basically:
` from trains import Task

task = Task.init("test", "test", "controller")
task.upload_artifact("test-artifact", dict(foo="bar"))
cloned_task = Task.clone(task, name="test", parent=task.task_id)
cloned_task.data.script.entry_point = "test_task_b.py"
cloned_task._update_script(cloned_task.data.script)
cloned_task.set_parameters(**{"artifact_name": "test-artifact"})
Task.enqueue(cloned_task, queue_name="default") `

Here is the minimal reproducable example.
Run test_task_a.py - It will register a dummy artifact, create a new task, set a parameter in that task and enqueue it test_task_b will try to retrieve parameter from parent task and fail

Yes this is correct. I am trying to create a minimal reproducable example

AgitatedDove14 I cannot confirm at 100%, the context is different (see previous messages) but it could be the same bug behind the scene...

What is weird is:
Executing the task from an agent: task.get_parameters() returns an empty dict Calling task.get_parameters() from a local standalone script returns the correct properties, as shown in web UI, even if I updated them in UI.So I guess the problem comes from trains-agent?

Thanks for your inputs, I will try that! For completion, here is how I retrieve the parameters:
` from trains import Task

task = Task.init("test", "test")
parent_task = Task.get_task(task.parent)
task.get_logger().report_text(task.get_parameters())
artifact_name = task.get_parameter("General/artifact_name")
artifact = parent_task.artifacts[artifact_name].get() `

So in my minimal reproducable example, it does work 🤣 very frustrating, I will continue searching for that nasty bug

yes

very cool, good to know, thanks SuccessfulKoala55 🙂

Hi SuccessfulKoala55 , super that’s what I was looking for

Indeed, I actually had the old configuration that was not JSON - I converted to json, now works 🙂

Very nice! Maybe we could have this option as a toggle setting in the user profile page, so that by default we keep the current behaviour, and users like me can change it 😄 wdyt?

no it doesn't! 3. They select any point that is an improvement over time

Thanks!3. I don't know, I never used Highcharts 🙂

I am not using hydra, I am reading the conf with:
config_dict = read_yaml(conf_yaml_path) config = OmegaConf.create(task.connect_configuration(config_dict))

But I am not sure it will connect the parameters properly, I will check now

Doing it the other way around works:
` cfg = OmegaConf.create(read_yaml(conf_yaml_path))
config = task.connect(cfg)
type(config)

<class 'omegaconf.dictconfig.DictConfig'> `

but then why do I have to do task.connect_configuration(read_yaml(conf_path))._to_dict() ?
Why not task.connect_configuration(read_yaml(conf_path)) simply?
I mean what is the benefit of returning ProxyDictPostWrite instead of a dict?

Same, it also returns a ProxyDictPostWrite , which is not supported by OmegaConf.create

I mean, inside a parent, do not show the project [parent] if there is nothing inside

Because it lives behind a VPN and github workers don’t have access to it

No worries! I asked more to be informed, I don't have a real use-case behind. This means that you guys internally catch the argparser object somehow right? Because you could also simply use sys argv to find the parameters, right?

Some more context: the second experiment finished and now, in the UI, in workers&queues tab, I see randomly
trains-agent-1 | - | - | - | ... (refresh page) trains-agent-1 | long-experiment | 12h | 72000 |

Why is it required in the case where boto3 can figure them out itself within the ec2 instance?

by replacing the pid with $PID ?

it actually looks like I don’t need such a high number of files opened at the same time

because at some point it introduces too much overhead I guess

now how to adapt to do it from extra_vm_bash_script ?

that works from within the ssh session

mmmh it fails, but if I connect to the instance and execute ulimit -n , I do see
65535while the tasks I send to this agent fail with:
OSError: [Errno 24] Too many open files: '/root/.commons/images/aserfgh.png'and from the task itself, I run:
import subprocess print(subprocess.check_output("ulimit -n", shell=True))Which gives me in the logs of the task:
b'1024'So nnofiles is still 1024, the default value, but not when I ssh, damn. Maybe rebooting would work