Hello!
First of all, thank you very much for making this work available!
I'm trying to use the code but having some trouble making it work.
First, I tried to install it by following the instructions on my MacOS machine, but then I found out that the environment needed to be Linux.
Then, I tried to install it on a Linux machine, but then found out that it requires a specific CUDA:
Traceback (most recent call last):
File "run_eval.py", line 262, in <module>
gamma=gamma, train_lr=train_lr, adamw=adamw, rescale=rescale, round2=False, decode_termini=decode_termini)
File "run_eval.py", line 194, in iterative_inference
gen_xyzs = run_inference(trainer, data_name=test_iter_prefix, folder_name=test_save_dir, batch_size=5000)
File "/home/diego/bkp.bmp/DiAMoNDBack/scripts/utils.py", line 442, in run_inference
trainer.op_number, batch_size=n, samples = next(sample_dl).cuda()[:n, :]), batches))
File "/home/diego/bkp.bmp/DiAMoNDBack/scripts/utils.py", line 442, in <lambda>
trainer.op_number, batch_size=n, samples = next(sample_dl).cuda()[:n, :]), batches))
File "/home/diego/.local/conda/envs/diffback/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
return func(*args, **kwargs)
File "../denoising_diffusion_pytorch/denoising_diffusion_pytorch_backmap_combined.py", line 702, in sample
return self.p_sample_loop((batch_size, 1, op_number), samples)
File "/home/diego/.local/conda/envs/diffback/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
return func(*args, **kwargs)
File "../denoising_diffusion_pytorch/denoising_diffusion_pytorch_backmap_combined.py", line 655, in p_sample_loop
state = torch.randn(shape, device=device)
RuntimeError: CUDA error: no kernel image is available for execution on the device
I wonder if you could update the conda environment script, make available a CPU version, or at least write down a list of minimum requirements that are needed to try/test/reproduce the work.
Thank you!
Hello!
First of all, thank you very much for making this work available!
I'm trying to use the code but having some trouble making it work.
First, I tried to install it by following the instructions on my MacOS machine, but then I found out that the environment needed to be Linux.
Then, I tried to install it on a Linux machine, but then found out that it requires a specific CUDA:
I wonder if you could update the conda environment script, make available a CPU version, or at least write down a list of minimum requirements that are needed to try/test/reproduce the work.
Thank you!