Datasets:
File size: 1,495 Bytes
5447dba 5e38d1a 5447dba 5e38d1a 5447dba 5e38d1a 5447dba | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | import duckdb
import torch
from torch_geometric.data import Data
from torch_geometric.data.data import DataEdgeAttr, DataTensorAttr
from torch_geometric.data.storage import BaseStorage, EdgeStorage, GlobalStorage
from torch_geometric.utils import is_undirected
from paths import DB_PATH, GRAPH_PATH
PATH = GRAPH_PATH
# torch>=2.6 defaults to weights_only=True; allowlist PyG's classes to keep it on.
torch.serialization.add_safe_globals(
[Data, DataEdgeAttr, DataTensorAttr, BaseStorage, EdgeStorage, GlobalStorage]
)
data = torch.load(PATH, weights_only=True)
print(data)
print("validate():", data.validate())
# is_undirected with edge_attr also requires the attrs to match on reversed pairs
print("is_undirected (attr-aware):",
is_undirected(data.edge_index, data.edge_attr, num_nodes=data.num_nodes))
# Round-trip three edges back against the source table.
con = duckdb.connect(DB_PATH, read_only=True)
print("\nround-trip check (saved value vs. table value):")
for i in (0, 1_000_000, 5_418_417):
s, t = data.edge_index[:, i].tolist()
a, b = data.node_id[s], data.node_id[t]
saved = data.edge_attr[i].tolist()
row = con.execute(
"""SELECT OddsRatio_log2, ChiTestsPValue FROM edge_ML_expected_ge5
WHERE (start_id = ? AND end_id = ?) OR (start_id = ? AND end_id = ?)""",
[a, b, b, a],
).fetchone()
print(f" col {i}: {a} <-> {b}")
print(f" saved={saved}")
print(f" table={list(row)} match={saved == list(row)}")
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