(self)
| 106 | ) |
| 107 | |
| 108 | def process(self): |
| 109 | # graph |
| 110 | coo_adj = sp.load_npz( |
| 111 | os.path.join( |
| 112 | self.raw_path, "reddit{}_graph.npz".format(self._self_loop_str) |
| 113 | ) |
| 114 | ) |
| 115 | self._graph = from_scipy(coo_adj) |
| 116 | # features and labels |
| 117 | reddit_data = np.load(os.path.join(self.raw_path, "reddit_data.npz")) |
| 118 | features = reddit_data["feature"] |
| 119 | labels = reddit_data["label"] |
| 120 | # tarin/val/test indices |
| 121 | node_types = reddit_data["node_types"] |
| 122 | train_mask = node_types == 1 |
| 123 | val_mask = node_types == 2 |
| 124 | test_mask = node_types == 3 |
| 125 | self._graph.ndata["train_mask"] = generate_mask_tensor(train_mask) |
| 126 | self._graph.ndata["val_mask"] = generate_mask_tensor(val_mask) |
| 127 | self._graph.ndata["test_mask"] = generate_mask_tensor(test_mask) |
| 128 | self._graph.ndata["feat"] = F.tensor( |
| 129 | features, dtype=F.data_type_dict["float32"] |
| 130 | ) |
| 131 | self._graph.ndata["label"] = F.tensor( |
| 132 | labels, dtype=F.data_type_dict["int64"] |
| 133 | ) |
| 134 | self._graph = reorder_graph( |
| 135 | self._graph, |
| 136 | node_permute_algo="rcmk", |
| 137 | edge_permute_algo="dst", |
| 138 | store_ids=False, |
| 139 | ) |
| 140 | |
| 141 | self._print_info() |
| 142 | |
| 143 | def has_cache(self): |
| 144 | graph_path = os.path.join(self.save_path, "dgl_graph.bin") |
nothing calls this directly
no test coverage detected