code: def raw_fitness(self, X, y, sample_weight):
          
          y_pred = self.execute(X)
          if self.transformer:
              y_pred = self.transformer(y_pred)
          raw_fitness = self.metric(y, y_pred, sample_weight)
  
          return raw_fitness
docs: Evaluate the raw fitness of the program according to X, y.
  
          Parameters
          ----------
          X : {array-like}, shape = [n_samples, n_features]
              Training vectors, where n_samples is the number of samples and
              n_features is the number of features.
  
          y : array-like, shape = [n_samples]
              Target values.
  
          sample_weight : array-like, shape = [n_samples]
              Weights applied to individual samples.
  
          Returns
          -------
          raw_fitness : float
              The raw fitness of the program.