Fastai v1 install issues thread


Fantastic, thank you, I am training dogs_cats without any issues.

I have noticed that the GPU utilization is significantly lower than with fastai 0.7, averaging only 30% compared to nearly 100% before, is this likely to be because I have reduced the number of workers and therefore the speed at which data is fed to the GPU?


Yup, you’re limited by the CPU now since you can’t multiprocess the data fetching.


And I’m guessing there is no easy fix to the multiprocessing issue on windows?

(Andrea de Luca) #106

Hi Fellas. I was playing with V1’s augmentor, and had a nasty surprise. I then replicated the issue inside an Ipython notebook, just to leave out any jupyter-related issue.

Above you can see a python prompt from my personal machine. is imported without any fuss, BUT the kernel does not see the function apply_tmfs() (Still, it is present in
Below, you can see a python prompt from a machine at my workplace upon which I installed V1. Same install method. The kernel sees apply_tmfs() without any complaint.

Any suggestion?

(Jeremy Howard (Admin)) #107

In the first one you’ve not spelt it correctly. Use tab-completion to help.

(Thomas) #108

I am starting to move to jupyter-lab (instaed of notebook) and in the enviroment I created to use fastai, jupyter notebook imports fastai without problems, but jupyter-lab does not find the library.
Any idea?

(Jeremy Howard (Admin)) #109

We need a lot more info to help you.

I’ll merge this in to the installation thread.

(Andrea de Luca) #110

Thanks boss. You are right, I didn’t spell it correctly since tab-completion didn’t work, and it didnt work since apply_tfms() is not seen. Look:

If I just import it in another way, the kernel does see apply_tfms()! This is madness…

I even wiped the whole environment, did a conda clean --all to flush any broken package in the cache repository, and reinstalled the whole env from scratch. Same behaviour.

Importing the whole fastai and calling vision.transform.apply_tfms() DOES WORK. It doesn’t like from import *, but just for transform, since everything else imported this way does work as well…

(Thomas) #111

From within the jupyter lab, I try to execute the tabular nb:

