x_val, requires_grad=False)
  
      # Performs backward pass with this variable
      output = model.forward(x)
  
      # Gets the index of the prediction
      y_val = output.data.numpy().argmax(axis=1)
  
      return y_val
  
file_path: opytimizer/examples/integrations/pytorch/lstm.py
imports: import numpy
  import torch
  from sklearn.datasets import load_digits
  from sklearn.model_selection import train_test_split
  from torch import optim
  from torch.autograd import Variable
  from opytimizer import Opytimizer
  from opytimizer.core import Function
  from opytimizer.optimizers.swarm import PSO
  from opytimizer.spaces import SearchSpace
label_desc: Use image node_id 2 for calling a global function with example usage: predict(model, x_val) and returns: y_val