code: def __init__(self, n_features, n_hidden, n_classes):
      # Overriding initial class
      super(LSTM, self).__init__()
  
      # Saving number of hidden units as a property
      self.n_hidden = n_hidden
  
      # Creates LSTM cell
      self.lstm = torch.nn.LSTM(n_features, n_hidden)
  
      # Creates linear layer
      self.linear = torch.nn.Linear(n_hidden, n_classes, bias=False)
  
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 1 to create a new LSTM object from inherited base classes: torch.nn with example: obj = LSTM(n_features, n_hidden, n_classes)