def __init__(self, dataset, model, hidden_size, num_shuffle, seed, **model_args):
assert model == "from_numpy_graph"
dataset = create_graph_classification_dataset(dataset)
self.num_nodes = dataset.graph_labels.shape[0]
self.num_classes = dataset.num_labels
self.label_matrix = np.zeros((self.num_nodes, self.num_classes), dtype=int)
self.labels = dataset.graph_labels
self.model = build_model(model, hidden_size, **model_args)
self.hidden_size = hidden_size
self.num_shuffle = num_shuffle
self.seed = seed
def __init__(
self,
dataset,
rw_hops=64,
subgraph_size=64,
restart_prob=0.8,
positional_embedding_size=32,
step_dist=[1.0, 0.0, 0.0],
):
self.rw_hops = rw_hops
self.subgraph_size = subgraph_size
self.restart_prob = restart_prob
self.positional_embedding_size = positional_embedding_size
self.step_dist = step_dist
self.entire_graph = True
assert positional_embedding_size > 1
self.dataset = data_util.create_graph_classification_dataset(dataset)
self.graphs = self.dataset.graph_lists
self.length = len(self.graphs)
self.total = self.length
