add it to the python path

PYTHONPATH="/src/project"

this allowed the script to run!
but now he does not see the folders that are in the /src/project folder"

can you please tell me how to make it so that he can see

this is for hydra launch

Current working directory ('os.getcwd()') : /root/.clearml/venvs-builds/3.7/code
Check that the config directory '/root/.clearml/venvs-builds/3.7/code/conf' exists and readable

now I am still clarifying the points that have become attractive to our leadership, I will supplement my answer, How will they answer me.

For reference
I have now locally raised Clearml on a nearby machine and logging is configured as in the textbook - all metrics are worked out.
On the machine where I run docker, I just copied the clearml.conf file. Maybe you need to do something else (send the /opt/clearml folder and drop it into the docker image?)?

i run:
` task = Task.init(
project_name=f"RL_experiments/{cfg.train.env_train.target.split('.')[-1]}/{'/'.join(cfg.train.trainmodule.target.split('.')[-2:])}",
task_name="demo",
reuse_last_task_id=False)

task.connect(dict(OmegaConf.to_container(cfg, resolve=True)))

logger = get_logger("train_ql", log_level=cfg.base.log_level)
logger.info(f"cfg:\n{OmegaConf.to_yaml(cfg)}")
tmp_values = train_dqn_task(cfg.train, cfg.base)
task.mark_completed() `

*leadership, management == customer

yes, ofc

` (base) user@s130:~$ clearml-init
ClearML SDK setup process

Please create new clearml credentials through the profile page in your clearml-server web app (e.g. )
Or create a free account at

In the profile page, press "Create new credentials", then press "Copy to clipboard".

Paste copied configuration here:
api {

web_server:  ` ` 
api_server:  ` ` 

credentials {
    "access_key" = "6VUTS73D48DMPVI1NMPS"
    "secret_key" = "4fGtZVirW0ztSLbm6JPLESM...

AgitatedDove14
my management liked that in wandb you can make reports on experiments with interactive graphs and that they would be viewed on the Internet + multicursor.
And I think what advantages ClearML has to compensate for this chips.
I thought that maybe someone made a comparison and find the necessary arguments in this comparison.

From the active one, we are still using local placement, logging the console, logging parameters, displaying metrics and debugging the picture with drawin...

like this?

export CLEARML_AGENT_SKIP_PYTHON_ENV_INSTALL="True"

upd: it's work!!!
Thanks a lot!

cool!
twm!

basket name all ok?

CostlyOstrich36
*If the agent did not perform a certain action, then its average reward per episode for this action will be nan , not 0

[ctrl + C] [ctrl + V]
https://github.com/allegroai/clearml/issues/604

CostlyOstrich36
usability of the pytorch_lightning logger

we log the average reward of each action for the RL agent.
If the agent you did this action on the current episode, then his average reward will be nan , not 0. for obvious reasons. And we would like it to be visualized in the same way as in the tensorboard, for informational content.

@<1523701205467926528:profile|AgitatedDove14>
thank you very much, it's clear!

and dell tasks, and all ok:
` #task = Task.init(
project_name=f"RL_experiments/{cfg.train.env_train.target.split('.')[-1]}/{'/'.join(cfg.train.trainmodule.target.split('.')[-2:])}",
task_name="demo",
reuse_last_task_id=False)

#task.connect(dict(OmegaConf.to_container(cfg, resolve=True)))

logger = get_logger("train_ql", log_level=cfg.base.log_level)
logger.info(f"cfg:\n{OmegaConf.to_yaml(cfg)}")
tmp_values = train_dqn_task(cfg.train, cfg.base)

...

please tell me, is it possible to somehow make it so that costomous fakets, which are not in the public domain, would be used?

for example, if I somehow start the execution of an agent task in a specific docker container?)

TimelyPenguin76
As I remember, the last one is 1.1.4
What exactly do you mean about task logger?

How do you like that?

Thank you very much for your help and for such a convenient product!)
I haven't figured out the alents yet, but it already looks amazing!)

And why can it be that the displayed time is zero?
although the experiments were considered for several days

@<1523701087100473344:profile|SuccessfulKoala55>
I'm talking about something like OPTUNA

wow, that's interesting, please let me know. Are there screenshots or a demo video somewhere where you can see how the enumeration parameters are set.

i use the local free version of clearml

1. specify container from UI

2. libraries in the ubuntu repository have not yet reached their pip / pypi repository

CostlyOstrich36 ^

Yes, thank you!) Is there an addition to it, how will it look like in Slack?

yes, I agree, thank you, tell me please, is it planned to add a multicursor in the future?

yes, that looks like it, thanks!
I'll try adding these and see how it helps

import numpy as np np.nan

all code

in documentation link https://docs.docker.com/compose/install/