import dgl import torch as th from dgl.data.utils import save_graphsg1 = dgl.DGLGraph() g1.add_nodes(3) g1.add_edges([0, 0, 0, 1, 1, 2], [0, 1, 2, 1, 2, 2]) g1.ndata["x"] = th.ones(3, 5) # 3個節(jié)點的embedding g1.edata['y'] = th.zeros(6, 5) # 6條邊的embedding # 補充：添加邊的方式 # g1.add_edges(th.tensor([3, 4, 5]), 1) # three edges: 3->1, 4->1, 5->1 # g1.add_edges(4, [7, 8, 9]) # three edges: 4->7, 4->8, 4->9 # g1.add_edges([1, 2, 3], [3, 4, 5]) # three edges: 1->3, 2->4, 3->5g2 = dgl.DGLGraph() g2.add_nodes(3) g2.add_edges([0, 1, 2], [1, 2, 1]) g2.edata["e"] = th.ones(3, 4)graph_labels = {"graph_sizes": th.tensor([3, 3])}save_graphs("data/try1.bin", [g1, g2], graph_labels) from dgl.data.utils import load_graphs from dgl.data.utils import load_labels# glist, label_dict = load_graphs("data/small.bin") # glist will be [g1, g2] glist, label_dict = load_graphs("data/try1.bin", [0]) # glist will be [g1] graph_sizes = load_labels("data/try1.bin")print(glist) # [DGLGraph(num_nodes=3, num_edges=6, # ndata_schemes={'x': Scheme(shape=(5,), dtype=torch.float32)} # edata_schemes={'y': Scheme(shape=(5,), dtype=torch.float32)})] print(label_dict) # {'graph_sizes': tensor([3, 3])} print(graph_sizes) # {'graph_sizes': tensor([3, 3])} 創(chuàng)作挑戰(zhàn)賽新人創(chuàng)作獎勵來咯，堅持創(chuàng)作打卡瓜分現(xiàn)金大獎

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