Hmm that makes sense, btw the PYTHONPATH set by the agent would be the working dir listed under the Task, But if you set the agent.force_git_root_python_path the agent would also add the root git repo to the python path

JitteryCoyote63 This seems like exactly what you are saying, elastic license issue...

Hi LazyFish41
Could it be some permission issue on /home/quetalasj/.clearml/cache/ ?

So you are saying it ignored everything after the bucket's "/" ?

A few more details on the New RC  (1.1.2rc0) change set:

Upload dataset now supports chunksize, for multi-part upload/download (useful with large datasets)
backwards compatibility, i.e. parent datasets do not have to support multi-part datasets
Notice multi-part datasets should be accessed with latest RC
cleaml-data upload --chunk-size Dataset().upload(..., chunk_size=None)
Get Dataset support partial download (i.e. for debugging, or for more efficient multi-node support)
Notice total n...

Although I didn't understand why you mentioned

torch

in my case?

Just a guess 🙂 other frameworks do multi-process as well,

I would guess it relates to parallelization of Tasks execution of the

HyperParameterOptimizer

class?

Yes that might be it, it's basically by product of using python "Process" class for multiprocessing. we are working on a fix, not a trivial unfortunately

My pleasure

Then when ran a second time, the task will contain the requirements of the (conda-) environment from the first run.

What you see in the log under "Summary - installed python packages:" will be exactly what is updated on the Task. But it does not contain the "ruamel_yaml_conda" package, this is what I cannot get...
But I did find this part:
ERROR: conda 4.10.1 requires ruamel_yaml_conda>=0.11.14, which is not installed.Which point to conda needing this package and then failing to i...

VexedCat68 yes 🙂 you can also pass the parent folder and it will zip the entire subfolders into a single artifact

This task is picked up by first agent; it runs DDP launch script for itself and then creates clones of itself with task.create_function_task() and passes its address as argument to the function

Hi UnevenHorse85
Interesting use case, just for my understanding, the idea is to use ClearML for the node allocation/scheduling and PyTorch DDP for the actual communication, is that correct ?

passes its address as argument to the function

This seems like a great solution.

the queu...

Hi @<1798887590519115776:profile|BlushingElephant78>

have multiple steps that run inside a gitlab repo

one thing to make sure that is not missed, "inside a gitlab repo" , notice the actual pipeline is running on agents/workers/k8s gitlab will be the trigger and monitor it, but the actual execution should probably happen somewhere with proper compute

this works fine when i run the pipeline from the script directly but when i run it from the web interface

try to configure your...

RipeGoose2 yes, the UI cannot embed the html yet, but if you go click on the link itself it will open the html in a new tab.
Could you verify it works ?

Hi PompousBeetle71
I remember it was an issue, but it was solved a while ago. Which Trains version are you using?

Hmm let me check something

SubstantialElk6 could you add a github issue to set the direct url for the vscode as a parameter to the cleaml-session?
We already have --vscode-version we could either extend it to include a direct url, or add a new argument.
wdyt ?

Could that be it ?

Hi GreasyPenguin66
Is this for the client side ? If it is why not set them in the clearml.conf ?

PipelineController works with default image, but it incurs overhead 4-5 min

You can try to spin the "services" queue without docker support, if there is no need for containers it will accelerate the process.

Repository cloning failed: Command '['git', 'fetch', '--all', '--recurse-submodules']' returned non-zero exit status 1.

This error is about failing to clone the pipeline code repo, how is that connected to changing the container ?!
Can you provide the full log?

os.system

Yes that's the culprit, it actually runs a new process and clearml assumes that there are no other scripts in the repository that are used, so it does not analyze them
A few options:
Manually add the missing requirement Task.add_requirements('package_name')make sure you call it before the Task.init
2. import the second script from the first script. This will tell clearml to analyze it as well.
3. Force the entire clearml to analyze the whole repository: https://g...

Hi @<1743079861380976640:profile|HighKitten20>

but when I try to use code stored in a GIT (Bitbucket) repo I got a repository cloning error, specifically

did you pass configure the git repo application/pass here: None

Hmm, Notice that it does store sym links to parent data versions (to save on multiple copies of the same file). If you call get_mutable_local_copy() you will get a standalone copy

Hmm EmbarrassedPeacock82
Let's try with
--input-size -1 60 1 --aux-config input.format=FORMAT_NCHWBTW: this seems like a triton LSTM configuration issue, we might want to move the discussion to the Triton server issue, wdyt?

EnviousStarfish54 quick update, regardless of the logging.config.dictConfig issue, I will make sure that even when the logger is removed, the clearml logging will continue to function 🙂
The commit will be synced after the weekend

Hi @<1523715429694967808:profile|ThickCrow29>

I am using the PipelineController with abort_on_failure set to False.

Is this a pipeline from code or from Tasks?
What is the clearml version?
Lastly, if a component fails, and another components is dependent on it's output, how would it run? if it is not dependent, why is it a child component?

hmm interesting use case, why do you need to add the "--no-binary"

Do you have any advice for this step, (monitoring)? I feel like it's not very well documented.

Yeah I think it is complicated.
I would start with the example here: None
Basically what it does is create histogram over time of the values the Rest API gets. Then in graphana it visualizes those values.
Notice that the request latency / frequency are automatically logged ...

Hi SkinnyPanda43

Let's say that I install the shared libs with pip in editable mode on my development evironment, how does the clearml-agent will handle those libraries if I submit a job

So installing packages from local folders with "-e" is in general ill-advised.
But using a full git path should work out of the box. for example if you install pip install https://github.com/user/repo/repo.git then the agent will be able to install it on the remote machine. The main challenge...

IrritableGiraffe81 could it be the pipeline component is not importing pandas inside the function? Notice that a function decorated with pipeline component become a stand-alone, this means that if you need pandas you need to import inside the function. The same goes for all the rest of the packages used.
When you are running with run_loclly or debug_pipeline you are using your local env , as opposed to the actual pipeline where a new env is created inside the repo.
Can you send the Entire p...

No it will not 😞 the closer is closer to the actual print.
That said, I'm sure it would not be complicated to add.
But I have to wonder, this will really create a mess in the console log, so if someone wants it, it will be global (i.e. also in the visible console. not only in the backend), so the case where the console on the machine itself is "clean" but the backend log is full of debug stuff is not clear to me

JitteryCoyote63
Sure, just please add a github issue request, so it does not get forgotten.
BTW: wouldn't it be more convinient to configure in the trains.conf ?