Great thanks. I can fix it so that the init isn’t slow any more (doing that now), but I suspect it’ll only push the issue to later… Can you try running this in a new notebook and tell me how long it takes? (It should be basically instant, but your profile suggests it’ll be slow):
import torch
for i in range(10): a=torch.tensor([1.,2.]).cuda()
Yes. It ran very quickly:
%time
import torch
for i in range(10): a=torch.tensor([1., 2.]).cuda()
CPU times: user 1 µs, sys: 0 ns, total: 1 µs
Wall time: 3.81 µs
I installed fastai through conda. Does changes pushed to the Github repo automatically update the conda packages? If not, what is the current best approach to have the latest version installed?
I wonder if Windows Subsystem for Linux could be used in the meantime
No. Use the ‘developer install’ from the bottom of the readme.
Unfortunately the windows subsystem for linux doesn’t give access to the GPU…
Quick questions:
Do you plan to release full-fledged documentation? If so, when?
FastaiV1 repository does actually include all the notebooks, which at a first glance seem to be identical to Fastai0.7 nbs. Can we use them with FastaiV1?
I’d really like to have V1 and V0.7 sitting together on my linux box. Should I expect issues about cuda and cudnn (different versions)?
The doc is fully released here. The notebooks are the ones from the old course, so they aren’t usable with v1 directly. You’ll have to wait for the new course to have compatible notebooks.
There’s no reason you can’t have v1 and v0.7 in different environments.
Been exploring fastai v1 a bit and it looks even greater than before! 1 quick question - with fastai v1, how do we do lr_find?
I tried learn.lr_find(), but after that learn.recorder.val_losses is an empty list, and learn.recorder.plot_losses() throws an exception, complaining no output activations
Thanks!
That’s great!
Has anyone built pytorch 1.0 on Windows and used it with Fastai?
Not that I know of. If someone has working wheels for pytorch 1.0 I’d like to have them too.
any ideas if we get to access the live lesson on youtube even if we don’t register? I don’t need the option for discussion though.
Not until the MOOC comes out.
thanks for the reply, Jeremy. I missed the registration for it. Any second opening? I’m reading the new examples and docs.fast.ai but would love to see you going through it.
No second opening, sorry.
Is the full code from https://www.fast.ai/2018/10/02/fastai-ai/ published somewhere?
It’s unclear to me where to find data_from_imagefolder. So a fully working example would be great.
