Yes all the same steps as before are required.
Hi, I’m going to sound like a meddling manager who knows nothing (mostly true…I haven’t even started the class yet!) but is there a list somewhere of major changes between 0.7 and v1? I’m just trying to think ahead: once I finish the course, what will I need to be able to transition to v1, and use it in real world applications?
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Hi,
Would it be possible for someone (with github access) to tag and cut a release right before the v1.0 migration happened. I see a tag from May '18 but a lot has happened since then.
Not entirely sure but this commit seems like a reasonable stopping point
Many thanks in advance
A
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Great idea! Do you happen to know the exact commands to do that, so I don’t have to go figure it out?
git tag -a v0.7 59caaaa -m "Preserving 0.7 state of fastai library pre-v1.0 release"
git push --tags origin master
the release will then have to be done via the github webinterface (or REST based client):
https://help.github.com/articles/creating-releases/
This is the easiest way, but means that the date of that tag will be the current day (day of the commit) and NOT in the past. This can be manipulated though if that is important to somebody, see answer below the one chosen as correct:
Best,
Marc
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Many thanks. I called it 0.7.2. It seems to have created a release automatically: https://github.com/fastai/fastai/releases
It’s based on the commit before I commented out the jupyter stuff (since that’ll be fixed upstream): https://github.com/fastai/fastai/commit/e85667cfae2e6873b1bb026195b5d09a74dfcff9
3 Likes
Thank you, @marcmuc. That’s handy.
BTW, perhaps what you shared about needing to make a release is no longer needed. At least, once I pushed the tag, github immediately created a release. i.e. no extra steps was necessary.
and I combined a bunch of answers to make a one-liner solution that sets the tag date to when it actually happened, uses annotated tag and requires no git checkout :
tag="v0.1.3" commit="8f33a878" bash -c 'GIT_COMMITTER_DATE="$(git show --format=%aD $commit)" git tag -a $tag -m $tag $commit'
git push --tags origin master
where tag is set to the desired tag string, and commit to the commit hash.
5 Likes
awesome one-liner, goes to my copy/paste cheat sheet 
1 Like
Hi all! Now that fastai 1 is out, I wrote a short post on medium about using fastai 1 on Colab. Please check out if you are interested!
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can you post the link to the colab notebook. Thanks!
Hi, sorry I forgot to put the link to my medium post! All my code is in screenshot if you read the medium post. Thanks!
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Hello, I’m new around here and have watched a few of the videos, am hooked, and I think what you’re up to here is amazing, so thank you!
I’ve got a question about the fastai library version. I’ve set up my own ubuntu dual-boot workspace, putting my 1080ti to more productive use than what I usually use it for… and have the old/0.7 version of the notebooks running smoothly. I’m sure that the general deep learning concepts from the now old version of the course are still just as valuable and I will go through them regardless, however I’m wondering about if at some point we can look forward to a new or updated version using the fastai 1.0 libray, considering it’s a from scratch rewrite? Do you think there is any harm at all in getting deep into the 0.7 course at this point? (just to be clear when I say old, I still mean the 2018 version, I say old because of the “old” wrapper version used in the course)
Yes, early 2019.
Still very useful - the concepts don’t change, and that’s what takes time to learn. Library changes are easy to learn.
1 Like
Thank you for your work!!
HI - thank you for all the work you have done. I am just starting and have seen the intro to Random Forests lesson 1. I am not sure how to proceed with library/version changes. I use the following code that I found in the forum to install fasai. Some of the libraries work, but I cannot get “from fastai.structured import *” (interested in the add_datepart function) to install. I see in the forum that the library has moved, but I am not sure what I need to do to access this “old” library.
#installs FastAI
#https://github.com/fastai/course-v3/blob/7dfe63de54daf2210f5b23f237e70ee246be5d0c/docs/google_colab_tutorial.md
from os.path import exists
from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag
platform = ‘{}{}-{}’.format(get_abbr_impl(), get_impl_ver(), get_abi_tag())
cuda_output = !ldconfig -p|grep cudart.so|sed -e ‘s/..([0-9]).([0-9]*)$/cu\1\2/’
accelerator = cuda_output[0] if exists(’/dev/nvidia0’) else ‘cpu’
!pip install torch_nightly -f https://download.pytorch.org/whl/nightly/{accelerator}/torch_nightly.html
!pip install fastai==1.0.28
import torch
print(torch.version)
print(torch.cuda.is_available())
print(torch.backends.cudnn.enabled)
I want to install fastai v0.7 using conda because I want to try out the Introduction to machine learning course.
Currently, on installing fast ai, I get an error that module structured not found.
Is there any way around ?
I cloned the fastai.git directory. I try to do conda env update on environment-cpu.yml. It is giving me a bunch of conda verification errors like CondaVerificationError: The package for numpy-base located at C:\Users\ssengupta
\AppData\Local\Continuum\anaconda2\pkgs\numpy-base-1.16.2-py36hc3f5095_0
appears to be corrupted. The path ‘Scripts/f2py.exe’
specified in the package manifest cannot be found.
Hey, for anyone who had difficulty running the notebooks on a windows 10 machine, this is what worked for me:
…Documents\Repo\fastai\courses\ml1>mklink /d fastai …\old\fastai
The existing symlink worked through cmd but not from jupyter.
The symlink created above did the trick. Hope that helps.