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vijaydwivedi75 / lrgb

Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
MIT License
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Support for PyG later than 2.0.2 #6

Open HaniItani opened 1 year ago

HaniItani commented 1 year ago

Hello,

Any plans for supporting later releases of PyG (e.g. 2.1)? It's a fairly new benchmark and it's not compatible with the newest PyG releases out of the box.

Best regards, Hani

rampasek commented 1 year ago

Hi,

You can also access it in GraphGPS that has been updated to PyG 2.0.4 compatibility: https://github.com/rampasek/GraphGPS

I will refactor GraphGPS to PyG 2.1 in the future. However the dataset loaders themselves should be perfectly functional in your PyG 2.1 codebase as they are.

Best, Ladislav

GARV-k commented 4 weeks ago

I am also using PyG >2.1 and in the main.py file, I just imported the OptimConfig and SchedulerConfig from torch_geometric.graphgym.optim. it gives a error : Traceback (most recent call last): File "/home/iplab/garv_iit-bhu/GraphTransformer/lrgb/main.py", line 178, in optimizer = create_optimizer(model.parameters(), File "/home/iplab/anaconda3/envs/lrgb/lib/python3.9/site-packages/torch_geometric/graphgym/optim.py", line 38, in create_optimizer return from_config(func)(params, cfg=cfg) File "/home/iplab/anaconda3/envs/lrgb/lib/python3.9/site-packages/torch_geometric/graphgym/config.py", line 578, in wrapper raise ValueError(f"'cfg.{arg_name}' undefined") ValueError: 'cfg.optimizer_config' undefined