Hi SteadyFox10 , unfortunately trains-agent currently supports only docker as a container solution (I guess they became the de-facto standard)
That said, there is the option of virtual environment, where the trains-agent installs everything inside a newly created virtual environment. That actually makes it quite easy to expand to other use cases. Essentially the docker option will spin a docker install trains-agent inside the docker and run it execute command.
Do you fee l...

Or you can do:
param={'key': 123}
task.connect(param)

Hmm I see your point.
Any chance you can open a github issue with a small code snippet to make sure we can reproduce and fix it?

BeefyCow3 On the plot itself click on the json download button

Hmmm, I'm not sure that you can disable it. But I think you are correct it should be possible. We will add it as another argument to Task.init. That said, FriendlyKoala70 what's the use case for disabling the code detection? You don't have to use it later, but it is always nice to know :)

I see... We could definitely add an argument to control it. I'll update here once there is an RC

Merged 🙂

Hmmm, that actually connects with something we were thinking about: introducing sections to the hyper parameters. This way we could easily differentiate between the command line arguments and other types of parameters. DilapidatedDucks58 what do you think?

The idea is that it is not necessary, using the trains-agent you can not only launch the experiment on a remote machine, you can override the parameters, not just cmd line arguments, but any dictionary you connected with the Task or configuration...

DilapidatedDucks58 if you have so many parameters, why don't you use the
task.connect_configuration(dict)
It will put it in the artifacts, as an editable json alike string.

BTW copying the cmd line assumes that you are running it in the same machine...

You can always access the entire experiment data from python
'Task.get_task(Id).data'
It should all be there.
What's the exact use case you had in mind?

It's dead simple to install:
Pip install trains-agent
the.n you can simply do:
Trains-agent execute --id myexperimentid

Is this the case?

AstonishingSeaturtle47 How would the code run without the sub-modules? And what is the problem we are trying to solve? (Because unfortunately there is no switch to disable it)

AstonishingSeaturtle47 that's awesome! Could you explain the hack, it might be helpful for others (I assume :))

check here None

Trains is fully open-source, that said properly publishing and maintaining the web client is still on our to do list (I mean there is totally readable JavaScript code packaged in the trains-server and the dockers). It is constantly pushed because there is generally less contributions on the front-end with these kind of projects. That said of you guys are willing to help, it will greatly help in pushing it forward... LivelyLion31 what do you think, would you guys like to help with the fronte...

Awesome, PRs are always welcome, and we try to help with any request and feature coming for users. We just added audio support (RC releasing in a few days) based only on users request.
https://github.com/allegroai/trains/issues/120

HugeArcticwolf77 changing the color is definitely a feature we will have in the next version, right now I think you cannot 😞 it is randomly chosen based on the title/series and I think your example is a great failure case of that randomness 😅

Hi StrangePelican34 , you mean poetry as package manager of the agent? The venvs cache will only work for pip and conda, poetry handles everything internally:(

try:
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docker_install_opencv_libs: true

Hmm I see, add this for example

extra_docker_shell_script: ["rm ~/.bashrc", "echo removed bashrc"]

None

Try to add '--network host' to the docker args on the task you are launching

Then try to add the missing apt packages

extra_docker_shell_script: ["apt-get install -y ???", ]

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@<1610083503607648256:profile|DiminutiveToad80> try to turn on:
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enable_git_ask_pass: true

Hi @<1661542579272945664:profile|SaltySpider22>
Basically you need to put all of these files into a repository , which is always a good practice.
The reason is that the pipeline (and for that matter any Task on the system) can store wither a single script or a git reference, but not multiple scripts.

What do you mean by "modules first and find a way to install that package" ?
Are those modules already in wheels ? are they part a git repository?
(the pipeline component can also start inside a git repository it clones)

Hi VivaciousWalrus21

After restarting training huge gaps appear in iteration axis (see the screenshot).

The Task.init actually tries to understand what was the last reported interation and continue from that iteration, I'm assuming that what happens is that your code does that also, which creates a "double shift" that you see as the jump. I think the next version will try to be "smarter" about it, and detect this double gap.
In the meantime, you can do:
` task = Task.init(...)...

SubstantialElk6
The CA is taken automatically by urllib, check the OS environments you need to configure it.
https://stackoverflow.com/questions/27835619/urllib-and-ssl-certificate-verify-failed-error
SSL_CERT_FILE REQUESTS_CA_BUNDLE