Closed kevinkle closed 5 years ago
Looks like diffpool/load_data.py returns a list of Networkx graphs, we can prob do this ourselves and provide and abstraction around each list entry, loading them into ram as needed
(venv) kevin@phac5021225:~/diffpool$ python -m train --bmname=KMERS --assign-ratio=0.1 --hidden-dim=30 --output-dim=30 --cuda=0 --num-classes=6 --method=soft-assign --benchmark-iterations=1
Remove existing log dir: log/KMERS_soft-assign_l3x1_ar10_h30_o30
CUDA 0
Traceback (most recent call last):
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/kevin/diffpool/train.py", line 665, in <module>
main()
File "/home/kevin/diffpool/train.py", line 653, in main
iterations=prog_args.benchmark_iterations)
File "/home/kevin/diffpool/train.py", line 487, in benchmark_task_val
graphs = load_data.read_graphfile(args.datadir, args.bmname, max_nodes=args.max_nodes)
File "/home/kevin/diffpool/load_data.py", line 22, in read_graphfile
graph_indic[i]=int(line)
MemoryError
Even when we bump swap to 240GB
Should address #51 instead, closing