def build(self, graph=None, optimizer=None):
    """
    Creates model graph and groups important variables into named collections.
    """
    if graph is None:
        graph = tf.Graph()
    with graph.as_default():
        inputs = create_inputs()
        logits = build_model(
            inputs=inputs.x,
            layers=self.hidden_layers,
            n_outputs=self.n_classes,
            activation=self.activation)
        training_op, metrics = create_optimizer(
            labels=inputs.y,
            logits=logits,
            opt_cls=optimizer)
        add_to_collection('inputs', *inputs)
        add_to_collection('metrics', *metrics)
        add_to_collection('training', logits, training_op)
    self._graph = graph