[1] !conda list
# packages in environment at /Users/thomascapelle/anaconda3/envs/fastai:
# Name                    Version                   Build  Channel
appnope                   0.1.0                    py37_0  
asn1crypto                0.24.0                   py37_0  
backcall                  0.1.0                    py37_0  
blas                      1.0                         mkl  
bleach                    3.0.2                    py37_0  
ca-certificates           2018.03.07                    0  
certifi                   2018.10.15               py37_0  
cffi                      1.11.5           py37h6174b99_1  
chardet                   3.0.4                    py37_1  
cryptography              2.3.1            py37hdbc3d79_0  
cycler                    0.10.0                   py37_0  
cymem                     1.31.2           py37h04f5b5a_0  
cytoolz                   py37h1de35cc_1  
dataclasses               0.6                        py_0    fastai
dbus                      1.13.2               h760590f_1  
decorator                 4.3.0                    py37_0  
dill                              py37_0  
entrypoints               0.2.3                    py37_2  
expat                     2.2.6                h0a44026_0  
fastai                    1.0.6                      py_1    fastai
fastprogress              0.1.10                     py_0    fastai
freetype                  2.9.1                hb4e5f40_0  
gettext                      h15daf44_3  
glib                      2.56.2               hd9629dc_0  
icu                       58.2                 h4b95b61_1  
idna                      2.7                      py37_0  
intel-openmp              2019.0                      118  
ipykernel                 5.0.0            py37h39e3cac_0  
ipython                   7.0.1            py37h39e3cac_0  
ipython_genutils          0.2.0                    py37_0  
ipywidgets                7.4.2                    py37_0  
jedi                      0.13.1                   py37_0  
jinja2                    2.10                     py37_0  
jpeg                      9b                   he5867d9_2  
jsonschema                2.6.0                    py37_0  
jupyter                   1.0.0                    py37_7  
jupyter_client            5.2.3                    py37_0  
jupyter_console           6.0.0                    py37_0  
jupyter_core              4.4.0                    py37_0  
kiwisolver                1.0.1            py37h0a44026_0  
libcxx                    4.0.1                h579ed51_0  
libcxxabi                 4.0.1                hebd6815_0  
libedit                   3.1.20170329         hb402a30_2  
libffi                    3.2.1                h475c297_4  
libgfortran               3.0.1                h93005f0_2  
libiconv                  1.15                 hdd342a3_7  
libpng                    1.6.35               ha441bb4_0  
libsodium                 1.0.16               h3efe00b_0  
libtiff                   4.0.9                hcb84e12_2  
markupsafe                1.0              py37h1de35cc_1  
matplotlib                3.0.0            py37h54f8f79_0  
mistune                   0.8.4            py37h1de35cc_0  
mkl                       2019.0                      118  
mkl_fft                   1.0.6            py37hb8a8100_0  
mkl_random                1.0.1            py37h5d10147_1  
msgpack-numpy                     py37_0  
msgpack-python            0.5.6            py37h04f5b5a_1  
murmurhash                0.28.0           py37h0a44026_0  
nbconvert                 5.3.1                    py37_0  
nbformat                  4.4.0                    py37_0  
ncurses                   6.1                  h0a44026_0  
ninja                     1.8.2            py37h04f5b5a_1  
notebook                  5.7.0                    py37_0  
numpy                     1.15.2           py37h6a91979_1  
numpy-base                1.15.2           py37h8a80b8c_1  
olefile                   0.46                     py37_0  
openssl                   1.0.2p               h1de35cc_0  
pandas                    0.23.4           py37h6440ff4_0  
pandoc                                 0  
pandocfilters             1.4.2                    py37_1  
parso                     0.3.1                    py37_0  
pcre                      8.42                 h378b8a2_0  
pexpect                   4.6.0                    py37_0  
pickleshare               0.7.5                    py37_0  
pillow                    5.3.0            py37hb68e598_0  
pip                       10.0.1                   py37_0  
plac                      0.9.6                    py37_0  
preshed                   1.0.1            py37h0a44026_0  
prometheus_client         0.4.2                    py37_0  
prompt_toolkit            2.0.6                    py37_0  
ptyprocess                0.6.0                    py37_0  
pycparser                 2.19                     py37_0  
pygments                  2.2.0                    py37_0  
pyopenssl                 18.0.0                   py37_0  
pyparsing                 2.2.2                    py37_0  
pyqt                      5.9.2            py37h655552a_2  
pysocks                   1.6.8                    py37_0  
python                    3.7.0                hc167b69_0  
python-dateutil           2.7.3                    py37_0  
pytorch-nightly-cpu       1.0.0.dev20181014         py3.7_0    pytorch
pytz                      2018.5                   py37_0  
pyzmq                     17.1.2           py37h1de35cc_0  
qt                        5.9.6                h45cd832_2  
qtconsole                 4.4.1                    py37_0  
readline                  7.0                  h1de35cc_5  
regex                     2018.07.11       py37h1de35cc_0  
requests                  2.19.1                   py37_0  
scipy                     1.1.0            py37h28f7352_1  
send2trash                1.5.0                    py37_0  
setuptools                40.4.3                   py37_0  
simplegeneric             0.8.1                    py37_2  
sip                       4.19.8           py37h0a44026_0  
six                       1.11.0                   py37_1  
spacy                     2.0.12           py37h6440ff4_0  
sqlite                    3.25.2               ha441bb4_0  
termcolor                 1.1.0                    py37_1  
terminado                 0.8.1                    py37_1  
testpath                  0.4.2                    py37_0  
thinc                     6.10.3           py37h6440ff4_0  
tk                        8.6.8                ha441bb4_0  
toolz                     0.9.0                    py37_0  
torchvision-nightly-cpu   0.2.1              pyh19dea27_0    fastai
tornado                   5.1.1            py37h1de35cc_0  
tqdm                      4.26.0           py37h28b3542_0  
traitlets                 4.3.2                    py37_0  
typing                    3.6.4                    py37_0  
ujson                     1.35             py37h1de35cc_0  
urllib3                   1.23                     py37_0  
wcwidth                   0.1.7                    py37_0  
webencodings              0.5.1                    py37_1  
wheel                     0.32.1                   py37_0  
widgetsnbextension        3.4.2                    py37_0  
wrapt                     1.10.11          py37h1de35cc_2  
xz                        5.2.4                h1de35cc_4  
zeromq                    4.2.5                h0a44026_1  
zlib                      1.2.11               hf3cbc9b_2 

[2]from fastai import *          # Quick access to most common functionality
   from fastai.tabular import *  # Quick access to tabular functionality
ModuleNotFoundError                       Traceback (most recent call last)
<ipython-input-1-eb17ac0e42e6> in <module>()
----> 1 from fastai import *          # Quick access to most common functionality
      2 from fastai.tabular import *  # Quick access to tabular functionality

ModuleNotFoundError: No module named 'fastai'

If I do exactly the same thing, in the jupyter notebook instead of lab, it works.
I am in a mac, with CPU versions of torch.
What other info I need to provide?

(Jeremy Howard (Admin)) #112

Thanks for the extra info. apply_tfms isn’t defined in that module. Generally it’s easiest to simply from fastai import * and from import * (assuming you are doing a vision application) then you’ll have everything you need. You can then type apply_tfms and jupyter will return <function so you can see where it came from. You’ll also find it in the vision.image section of the docs:

(Andrea de Luca) #113

Thanks for your quick and effective reply.

