-
Notifications
You must be signed in to change notification settings - Fork 18
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Inference.py error #4
Comments
I got the same error, I suspect is it related to dependencies/versioning. I'm not able to solve this issue yet, please keep us updated if you got around it! |
I agree with dependencies/versioning part. I got this error on both pycharm and colab. In pycharm, I changed the source code of torch-geometric but then I got AttributeError: 'GlobalStorage' object has no attribute 'slices' error. I think it is related to multi-gpu thing, I can't figure out how to run this with CPU. In colab I am trying to figure out something else but I have no idea for now. |
Thanks for the update @musdfakoc, I'm trying at my end, too. Lets keep this thread active. |
Hi, |
hi again, how are we supposed to plot the json outputs? thanks already |
hi, thanks for the great work here. I tried to run the pretrained model but I get this error:
Using GPU 0
['Tesla K80']
{'cuda': 0, 'comment': 0, 'batch_size': 8, 'train_data_dir': '/content/drive/MyDrive/Colab Notebooks/Building-GAN/Data/6types-processed_data', 'raw_dir': '/content/drive/MyDrive/Colab Notebooks/Building-GAN/Data/6types-raw_data', 'train_size': 96000, 'test_size': 4000, 'n_cpu': 8, 'variation_eval_id1': 96018, 'variation_eval_id2': 96010, 'variation_num': 25, 'latent_dim': 128, 'noise_dim': 32, 'program_layer': 4, 'voxel_layer': 12, 'gan_loss': 'WGANGP', 'gp_lambda': 10.0, 'lp_weight': 0.0, 'tr_weight': 0.0, 'far_weight': 0.0, 'lp_sample_size': 20, 'lp_similarity_fun': 'cos', 'lp_loss_fun': 'hinge', 'lp_hinge_margin': 1.0, 'n_epochs': 1000, 'n_critic_d': 1, 'n_critic_g': 5, 'n_critic_p': 5, 'plot_period': 10, 'eval_period': 20, 'g_lr': 0.0001, 'd_lr': 0.0001, 'b1': 0.5, 'b2': 0.999}
Total 120000 data: 96000 train / 4000 test
TypeError Traceback (most recent call last)
in ()
59 variation_test_data1 = torch.load(os.path.join(args.train_data_dir, data_fname_list[args.variation_eval_id1]))
60 variation_test_data2 = torch.load(os.path.join(args.train_data_dir, data_fname_list[args.variation_eval_id2]))
---> 61 variation_test_batch1 = Batch.from_data_list([variation_test_data1 for _ in range(args.variation_num)], follow_batch)
62 variation_test_batch2 = Batch.from_data_list([variation_test_data2 for _ in range(args.variation_num)], follow_batch)
63
2 frames
/usr/local/lib/python3.7/dist-packages/torch_geometric/data/collate.py in _collate(key, values, data_list, stores, increment)
135 # Concatenate a list of
torch.Tensor
along thecat_dim
.136 # NOTE: We need to take care of incrementing elements appropriately.
--> 137 cat_dim = data_list[0].cat_dim(key, elem, stores[0])
138 if cat_dim is None or elem.dim() == 0:
139 values = [value.unsqueeze(0) for value in values]
TypeError: cat_dim() takes 3 positional arguments but 4 were given
any idea how to solve this? I think this is about package versions. Can you provide some requirements.txt or something else?
The text was updated successfully, but these errors were encountered: