Hi UnsightlySeagull42 ,

didn’t get that 😕 what do you mean by

strings are not there anymore.

what is the value? nothing?

👍

Hi SucculentBeetle7 ,

get_local_copy()  will return the entire dataset (the zip file), but you can divide the dataset and have the same parent for all of them, what do you think?

Hi OddShrimp85 ,

Whats the clearml version you are using? Do you have boto3 installed?

if you are using add_function_step you can pass packages=["protobuf<=3.20.1"]
(there is an example in the sdk docs https://clear.ml/docs/latest/docs/references/sdk/automation_controller_pipelinecontroller#add_function_step-1 )

👍 great, so if you have an image with clearml agent, it should solve it 😀

Agents - https://www.youtube.com/watch?v=MX3BrXnaULs

Thanks GiganticTurtle0 , I was able to reproduce it, a fix will be out shortly, will keep you update about it in this thread

HelpfulHare30 can you share the ClearML version?

I just tried and everything works.

I run this for the template task:

` from clearml import Task

task = Task.init(project_name="Examples", task_name="task with connected dict")

period = {"start": "2020-01-01 00:00", "end": "2020-12-31 23:00"}

task.connect(period, name="period") `

and this for the clone one:

` from clearml import Task

template_task = Task.get_task(task_id="<Your template task id>")
cloned_task = Task.clone(source_task=template_task,
name=templat...

not the parameters, but maybe this can help - https://clear.ml/docs/latest/docs/clearml_data

Hi MinuteCamel2 ,

It’s all part of the auto-magic 🪄 after Task.init , the pytorch lightning functions are bind with ClearML, so it will report all the outputs to your ClearML app 🙂

let me try to reproduce this issue

There are many ways to do so, this is an example for github action: https://github.com/allegroai/trains-actions-train-model

Hi CooperativeFox72 ,

basically each user should do it once, just to add credentials in the user’s profile page.

About credentials for the server, let me check that for you

For the trains-agent , you have an option to specify the trains.conf file you want it to run with. just start the trains-agent with trains-agent --config ~/trains_agent.conf (where ~/trains_agent.conf is your ~/trains.conf file for the agent run).

how could I configure this in the docker compose?

Do you mean to env vars?

Hi DisturbedWalrus17 ,

Do you want to clear the parameters from a cloned task?

Hi SmarmySeaurchin8

I tried to reproduce your issue (run https://github.com/allegroai/trains/blob/master/examples/reporting/image_reporting.py example with many report_image calls) and got all the outputs in the debug samples section, can you share a snippet or how can I reproduce this issue?

yep, you should get a dict like:

{'title': {'series': { 'x': [0, 1 ,2], 'y': [10, 11 ,12], }}}

So for the UI each user will need to add the credentials only once, the users should have the credentials in ~trains.conf file. They just need to copy those to the profile page

Hi WackyRabbit7 , how do you run the agent? manually command?

You can change the dataset _task object to have your storage location as output_uri

Hi ReassuredTiger98 ,

try:
` from clearml.config import running_remotely

if running_remotely():
... `

Hi GracefulDeer63 ,

What trains and trains-server versions are you using?

didn't get it, do you get the model in the task with local path?

Hi CleanPigeon16 , yes it is.

You can just write the same as you do in your ~/clearml.conf file, for example:

agent.force_git_ssh_protocol = true

And all the others works as expected?

Hi WackyRabbit7

You can get all the agents PIDs by
ps -ef | grep "trains-agent"and kill -9 <pid> for the requested agent.

You can also pkill -f "trains-agent --gpus 0"   - This will kill a process that started trains-agent --gpus 0 .
Notice it matches the cmd pattern so it has to match the way you executed the trains-agent. This can be checked with  ps -Af | grep trains-agent

Hi RoundSeahorse20 ,

According to the error, history.history['accuracy'] and history.history['loss'] are lists containing the values for the accuracy and loss.

You can go over those and report each value:
for idx, val in enumerate(history.history['accuracy']): logger.report_scalar("accuracy score", "Train", iteration=idx, value=val)Can this do the trick?

Hi FierceHamster54 ,

I think

And is this compatible with the

Task.force_store_standalone_script()

option ?

is causing the issue, you are storing the entire script as a standalone without any git, so once you are trying to import other parts of the git, BTW any specific reason using it in your pipeline?