But allow me one more question: If my personal box shows the expected behaviour, why did the DL box at work behave differently?


Yes I was reading it right now, it is a pleasure to read such a well-written documentation. Job well done!

(Stas Bekman) #114

(Thomas) #115

I checked, and reinstalling jupyter-lab solved the issue. There are many threads about conda enviroments not showing in jupyter,

I hope that when jupyter-lab is officially released this is solved.
You can create a new, empty enviroment in conda, and call jupyter-lab/notebook and it will open, calling the system jupyter. This should not be allowed.

(Stas Bekman) #116

@tcapelle , I documented a summary of that SO thread here:
Since I can’t reproduce this issue, please review and let me know if anything needs to be changed in that new section.

If someone can give me a set of commands to run including creating a new conda environment and indicate at which stage the problem shows up - that will help me to reproduce the problem - and solve it.


sorry if that’s the incorrect thread to reply on… do you know when pytorch1.0 is going to be ready in windows (rather than building myself)?

i have tried a whole day, installing vs2017 and follow the steps in pytorch website but can’t get it compiled…
i need to do a trial and error on installing cmake, msbuild, vs2017, v141…etc but still can’t get it done.


They said at the conference the v1 would really be out around NIPS though you can also ask that question on the pytorch forum :wink:

(Matthew Rosenthal) #119

Just wanted to post that I built a new Ubuntu 18.04 box today with a 1080ti and was able to get it all installed fairly straightforward(only 1 full OS re-install).

I mainly followed this guide -

Instead of using ubuntu gui(first 2 steps) to install nvidia drivers I did it through apt install the ppa repo:

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo apt install nvidia-driver-410

I did conda install for pytorch with this:

conda install pytorch-nightly cuda92 -c pytorch

(Chan Sooi Loong) #121

how install the latest version of fastai?
running conda update fastai -c fastai will only install version 1.0.6

UPDATE: manage to install the latest version after doing these steps:

  1. conda update conda -y
  2. conda install anaconda -y

If you encounter any permission error, do this:
sudo chown -R user /home/user/src
where user is the username, /home/user/src is the folder the where anaconda is installed in Ubuntu

(Scott H Hawley) #122

I’m getting “ImportError: cannot open shared object file: No such file or directory”

As per the Troubleshooting thread, I my driver is
nvidia-396/xenial,now 396.54-0ubuntu0~gpu16.04.1 amd64 [installed]
, and nvidia-smi is working.

$ find /usr/ | grep

…these are from the CUDA that I just installed tonight in trying to get FastAI working.

On this Ubuntu 16.04 system, previously I was using CUDA 9.1 with CUDNN7.0 with PyTorch and it worked fine with my GPU. The things that are broken tonight are a result of trying to follow the installation instructions.

I’ve created a fresh conda environment, ran the 3 conda install lines to install pytorch and the fastai packages, but when I run the test line, I get

$ python -c 'import fastai; fastai.show_install(1)'
Traceback (most recent call last):
File "&lt;string&gt;", line 1, in &lt;module&gt;
File "/opt/anaconda/envs/fastai/lib/python3.6/site-packages/fastai/", line 1, in &lt;module&gt;
from .basic_train import *
File "/opt/anaconda/envs/fastai/lib/python3.6/site-packages/fastai/", line 2, in &lt;module&gt;
from .torch_core import *
File "/opt/anaconda/envs/fastai/lib/python3.6/site-packages/fastai/", line 2, in &lt;module&gt;
from .imports.torch import *
File "/opt/anaconda/envs/fastai/lib/python3.6/site-packages/fastai/imports/", line 2, in &lt;module&gt;
from .torch import *
File "/opt/anaconda/envs/fastai/lib/python3.6/site-packages/fastai/imports/", line 1, in &lt;module&gt;
import torch, torch.nn.functional as F
File "/opt/anaconda/envs/fastai/lib/python3.6/site-packages/torch/", line 84, in &lt;module&gt;
from torch._C import *
ImportError: cannot open shared object file: No such file or directory

Would appreciate any help! Thanks.

PS- I do need CUDA installed ‘normally’ on my system, because I also have a project that uses Keras that I need to run on this machine. (…Oh geez, and I removed CUDA 9.1 in doing the Troubleshooting, but my Tensorflow was built from source using 9.1!)

(Stas Bekman) #123

There is an issue with the recent fastai conda packages if you have an outdated anaconda package.

This is caused by an outdated anaconda package, which wants a numpy < 1.15


conda install anaconda

which should install anaconda 5.3.0 or higher.

and then it should work.

I changed meta.yaml deps to not ask for numpy>=1.15, but rolled back to >=1.12 so the next release should take care of it.