Installation failed

[thiner]

I tried to prepare environment with conda env create -f env.yaml, but failed. The error message as below:

Pip subprocess error: ERROR: Ignored the following versions that require a different python version: 2.10.1 Requires-Python <3; 2.11.0 Requires-Python <3; 2.11.1 Requires-Python <3; 2.4.0 Requires-Python <3; 2.4.1 Requires-Python <3; 2.4.2 Requires-Python <3; 2.4.3 Requires-Python <3; 2.4.4 Requires-Python <3; 2.5.0 Requires-Python <3; 2.5.1 Requires-Python <3; 2.5.2 Requires-Python <3; 2.6.0 Requires-Python <3; 2.6.1 Requires-Python <3; 2.6.2 Requires-Python <3; 2.7.0 Requires-Python <3; 2.7.2 Requires-Python <3; 2.8.0 Requires-Python <3; 2.8.1 Requires-Python <3; 2.8.2 Requires-Python <3; 2.8.3 Requires-Python <3; 2.8.4 Requires-Python <3; 2.8.5 Requires-Python <3; 2.8.6 Requires-Python <3; 2.8.7 Requires-Python <3; 2.9.2 Requires-Python <3 ERROR: Could not find a version that satisfies the requirement apex==0.1 (from versions: 0.9.8dev.linux-i686, 0.9.8.dev0, 0.9.8a0.dev0, 0.9.9.dev0, 0.9.10.dev0) ERROR: No matching distribution found for apex==0.1

failed

CondaEnvException: Pip failed

[LukeForeverYoung]

It seems that the main error is related to the installation of apex. mPLUG-Owl depends on cpp extension (MixedFusedLayerNorm) of apex, therefore compiling apex from source code is needed.

[vishaal27]

Do you install apex from source on A100s? Seems like the installation is not as straightforward for them.

[MAGAer13]

We recommand to install apex from the source. Apex.

git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

[LukeForeverYoung]

Our repository now includes an Apex copy and installation guidelines, which have been validated for installation in V100 and A100 with PyTorch 1.13.1+cu117. Please refer to the repository for more information.

[thiner]

Thanks for your updates. But maybe you forgot to push the apex_22.01_pp code?

[MAGAer13]

We have updated it. By the way, we are planning to remove the reliance of apex in the next version. Stay Tuned.

[thiner]

Installation failed again. I updated the env.yaml file, update the pytorch version to 1.13.1 as you mentioned above. But it ran into error prompting plenty of lib version imcompatible issues. Can you generat a workable environment.yml file by conda env export --from-history | findstr -v "prefix" > environment.yml ? By the way, I think it's better to add env name in the env.yaml file. E.g. name: owl

[cnxupupup]

Does the Apex installation of your project support 3090 or TITAN RTX？because there are some problems encountered in the installation