I’m using fastai 0.7 and 1.0 with ubuntu 18. Everything is working okay.
I can’t believe I’m saying this, but ubuntu 18 has a “friendly UI” or atleast compared to 16.
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@bholmer It’s just as easy as a pip install.
Please check the steps for AWS in the wiki. You’ll just need to follow those.
If you’re going through the ML mooc, you could build a 2nd environment to install fastai_v1
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Is there a stable docker image for the course? I’ve tried to install everything from scratch on PC, but failed miserable and wasted two weekends in the process, but I know how to use docker 
During class, do we know if it’s better to stick to the development version of fast.ai (in git repo) or use the released version?
I had problems running the examples until I switched to the development version, and I am fine with that, but I think it would be good to know what the recommended approach is.
We’ll be using conda for the class, not development version. But until Monday you might find dev version best if you’re trying to follow along.
Setup Fastai v1 on Paperspace
Hello everyone!
I’ve create a small step-by-step guido to setup and configure the new fast.ai v1 version on the already available fast.ai paperspace template.
Please check the guide on https://gist.github.com/tcvieira/d29d38068a6cd2c455baaaf0d183534b
I’d appreciate all feedbacks!
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On day to day basis, is it enough to run :
conda update -c fastai fastai
conda update -c fastai torchvision-nightly
to update ones local install? If so perhaps this should be added to the install instructions.
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Great! Thanks. I’ll try it out tonight.
BTW, will v0.7 still be usable after installing v1.0?
(I noticed that @init_27 says he has both 0.7 and 1.0 working).
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you need to set up different conda environments for the 2 versions, then it is no problem.
you cannot have 2 versions of fastai in the same env at the same time. you have to switch between environments using conda activate fastai and conda activate fastaiv1 (just examples)
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Hello, I just updated the wiki guide for implementing Fastai v1 in Google Colab
Please checkout, everything is working fine!
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LIke @marcmuc said, you can have both on the same machine but in differente enviroments. That’s why in my step by step I’ve created another env for v1.
The only problem I’ve found was that when switching env, sometimes, my Jupyter config gets messy. So, I’ve got to reconfigure it.
Update on my help request to Paperspace - they promise to have a fast.ai v1.0 template ready by the start of class. That will be useful for people new to Paperspace.
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Please, feel free to add a note to the wiki. Note, anyone can edit the above wiki. I generally do some policing to reduce redundant points from being added.
Will do!
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Binary Updates. I’ve installed the binary version 1.0 on my local UBUNTU 16.04 LTS using conda and ‘conda install …’ and it seems to be working fine, I used the binary instructions and had only one minor problem with the source path. My bash was looking in the wrong place so ‘source activate’ wasn’t working. This was easily fixed by editing my .bashrc file and commenting out the added export PATH line. In my last class last iteration (Part 2,V2), I would just do a git pull, and get new source. Since I’m now using Conda, my questions are:
- How often do the binaries change?
- How do I update my machine when the do?
Thanks
Some of you may have a MSDN account and will have access to an Azure subscription (like me). You can use Azure to setup the VM. I found a nice guide to set this up -
Make sure to select Linux in place of Windows.
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In case you didn’t get an answer:
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I configured the Azure Ubuntu 16.04 Deep Learning Virtual Machine for FastAI v1.0 with no issues - just followed the guidance for Part 1 v3 config.
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