def build_model(self, n_features, n_classes):
        """Create the computational graph.

        This graph is intented to be created for finetuning,
        i.e. after unsupervised pretraining.
        :param n_features: Number of features.
        :param n_classes: number of classes.
        :return: self
        """
        self._create_placeholders(n_features, n_classes)
        self._create_variables(n_features)

        next_train = self._create_encoding_layers()
        self.mod_y, _, _ = Layers.linear(next_train, n_classes)
        self.layer_nodes.append(self.mod_y)

        self.cost = self.loss.compile(self.mod_y, self.input_labels)
        self.train_step = self.trainer.compile(self.cost)
        self.accuracy = Evaluation.accuracy(self.mod_y, self.input_labels)
Create the computational graph.

        This graph is intented to be created for finetuning,
        i.e. after unsupervised pretraining.
        :param n_features: Number of features.
        :param n_classes: number of classes.
        :return: self