ResolvePackageNotFound on Windows

Renaldas111 commented 2 years ago

As I read, all these not found packages should go under pip section with different formatting, it is some kind of a bug, I understand (https://github.com/datitran/object_detector_app/issues/41). This would be very time consuming to rename and reformat all these packages manually. Is there a way to make a requirements file for all platforms?

conda env create -f environment.yml Collecting package metadata (repodata.json): done Solving environment: failed

ResolvePackageNotFound:

setuptools==52.0.0=py37h06a4308_0
cudatoolkit==11.0.221=h6bb024c_0
nbconvert==6.1.0=py37h89c1867_0
zeromq==4.3.4=h2531618_0
jpeg==9b=h024ee3a_2
jupyter_core==4.7.1=py37h89c1867_0
mistune==0.8.4=py37h4abf009_1002
lz4-c==1.9.3=h2531618_0
libprotobuf==3.13.0.1=h8b12597_0
readline==8.1=h27cfd23_0
argon2-cffi==20.1.0=py37h4abf009_2
libpng==1.6.37=hbc83047_0
jedi==0.18.0=py37h89c1867_2
libstdcxx-ng==9.1.0=hdf63c60_0
yaml==0.2.5=h516909a_0
numpy==1.20.2=py37h2d18471_0
cryptography==3.1.1=py37h1ba5d50_0
jupyter_nbextensions_configurator==0.4.1=py37h89c1867_2
libuv==1.40.0=h7b6447c_0
brotlipy==0.7.0=py37h7b6447c_1000
zstd==1.4.9=haebb681_0
libsodium==1.0.18=h36c2ea0_1
freetype==2.10.4=h5ab3b9f_0
sqlite==3.35.4=hdfb4753_0
intel-openmp==2021.2.0=h06a4308_610
zlib==1.2.11=h7b6447c_3
mkl==2021.2.0=h06a4308_296
tk==8.6.10=hbc83047_0
python==3.7.10=hdb3f193_0
ipython==7.26.0=py37h6531663_0
ca-certificates==2021.10.8=ha878542_0
watchdog==0.10.4=py37h89c1867_0
pytorch==1.7.1=py3.7_cuda11.0.221_cudnn8.0.5_0
libtiff==4.1.0=h2733197_1
ninja==1.10.2=hff7bd54_1
mpi4py==3.0.3=py37hd955b32_1
lcms2==2.12=h3be6417_0
matplotlib-base==3.3.1=py37h817c723_0
pandas==1.1.3=py37he6710b0_0
libgfortran4==7.5.0=ha8ba4b0_17
pandoc==2.14.1=h7f98852_0
mkl-service==2.3.0=py37h27cfd23_1
libgcc-ng==9.1.0=hdf63c60_0
xz==5.2.5=h7b6447c_0
shortuuid==1.0.1=py37h89c1867_4
pip==21.1.2=py37h06a4308_0
ld_impl_linux-64==2.33.1=h53a641e_7
mkl_random==1.2.1=py37ha9443f7_2
pyyaml==5.3.1=py37hb5d75c8_1
lxml==4.6.3=py37h9120a33_0
openmpi==4.0.2=hb1b8bf9_1
cffi==1.14.3=py37he30daa8_0
libgfortran-ng==7.5.0=ha8ba4b0_17
libxml2==2.9.10=hb55368b_3
certifi==2021.10.8=py37h89c1867_1
numpy-base==1.20.2=py37hfae3a4d_0
ncurses==6.2=he6710b0_1
openssl==1.1.1n=h7f8727e_0
promise==2.3=py37h89c1867_4
tornado==6.1=py37h4abf009_0
pillow==8.2.0=py37he98fc37_0
jupyter_highlight_selected_word==0.2.0=py37h89c1867_1002
libxslt==1.1.34=hc22bd24_0
kiwisolver==1.3.1=py37hc928c03_0
libffi==3.3=he6710b0_2
icu==58.2=hf484d3e_1000
mkl_fft==1.3.0=py37h42c9631_2

xl-sr commented 2 years ago

I added a minimal environment, you can give it a try again

Renaldas111 commented 2 years ago

Ok, thanks! This time the environment installs with no problem, but the next problem was AssertionError: Torch not compiled with CUDA enabled. Solved it by conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch . Remember spending hours and getting the same problem when trying to install Stylegan and ProjectedGAN, so this time solved the problem in minutes. Would be nice if the proper version would be installed straight out of environment file. Finally, tried to run python train.py --outdir=I:/Out --cfg=stylegan3-t --data=I:/data256.zip --gpus 1 --batch=4 --mirror=1 --snap 10 --kimg 10000 --stem --syn_layers 10 --metrics=none The process stuck at Setting up PyTorch plugin "filtered_lrelu_plugin"... Maybe I was not patient enough, but waited for more than 5 minutes seemed for me reasonable amount of time to conclude something is wrong.

Finally, I just ran Stylegan XL from ProjectedGAN env I used for many months. It asked for several additional modules to install, and at least now I am at:

Setting up augmentation... Distributing across 1 GPUs... Setting up training phases... Exporting sample images... Initializing logs... Skipping tfevents export: No module named 'tensorboard' Training for 10000 kimg...

Setting up PyTorch plugin "upfirdn2d_plugin"... Done. tick 0 kimg 0.0 time 2m 08s sec/tick 12.8 sec/kimg 3199.28 maintenance 115.1 cpumem 4.98 gpumem 6.60 reserved 8.08 augment 0.000

xl-sr commented 2 years ago

great that it works for you now :) it's always tricky to make environments work everywhere. I'll leave the environment as is now and close this issue, but I'll refer to it in the README for Windows users.

huvers commented 2 years ago

Windows still gave me an issue with 'cudatoolkit=11.1', but adding 'conda-forge' to the channels in environment.yml solves it.

rimless commented 1 year ago

Ok, thanks! This time the environment installs with no problem, but the next problem was AssertionError: Torch not compiled with CUDA enabled. Solved it by conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch . Remember spending hours and getting the same problem when trying to install Stylegan and ProjectedGAN, so this time solved the problem in minutes. Would be nice if the proper version would be installed straight out of environment file. Finally, tried to run python train.py --outdir=I:/Out --cfg=stylegan3-t --data=I:/data256.zip --gpus 1 --batch=4 --mirror=1 --snap 10 --kimg 10000 --stem --syn_layers 10 --metrics=none The process stuck at Setting up PyTorch plugin "filtered_lrelu_plugin"... Maybe I was not patient enough, but waited for more than 5 minutes seemed for me reasonable amount of time to conclude something is wrong.

Finally, I just ran Stylegan XL from ProjectedGAN env I used for many months. It asked for several additional modules to install, and at least now I am at:

Setting up augmentation... Distributing across 1 GPUs... Setting up training phases... Exporting sample images... Initializing logs... Skipping tfevents export: No module named 'tensorboard' Training for 10000 kimg...

Setting up PyTorch plugin "upfirdn2d_plugin"... Done. tick 0 kimg 0.0 time 2m 08s sec/tick 12.8 sec/kimg 3199.28 maintenance 115.1 cpumem 4.98 gpumem 6.60 reserved 8.08 augment 0.000

I met the same problem, and don't know why. It will stuck for 30 mins and quit automatically since the timeout.

autonomousvision / stylegan-xl

ResolvePackageNotFound on Windows #10