Or should the task.close appear before the task.mark_failed?

Well the requirements were automatically filled, not by me

Great, thanks

It does match the image.

SuccessfulKoala55 , meanwhile I try that, I encounter something weird. I am using a clearml agent with the following
clearml-agent daemon --detached --docker --gpus 0,1,2,3 --dynamic-gpus --queue kenny_1_gpu_queue=1
But for some reason although all the gpus are free and no other agent is on the machine, only one task is executed at the time instead of 4. Why is that?

Hi SuccessfulKoala55 ,
failed. I read in the docs I can use mark_failed .
How should I use it correctly with task.close()?

SuccessfulKoala55
Exactly

SuccessfulKoala55
Well, I've removed the requirement altogether and now it won't fail on this anymore (TF is provided anyway AFAIK via the image) but now I get the following:

Any ideas?

*Needless to say, when running locally this works with no problem. Also the http://nvcr.io/nvidia/tensorflow:21.02-tf2-py3 image is able to run TRT

It should be possible somehow, as they are attached to the Task and displayed in the Task's results tab

Sure, just a moment

I am also running from a NVIDIA container and I get
ERROR: No matching distribution found for tensorflow==2.4.0+nv
clearml_agent: ERROR: Could not install task requirements!

docker image is
http://nvcr.io/nvidia/tensorflow:21.10-tf2-py3
What should I do?

This is what I mean

Clearml agent 1.1.1

e.g., Dir/To/Stuff//Another

no, in the project name

project name is: RemoteStorage06/saips06/rdekel/hackathon_baselines/DATA_DIR/
No strange characters as far as I can tell

AgitatedDove14 , could it be that the GitHub is not synchronized? I can find only up to 1.2.0.rc3 in it.

I'd like if possible a command line, same as I'd just sent, to recognize the specific worker that was brought up in this manner and kill only it

I was told not to kill the process, also, finding it on my own seems very un-user-friendly

Will try. Thanks.

clearml-agent daemon --detached --gpus 0,1,2 --dynamic-gpus --queue 2_gpu_queue=2 --docker --stop

Well, on the first task it grabs it opens a different WORKER:gpu0 worker entry as expected while the agent stays with WORKER:dgpu0,1,2,3
but the other tasks on queue won't start and upon the first task's completion the following are not being run on WORKER:gpu0 but on WORKER:dgpu0,1,2,3 instead using only 1 GPU (the task execution says it runs on WORKER:gpu0)

Sent you the log privately.

I know you can download the data like a json from the plots tab in the UI, but I want the data programmatically

scalars are only some of the results a Task can have

Thanks. But I am not talking about scalars. I am talking about plots I've reported to ClearML using .report_histogram or .report_scatter2d or .report_table

But this is not the data I want

A task can also have plots - for example 2d scatter plots and histograms

SuccessfulKoala55 I've tried changing manually the TF version but it fails. I get:
import tensorflow as tf
File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/tensorflow/init.py", line 435, in <module>
_ll.load_library(_main_dir)
File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/tensorflow/python/framework/load_library.py", line 153, in load_library
py_tf.TF_LoadLibrary(lib)
tensorflow.python.framework.errors_impl.NotFoundError: /usr/local/lib/py...

try making two tasks, both with the same project name (While the project name contains '//') and you will get the same error.