utils

Module Contents

Classes

ArgClass

Functions

build_args_from_dict(dic)
add_remaining_self_loops(edge_index, edge_weight, fill_value, num_nodes)
row_normalization(num_nodes, edge_index, edge_weight=None)
symmetric_normalization(num_nodes, edge_index, edge_weight=None)
spmm(indices, values, b)	Args:
spmm_adj(indices, values, shape, b)
edge_softmax(indices, values, shape)	Args:
mul_edge_softmax(indices, values, shape)	Args:
remove_self_loops(indices)

class utils.ArgClass

Bases: object

utils.build_args_from_dict(dic)

utils.add_remaining_self_loops(edge_index, edge_weight, fill_value, num_nodes)

utils.row_normalization(num_nodes, edge_index, edge_weight=None)

utils.symmetric_normalization(num_nodes, edge_index, edge_weight=None)

utils.spmm(indices, values, b)

Args: indices : Tensor, shape=(2, E) values : Tensor, shape=(E,) shape : tuple(int ,int) b : Tensor, shape=(N, )

utils.spmm_adj(indices, values, shape, b)

utils.edge_softmax(indices, values, shape)

Args:

indices: Tensor, shape=(2, E) values: Tensor, shape=(N,) shape: tuple(int, int)

Returns:

Softmax values of edge values for nodes

utils.mul_edge_softmax(indices, values, shape)

Args:

indices: Tensor, shape=(2, E) values: Tensor, shape=(E, d) shape: tuple(int, int)

Returns:

Softmax values of multi-dimension edge values for nodes

utils.remove_self_loops(indices)

utils.args