Hi ColossalDeer61 ,
the next trains-agent RC (solving the #196 issue) will also solve the double install issue 🙂
Is it possible, instead of reinstalling the packages, to simply switch to a different existing virtualenv, at the beginning of the task execution?
Hi ColossalDeer61 ,
Xxx is the module where my main experiment script resides.
So I think there are two options,
Assuming you have a similar folder structure-main_folder
--package_folder
--script_folder
---script.py
Then if you set the "working directory" in the execution section to "." and the entry point to "script_folder/script.py", then your code could do:from package_folder import ABC
2. After cloning the original experiment, you can edit the "installed packages", and add a new line with:git+ https://github.com/user/repo/repo.git
This is the equivalent of doing pip install git+ https://github.com/user/repo/repo.git
What do you think?
Another (minor) issue is that all the packages that are installed using git+https are cloned and installed twice, immediately one after the other
Manually editing the requirements is indeed a step forward, thanls.
The current challenge is installing with "--no-binary" flag
For example:
h5py==2.10.0 --no-binary=h5py
hmm interesting use case, why do you need to add the "--no-binary"
Another (minor) issue is that all the packages that are installed using git+https are cloned and installed twice, immediately one after the other
Yes this is so that we can better log the installed package name, not a major issue, but we just fixed a bug with derivative packages from git packages.
https://github.com/allegroai/trains/issues/196
In this case local changes are made that can impact these libraries.
I am not sure it is a real problem in the trains scenario