@mcahny @SeokjuLee
I got the first step, 1) Compile Resample2d, Correlation dependencies, complete by using the versions from the flownet2 repo, but can't seem to get the demo_vi.py script to run.
It makes it to line 162, where the following line produces a segmentation fault:
outputs, , , , = model(maskedinputs, masks_, lstm_state, prev_feed, t)
I've checked the values of the input variables, where t=0 (first frame), lstm_state=None, and the other three tensors have the following shapes:
maskedinputs.shape = torch.Size([1, 3, 5, 512, 512])
masks_.shape = torch.Size([1, 1, 5, 512, 512])
prev_feed.shape = torch.Size([1, 5, 512, 512])
I could also print the model structure if that helps.
My version of torch is 1.0.0, and CUDA is 10.0. Not sure if these versions could be the issue...
@mcahny @SeokjuLee I got the first step, 1) Compile Resample2d, Correlation dependencies, complete by using the versions from the flownet2 repo, but can't seem to get the demo_vi.py script to run.
It makes it to line 162, where the following line produces a segmentation fault: outputs, , , , = model(maskedinputs, masks_, lstm_state, prev_feed, t) I've checked the values of the input variables, where t=0 (first frame), lstm_state=None, and the other three tensors have the following shapes: maskedinputs.shape = torch.Size([1, 3, 5, 512, 512]) masks_.shape = torch.Size([1, 1, 5, 512, 512]) prev_feed.shape = torch.Size([1, 5, 512, 512])
I could also print the model structure if that helps.
My version of torch is 1.0.0, and CUDA is 10.0. Not sure if these versions could be the issue...