For 'TRAINS Monitor: Could not detect iteration reporting, falling back to iterations as seconds-from-start' message - the iteration reporting is automatically detected if you are using tensorboard , matplotlib , or explicitly with trains.Logger
Assuming there were no reports, so the monitoring falls back to report every 30 seconds.

Thanks for the examples, will try to reproduce it now.

Hi GleamingGiraffe20 , still getting those errors?

Hey SubstantialElk6 ,

You can try adding environment vars with that info:

os.environ["CLEARML_API_HOST"] = api_server os.environ["CLEARML_WEB_HOST"] = web_server os.environ["CLEARML_FILES_HOST"] = files_server os.environ["CLEARML_API_ACCESS_KEY"] = access_key os.environ["CLEARML_API_SECRET_KEY"] = secret_key

yes, you could also use the container’s SETUP SHELL SCRIPT and run command to install your python version (e.g.
sudo apt install python3.8for example)

Hi JitteryCoyote63 , Did you edit the diff part?

can you share configs/2.2.2_from_scratch.yaml file with me? The error point to line 13, anything special in this line?

It should be fixed in one of the next versions

Hi WackyRabbit7 , saw you updated the GH issue, will try to reproduce it here

For the agent?

👍

are you referring to the docker image? The same as before with task.set_base_docker("dockerrepo/mydocker:custom --env GIT_SSL_NO_VERIFY=true")

So running the docker with ‘“device=0,1”’ works? We will check that

When you start the ClearML agent, the last line is the file for the agent’s output, for linux is should be something like:

Running CLEARML-AGENT daemon in background mode, writing stdout/stderr to /tmp/.clearml_agent_daemon_***.txt

you need to run it, but not actually execute it. You can execute it on the ClearML agent with task.execute_remotely(queue_name='YOUR QUEUE NAME', exit_process=True) .

with this, the task wont actually run from your local machine but just register in the ClearML app and will run with the ClearML agent listening to 'YOUR QUEUE NAME' .

If you are referring to Python packages, you should add it to the “installed packages” section on the execution tab of you experiment. just replace the version with your package location, for example, if you have clearml == 0.17.4 , you can replace it with
git+to get the latest version of clearml.

which ClearML agent version are you running?

Hi GleamingGiraffe20 ,

Without adding Task.init , i’m getting some OSError: [Errno 9] Bad file descriptor error, do you get those too?

Do you run your script from CLI or IDE (pycharm maybe?)?

Can you try something like

` from clearml import Task

task = Task.get_task(task_id="TASK ID")
task.started()
task.get_logger().report_scalar("Some title", series="series", value=2, iteration=0)
task.flush()
task.completed() `This works for me, I can get the report

BTW whats the status of the task before running this code?

Can you check you have space at the end of the diff file?

https://hub.docker.com/r/nvidia/cuda/tags?page=1&ordering=last_updated&name=11.0-

Hi PanickyMoth78 ,

Note that if I change the component to return a regular meaningless string -

"mock_path"

, the pipeline completes rather quickly and the dataset is not uploaded. (edited)

I think it will use the cache from the second run, it should be much much quicker (nothing to download).

The files server is the default for saving all the artifacts, you can change this (default) with env var ( CLEARML_DEFAULT_OUTPUT_URI ) or config file ( ` sdk.development...

SmugTurtle78
by the end of this week

I can help you with that 🙂

task.set_base_docker("dockerrepo/mydocker:custom --env GIT_SSL_NO_VERIFY=true")

For this you don’t really need the output_uri , you can just do it as is.

not much info 😕

Can you manually run the docker ?

yep

Checking that

ok, I think I missed something on the way then.

you need to have some diffs, because

Applying uncommitted changes Executing: ('git', 'apply', '--unidiff-zero'): b"<stdin>:11: trailing whitespace.\n task = Task.init(project_name='MNIST', \n<stdin>:12: trailing whitespace.\n task_name='Pytorch Standard', \nwarning: 2 lines add whitespace errors.\n"
can you re-run this task from your local machine again? you shouldn’t have anything under UNCOMMITTED CHANGES this time (as we ...

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 🙂

Hi MotionlessCoral18 , can you check the configuration you added under you profile? is the bucket entry contains the HOST (ENDPOINT) section?