def minus_initialize(node: Node, x=None, **kwargs): node.set_input_dim(x.shape[1]) node.set_output_dim(x.shape[1]) node.set_param("c", 1)
def unsupervised_backward(node: Node, X=None, Y=None): b = node.get_buffer("b") node.set_param("b", np.array(b).copy())
def on_train(node: Node, x, y=None): if y is not None: node.set_param("b", node.b + np.mean(x + y)) else: node.set_param("b", node.b + np.mean(x))
def off_backward_basic(node: Node, X=None, Y=None): b = np.mean(node._X) node.set_param("b", np.array(b).copy())