I was able to reproduce this problem following your instructions. Mine was installed via conda and had no such problems.
So as you identified pip installs incompatible versions of some of the numpy functionality and bottleneck, conda’s versions of these packages don’t have that problem. The problem happens during pandas’ import.
It looks like a new long overdue release is being tested: https://github.com/kwgoodman/bottleneck/issues/191, so perhaps let’s wait a little bit and perhaps it’ll get resolved automatically with the new release.
If, however, it gets delayed and/or new numpy is still not released, we will pin pip to bottleneck=1.2.0 for the next fastai release.
As you can see from the bug report, I managed to reduce the problem to:
python -c "import pandas"
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
Forgive the noob question here, but I am purposely working under 1.0.36.post1. I am using bash-git-prompt. When I am in the fastai folder, I am able to confirm I am using version 1.0.36.post1. When create a new folder for Kaggle competitions within the fastai folder, and then cd into the Kaggle folder, I check the version and now see that I am using 1.0.40.
All of this is done within a virtual environment. Any ideas on how I can make sure I am still under 1.0.36.post1? Apologies if I am supposed to be asking this question under a different thread than this one.
Use locate fastai/data_block.py if you’re on unix to find all the instances and then you will see if you have it installed twice. You probably have some symlinks pointing to a second install or something similar. Can’t tell without a proper report.
p.s. if you’re working with the git checkout, there was originally also a git cross-over in the 1.0.36 branch (with master HEAD) that has been fixed since then, so if you’re using the 1.0.36 branch, you need to update it.
I am having trouble upgrading to the latest version of fastai on Windows 10 using conda. I haven’t been able to update since 1.0.38. Running conda update fastai returns “all packages already installed”, even though there have been several new versions.
The only thing I can see is that at version 1.0.39, the build changed from py_1 to 1. Could this be causing the issue? I tried removing fastai and reinstalling, but it just installed 1.0.38 again. Specifying the latest version explicitly doesn’t work either.
Here’s the output of conda search fastai. The new versions are there, but it won’t install.
Name Version Build Channel
fastai 1.0.37 py_1 fastai
fastai 1.0.38 py_1 fastai
fastai 1.0.39 1 fastai
fastai 1.0.40 1 fastai
fastai 1.0.41 1 fastai
fastai 1.0.42 1 fastai
fastai doesn’t install dataclasses for py37, but it’s needed for py36. Most likely what happened is that you installed fastai with py37, but then some other package downgraded python to py36 and you’re running fastai with py36, while you installed it with py37?
It’d help if you were to follow the guideliness for support: https://docs.fast.ai/support.html
You’re not saying when you encountered the error. Please put yourself in the shoes of the person that has no idea what you did and then you will know what information to share
we currently don’t use conda-forge and all package dependencies are tested against the anaconda channel, so it’s possible that something is off in your case, since you’re on the fringe. But again I have no way of telling.
sorry I missed to clarify the python version. I installed python 3.6 after the conda installation (So what you wrote is not true for my case). Then I install fastai via conda -c pytorch -c fastai fastai.
The error of No module named 'dataclasses' occurred after I ran the cell of from fastai.tabular import *.
I created the environment on nvidia-docker. There, I used anaconda to follow the instruction on the github repo as possible.
Thank you for providing these details, @crcrpar. Indeed there was a bug in the conda package setup for py36, should be resolved in fastai-1.0.43 when that is released. Until then, please add conda install dataclasses to your docker build script.
yeah, conda is not very flexible in this situation. pip allows defining a dynamic package dependency which gets sorted out during install. conda only during package build and then it’s set in stone. So the variant is only doable if py36 and py37 packages are built. Since fastai is noarch, this variant unfortunately doesn’t work. But luckily no harm in reinstalling dataclasses for py37, so all is good.
Hi,
I get the following error:
DistributionNotFound: The ‘fastprogress>=0.1.18’ distribution was not found and is required by the application
when running
from fastai.vision import *
or other import operations in an Jupyter Notebook.
It runs fine when running it just in python.
I installed it through pip
fastai 1.0.42
fastprogress 0.1.18
Python version
3.6.3 (default, Sep 2 2018, 00:38:05)
I am running Ubuntu 16.04.
I should also note that this might be related to my pyenv setup, which I am using. However, I have not had any problems with the pyenv-jupyter combination so far.
What seems to be best practice (if there even is one) for upgrading to a new version of a Nvidia driver, or a new Pytorch version? I’ve read the documentation on https://docs.fast.ai/troubleshoot.html, but couldn’t find guidance. What I’m asking is, do you wait a while, so as to make sure it’s stable, or do you upgrade as soon as a new version is released?
Usually, you want to upgrade things like nvidia drivers, when the new release includes:
fixes to something that was broken that you needed to work
new features you actually need
speed improvements that are important to you
and when you upgrade hardware and then you may have to get a newer driver.
In all other circumstances, if you have a satisfactory setup - save your time and sanity and don’t update, especially since often updates break other things.
Another time I update everything is when I revamp everything anyway, e.g. new Ubuntu version once in a few years.
Hi helpers. I have been getting this conda error for about a week whenever trying to update the fastai conda environment. Can anyone help?
Some clues…
The conda command below used to work.
The error might have started after conda asked me to update conda. I did this by dutifully copy/pasting the command given, without understanding what it did.
My setup is local, with Ubuntu 16.04 LTS, GTX 1070.
conda list(s) currently the following versions. They work together. I don’t know which are needed, but I prefer to use Cuda92, or whichever is the most recent stable version.