I see if this is the case try to set
'output_uri="file:///full/path/to/dir"'
Notice it has to have the full path there and the file:// prefix

BTW: trains-agent is leaner, and does not need plotly. And you can use the APIClient to basically query the entire system, would that be a better solution? See https://github.com/allegroai/trains-agent/blob/master/examples/archive_experiments.py

make sense ?

When you have a bit of experience, please suggest a path forward, it will be great to integrate

Does what you suggested here >

Yes, it is basically the same underlying mechanism, only instead of 1-to-1 it's 1-to-many

Hi StickyMonkey98

a 

very

 large number of running and pending tasks, and doing that kind of thing via the web-interface by clicking away one-by-one is not a viable solution.

Bulk operations are now supported , upgrade the clearml-server to 1.0.2 🙂

Is it possible to fetch a list of tasks via Task.get_tasks,

Sure:
Task.get_tasks(project_name='example', task_filter=dict(system_tags=['-archived']))

TartSeal39 please let me know if it works, conda is a strange beast and we do our best to tame it.
Specifically when you execute manually on a conda env we collect (separately) the conda packages & the python packages (so later we can replicate on both conda & pip, or at least do our best)
Are you running both development env and agent with conda ?

Hi DeliciousBluewhale87
I think you are correct, there is no way to pass it.
As TimelyPenguin76 mentioned you can either set a default output_uri on the agent's config file, or edit the created Task in the UI.
What is the specific use case ? Maybe we should add this ability, wdyt?

@<1535793988726951936:profile|YummyElephant76> oh you mean like jupyter server was running, then inside the notebook you would start a new venv, in that venv "notebook" package was missing, hence it failed detecting the notebook ?

apologies @<1798887585121046528:profile|WobblyFrog79> somehow I missed your reply,

My workflow is based around executing code that lives in the same repository, so it’s cumbersome having to specify repository information all over the place, and changing commit hash as I add new code.

It automatically infers the repo if the original as long as the pipeline code itself is inside the repo, by that I mean the pipeline logic, when you run it the first time (think development etc), if it s...

SubstantialElk6
Notice if you are using a manual setup the default is "secure: false" you have to change it to "secure: true":
https://github.com/allegroai/clearml-agent/blob/176b4a4cdec9c4303a946a82e22a579ae22c3355/docs/clearml.conf#L251

so that you can get the latest artifacts of that experiment

what do you mean by " the latest artifacts "? do you have multiple artifacts on the same Task or s it the latest Task holding a specific artifact?

@<1651395720067944448:profile|GiddyHedgehong81> just to be clear, Dataset.get_local_copy returns a path to your files,
You have to Manually add the additional path to the specific files you need to use. It does Not know that in advance.
That was the initial issue you had, and I assume it is the same one here. does that make sense ?

Anyhow if the StorageManager.upload was fast, the upload_artifact is calling that exact function. So I don't think we actually have an issue here. What do you think?

I think it would make sense to have one task per run to make the comparison on hyper-parameters easier

I agree. Could you maybe open a GitHub issue on it, I want to make sure we solve this issue 🙂

What if I register the artifact manually?

task.upload_artifact('local folder', artifact_object=' ')This one should be quite quick, it's updating the experiment

if fails during 

add_step

 stage for the very first step, because 

task_overrides

 contains invalid keys

I see, yes I guess it it makes sense to mark the pipeline as Failed 🙂
Could you add a GitHub issue on this behavior, so we do not miss it ?

Great to hear!

Hi NonchalantGiraffe17
You mean this documentation?
https://clear.ml/docs/latest/docs/references/api/tasks#post-tasksclone

However, the pipeline experiment is not visible in the project experiment list.

I mean press on the "full details" in the pipeline page

Well that depends on how you think about the automation. If you are running your experiments manually (i.e. you specifically call/execute them), then at the beginning of each experiment (or function) call Task.init and when you are done call Task.close . This can be done in parallel if you are running them from separate processes.
If you want to automate the process, you can start using the trains-agent which could help you spin those experiments on as many machines as you l...

I believe AnxiousSeal95 is.
ElatedFish50 any specific reason for the question?

Hi JitteryCoyote63
Show running experimentsIt doesn't?
Have the legend clickable, to hide/show experiments based on their status:+1:
Have a line connecting points that are SOTA (example in https://paperswithcode.com/sota/image-generation-on-cifar-10 )I like that, how is that selected? (I know FE are thinking of replacing this entire graph library, so maybe good timing in terms of what to look at)

Hi @<1523702969063706624:profile|PoisedShark13>

However, INSTALLED PACKAGES of my task is misses many of installed packages (any idea why?)

It automatically detects the directly imported packages, literally analyzing your code base and looking for imports
The derivative packages (i.e. the one that any of the "main" packages need, will be listed after the first time the agent installs everything)
If something specific is missing, you can manually add it with:

Task.add_requiremen...

This port is odd, it should be 8008
8015

So basically a list of Path objects ?

I can share some code

Please do 🙂

Thank you @<1689446563463565312:profile|SmallTurkey79> !!!

Hmm that is a good question, are you mounting the clearml.conf somehow ?

repeat it until they are all dead 🙂