Two question regarding deployment/setup

Hello,

1. After setting up trains-agent, how should I make sure the agent has access to that latest code updates?

For example:

1. I’m working on my dev machine, starting a new experiment

2. I’m duplicating the experiment on the trains-server

3. The agent grabs the experiment and starts doing its thing

4. I’m making a code change on my dev machine, starting a new experiment

5. I’m duplicating the experiment on the trains-server

6. —> what should happen next? <— the agent is yet to be updated with the latest code change, should I update all of the agents manually before?

7. Do I need to mount different weights volume for each agent?

Thank you! Shaked

[Shaked]

Hey @bmartinn

Thank you for your reply.

Apparently the issue was related to the experiment, because I tried another one and it just worked… I guess I did something wrong before and didn’t give enough attention how I messed it up .

Thanks again Shaked

[bmartinn]

@Shaked , it seems it is running the selected docker, but from your error I assume it did not install the required python packages inside the docker.

Let’s take the trains package as an example, do you have it under “Experiment” -> “Execution” -> “Installed Packages” ?

If you do not, that seems to be the problem. Python packages are installed inside the docker according to this section on the experiment. It should be automatically populated when you execute your code in development-mode, e.g. manually, without the trains-agent.

If the trains package is listed under “Installed Packages”, then I suggest you send the installation log, because obviously it failed to install it…

BTW, what do you mean by:

Just to make sure, we are trying to mount local python modules from /home/Shaked/remote_code/green:/opt/green and /opt/experiments using our own custom base docker image.