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View Code? Open in Web Editor NEWScalable and privacy-enhanced graph generative models for benchmark graph neural networks
Home Page: https://arxiv.org/abs/2207.04396
Scalable and privacy-enhanced graph generative models for benchmark graph neural networks
Home Page: https://arxiv.org/abs/2207.04396
Steps to reproduce the error from a Google Colab:
!python --version
>>> Python 3.7.15
!git clone https://github.com/minjiyoon/CGT.git
import os
os.chdir('CGT')
!python -m pip install k-means-constrained networkx jinja2
!python -m pip install --force-reinstall ortools==9.3.10497
!python test.py
produced the output:
original sampling time: 1.051
original evaluation time: 39.548, acc: [0.83785439 0.83987465 0.83943878 0.81844264]
Clustering time: 12.330
tcmalloc: large alloc 2934784000 bytes == 0x10646000 @ 0x7fb5c10cf1e7 0x7fb5bea200ce 0x7fb5bea76cf5 0x7fb5bea76e08 0x7fb5beb360f4 0x7fb5beb3930c 0x7fb5becc03ac 0x7fb5becc0e10 0x5917ee 0x591ac9 0x7fb5beb402a6 0x4e50c9 0x50d124 0x58fd37 0x50c4fc 0x5b4ee6 0x58ff2e 0x50d482 0x58fd37 0x50c4fc 0x5b4ee6 0x6005a3 0x607796 0x60785c 0x60a436 0x64db82 0x64dd2e 0x7fb5c0cccc87 0x5b636a
tcmalloc: large alloc 2934784000 bytes == 0x10646000 @ 0x7fb5c10cf1e7 0x7fb5bea200ce 0x7fb5bea76cf5 0x7fb5bea76e08 0x7fb5beb360f4 0x7fb5beb3930c 0x7fb5becc03ac 0x7fb5becc0e10 0x5917ee 0x591ac9 0x7fb5beb402a6 0x4e50c9 0x50d124 0x58fd37 0x50c4fc 0x5b4ee6 0x58ff2e 0x50d482 0x58fd37 0x50c4fc 0x5b4ee6 0x6005a3 0x607796 0x60785c 0x60a436 0x64db82 0x64dd2e 0x7fb5c0cccc87 0x5b636a
tcmalloc: large alloc 2077827072 bytes == 0x104ae000 @ 0x7fb5c10cf1e7 0x7fb5bea200ce 0x7fb5bea76cf5 0x7fb5bea76e08 0x7fb5beb360f4 0x7fb5beb3930c 0x7fb5becc03ac 0x7fb5becc0e10 0x5917ee 0x591ac9 0x7fb5beb402a6 0x4e50c9 0x50d124 0x58fd37 0x50c4fc 0x5b4ee6 0x58ff2e 0x50d482 0x58fd37 0x50c4fc 0x5b4ee6 0x6005a3 0x607796 0x60785c 0x60a436 0x64db82 0x64dd2e 0x7fb5c0cccc87 0x5b636a
Clustered graph generation time: 4.611
[GPT] data preparation time: 0.924
Traceback (most recent call last):
File "test.py", line 110, in <module>
main()
File "test.py", line 71, in main
generated_list, cluster_center = gpt.run(args, adj, feat, label, ids, train_name=args.gpt_train_name)
File "/content/CGT/generator/gpt/gpt.py", line 103, in run
model_name, model, comp_ids = train(args, graphs, cluster_ids, labels, split_ids, train_name, split_name=split)
File "/content/CGT/generator/gpt/gpt.py", line 52, in train
trainer.train(split_name)
File "/content/CGT/generator/gpt/trainer.py", line 116, in train
run_epoch('train')
File "/content/CGT/generator/gpt/trainer.py", line 79, in run_epoch
logits, loss = model(x, lbl, y)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/content/CGT/generator/gpt/model.py", line 248, in forward
targets = targets.view(-1)
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.
Could you provide more accurate instructions to reproduce your code?
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