pkg_resources.DistributionNotFound: The 'dataclasses' distribution was not found and is required by torch

[werhoog]

Hi, I have installed the topaz the newest version 0.2.5. Because the GPU version is sm_83, I installed the pytorch==1.7.0=py3.7_cuda11.0.221_cudnn8.0.3_0. And then I installed topaz with conda install topaz.
However, when I run the command topaz in the terminal, the error follows,
Traceback (most recent call last):
File "/data/Apps//topaz_0.2.5python3/bin/topaz", line 6, in
from pkg_resources import load_entry_point
File "/data/Apps/topaz_0.2.5python3/lib/python3.7/site-packages/pkg_resources/init.py", line 3267, in
@_call_aside
File "/data/Apps/topaz_0.2.5python3/lib/python3.7/site-packages/pkg_resources/init.py", line 3251, in _call_aside
f(*args, **kwargs)
File "/data/Apps/topaz_0.2.5python3/lib/python3.7/site-packages/pkg_resources/init.py", line 3280, in _initialize_master_working_set
working_set = WorkingSet._build_master()
File "/data/Apps/topaz_0.2.5python3/lib/python3.7/site-packages/pkg_resources/init.py", line 582, in _build_master
ws.require(requires)
File "/data/Apps/opaz_0.2.5python3/lib/python3.7/site-packages/pkg_resources/init.py", line 899, in require
needed = self.resolve(parse_requirements(requirements))
File "/data/Apps/topaz_0.2.5python3/lib/python3.7/site-packages/pkg_resources/init.py", line 785, in resolve
raise DistributionNotFound(req, requirers)
pkg_resources.DistributionNotFound: The 'dataclasses' distribution was not found and is required by torch

Do you have any idea about this error?
Thanks!

[tbepler]

This looks like a problem with the python package system. Can you share the complete details of your conda environment (you can find this by running conda list in your topaz environment)?

P.S. the topaz version on conda is 0.2.4. If you want the dev build of 0.2.5, you need to install from source.

[tbepler]

Are there any updates on this issue? Did you figure out the problem @werhoog?

[biochem-fan]

I am having this issue after fresh install with conda install topaz cudatoolkit=11.0 -c tbepler -c pytorch.

conda list says:

# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                        main
_openmp_mutex             5.1                       1_gnu
blas                      1.0                         mkl
bottleneck                1.3.4            py38hce1f21e_0
ca-certificates           2022.4.26            h06a4308_0
certifi                   2022.5.18.1      py38h06a4308_0
cudatoolkit               11.0.3              h88f8997_10    conda-forge
dataclasses               0.8                pyh6d0b6a4_7
freetype                  2.11.0               h70c0345_0
future                    0.18.2                   py38_1
giflib                    5.2.1                h7b6447c_0
intel-openmp              2021.4.0          h06a4308_3561
joblib                    1.1.0              pyhd3eb1b0_0
jpeg                      9e                   h7f8727e_0
lcms2                     2.12                 h3be6417_0
ld_impl_linux-64          2.38                 h1181459_1
libffi                    3.3                  he6710b0_2
libgcc-ng                 11.2.0               h1234567_1
libgfortran-ng            7.5.0               ha8ba4b0_17
libgfortran4              7.5.0               ha8ba4b0_17
libgomp                   11.2.0               h1234567_1
libpng                    1.6.37               hbc83047_0
libstdcxx-ng              11.2.0               h1234567_1
libtiff                   4.2.0                h2818925_1
libuv                     1.40.0               h7b6447c_0
libwebp                   1.2.2                h55f646e_0
libwebp-base              1.2.2                h7f8727e_0
lz4-c                     1.9.3                h295c915_1
mkl-service               2.4.0            py38h7f8727e_0
mkl_fft                   1.3.1            py38hd3c417c_0
mkl_random                1.2.2            py38h51133e4_0
ncurses                   6.3                  h7f8727e_2
ninja                     1.10.2               h06a4308_5
ninja-base                1.10.2               hd09550d_5
numexpr                   2.8.1            py38h6abb31d_0
numpy                     1.22.3           py38he7a7128_0
numpy-base                1.22.3           py38hf524024_0
openssl                   1.1.1o               h7f8727e_0
packaging                 21.3               pyhd3eb1b0_0
pandas                    1.4.2            py38h295c915_0
pillow                    9.0.1            py38h22f2fdc_0
pip                       21.2.4           py38h06a4308_0
pyparsing                 3.0.4              pyhd3eb1b0_0
python                    3.8.13               h12debd9_0
python-dateutil           2.8.2              pyhd3eb1b0_0
pytorch                   1.7.0           py3.8_cuda11.0.221_cudnn8.0.3_0    pytorch
pytz                      2022.1           py38h06a4308_0
readline                  8.1.2                h7f8727e_1
scikit-learn              1.0.2            py38h51133e4_1
scipy                     1.7.3            py38hc147768_0
setuptools                61.2.0           py38h06a4308_0
six                       1.16.0             pyhd3eb1b0_1
sqlite                    3.38.3               hc218d9a_0
threadpoolctl             2.2.0              pyh0d69192_0
tk                        8.6.12               h1ccaba5_0
topaz                     0.2.5                      py_0    tbepler
torchvision               0.8.1                py38_cu110    pytorch
typing_extensions         4.1.1              pyh06a4308_0
wheel                     0.37.1             pyhd3eb1b0_0
xz                        5.2.5                h7f8727e_1
zlib                      1.2.12               h7f8727e_2
zstd                      1.5.2                ha4553b6_0

[biochem-fan]

For me with 1080Ti, conda install topaz cudatoolkit=10.0 -c tbepler -c pytorch solved the issue, but this workaround is not usable for people with newer cards.