INNER CODE UNIT · Python

loss

joeddav/devol · devol/devol.py:203

        loss = log_loss(np.concatenate(([1], np.zeros(n - 1))), np.ones(n) / n)
        accuracy = 1 / n
        gc.collect()

        if K.backend() == 'tensorflow':
            K.clear_session()
            tf.reset_default_graph()

        print('An error occurred and the model could not train:')
        print(error)
        print(('Model assigned poor score. Please ensure that your model'
               'constraints live within your computational resources.'))
        return loss, accuracy

    def _evaluate_population(self, members, epochs, fitness, igen, ngen):
        fit = []
        for imem, mem in enumerate(members):
            self._print_evaluation(imem, len(members), igen, ngen)

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