Axis=0 for concat

        cost = L2Loss(in_layers=[label, regression])

        costs.append(cost)

    all_cost = Concat(in_layers=costs)

    all_cost = Concat(in_layers=costs, axis=0)

    self.weights = Weights(shape=(None, self.n_tasks))

    loss = WeightedError(in_layers=[all_cost, self.weights])

    self.set_loss(loss)

      for node in order:

        with tf.name_scope(node):

          node_layer = self.layers[node]

          print(node)

          node_layer.create_tensor(training=self._training_placeholder)

      self.built = True