text: #Make the model now
  class PowerPredictor(nn.Module):
    def __init__(self,input_features,num_outputs,neuronslist):
      super().__init__()
      self.input_features = input_features
      self.num_outputs = num_outputs
      self.neuronslist = neuronslist
      '''Here,
      input_features : Number of different features in dataset
      num_outputs : Number of outputs
      neuronslist : List of number of hidden units per layer
                    (Since there are three layers so there will be three elements in this list'''
  
  
      self.linear1 = nn.Linear(self.input_features,self.neuronslist[0])
      self.act1 = nn.Softplus()
  
      self.linear3 = nn.Linear(self.neuronslist[0], self.neuronslist[1])
      self.act3 = nn.Softplus()
  
      self.linear6 = nn.Linear(self.neuronslist[1], self.num_outputs)
      self.act6 = nn.Softplus()
  
    def forward(self,x):
      out = self.act1(self.linear1(x))
      #out = self.act2(self.linear2(out))
      out = self.act3(self.linear3(out))
      #out = self.act4(self.linear4(out))
      #out = self.act5(self.linear5(out))
      out = self.act6(self.linear6(out))
      return out
  