text: ### Acá definiremos el modelo Pytorch que usaremos.
  
  import torch
  import torch.nn as nn
  import torch.optim as optim
  from torch.nn import functional as F
  
  input_size = 4
  output_size = 3 #del target
  hidden_size = 30 #Nro de neuronas por layer.
  
  class ModeloIris(nn.Module):
      
      def __init__(self):
          super(ModeloIris, self).__init__()
          self.layer1 = nn.Linear(input_size, hidden_size)
          self.layer2 = nn.Linear(hidden_size, hidden_size)
          self.layer3 = nn.Linear(hidden_size, hidden_size)
          self.layerOut = nn.Linear(hidden_size, output_size)
          
      def forward(self, X):
          X = torch.sigmoid((self.layer1(X)))
          X = torch.sigmoid((self.layer2(X)))
          X = torch.sigmoid((self.layer3(X)))
          X = self.layerOut(X)
          
          return F.log_softmax(X, dim =-1)