pip install clearml==0.17.5rc4

Hi WickedGoat98

"Failed uploading to //:8081/files_server:"

Seems like the problem. what do you have defined as files_server in the trains.conf

No idea why it fails...

It does not upload, the default behavior is to log the artifact (so you know where you stored, but not enforce unnecessary uploads)
If you were to change:
task = Task.init(project_name='examples', task_name='Keras with TensorBoard example')to:
task = Task.init(project_name='examples', task_name='Keras with TensorBoard example', output_uri=" ")It would also upload the model

the other repos i have are constantly worked on and changing too

Not only it will be cloned automatically, the git diff of the sub-modules are stored as well 🙂

Yes there was a bug that it was always cached, just upgrade the clearml
pip install git+

You mean the job with the exact same arguments ?
do you have other arguments you are passing ?
Are you using Optuna / HBOB ?

In theory it should have worked.
Can you send me the full Task log? (with cache and everything?)
I suspect since these are not the default folders, something is misconfigured / missing
(you can DM the log, so it won't end on a public the channel))

Yes, there is no real limit, I think the only requirements id docker v19+

ZanyPig66 you are correct in your assumptions. What exactly do you have in the Task? If there is no git repo the entire script should be under "uncommitted changes. What is your case?

YEY 🙂

@<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 ?

Could it be you have two entries of "console_cr_flush_period" ?

Hi BoredPigeon26
what do you mean by "reuse the task" ? is this manual execution (i.e. from code)?
How about archiving the old version?
You can also force Task.init to always create a new Task (which preserves the previous run alongside the execution tab)
Basically what's the specific use case ?

About .get_local_copy... would that then work in the agent though?

Yes it would work both locally (i.e. without agent) and remotely

Because I understand that there might not be a local copy in the Agent?

If the file does not exist locally it will be downloaded and cached for you

Merged 🙂

SubstantialElk6 Ohh okay I see.
Let's start with background on how the agent works:
When the agent pulls a job (Task), it will clone the code based on the git credentials available on the host itself, or based on the git_user/git_pass configured in ~/clearml.conf
https://github.com/allegroai/clearml-agent/blob/77d6ff6630e97ec9a322e6d265cd874d0ab00c87/docs/clearml.conf#L18
The agent can work in two modes:
Virtual environment mode, where it will create a new venv for each experiment ba...

AntsyElk37

and when i try to use --output-uri i can't pass true because obviously i can't pass a boolean only strings

hmm, that sounds right, I think we should fix that so when using --output-uri true the value that is passed is actually True, not the string "true".
Regrading the issue itself:
are you saying --skip-task-init is being ignored ? and it always adds the Task.init call? you can also pass --output-uri https://files.clear.ml (which is the same as True) ,...

And if you could also update the docs with all env vars possible to set up it would awesome!

Yes, I'll pass it on, that is a good point

Thanks! Yes, this could be great !

Could you please open a GitHub issue, so we remember to update the feature ?

BTW: if you want to sync between artifacts / settings, I would recommend calling task.reload() to get the latest values back from the server.

ReassuredTiger98 there is an open issue on supporting bash script as pre run inside a docker (which will be supported in the next major release)
BTW: if you already have a docker file the fastest way would just to build the docker file and push it once, then you just specify the docker image:tag, this can be done a Task specific level.

Guys, any chance you can verify the RC solves the issue?
pip install clearml==1.0.2rc0

Let me check ....

GreasyPenguin14 makes total sense.
In that case I would say variants to the accuracy make sense to me, I would suggest:
title='trains', series='accuracy/day' and title='trains', series='accuracy/night'
Regrading hierarchy, from the implementation perspective a unique identifier is always the combination of title/series (or in other words metric/variant), introducing another level is a system wide change.
This means it might be more challenging than expected ...

Based on what I see when the ec2 instance starts it installs the latest, could it be this instance is still running?

Different question. How can I pass PYTHONPATH env variable to a task, run by agent (so python can find classes inside m subdirectories)?

Hi HelpfulHare30
By default the working directory will be added to the python path, this means if I have under execution:
Working Dir: "." Script: "src/script.py"The root git repo will be added to the python path.
BTW: next RC you could add a flag to the agent to always add the git repo

I am trying to use the

configuration vault

option but it doesn't seem to apply the variables I am using.

Hi EmbarrassedSpider34 I think this is an enterprise feature...

Manged to make the credentials attached to the configuration when the task is spinned,

I'm assuming env variables ?

Thanks EnviousStarfish54
Let me check if I can reproduce it

Correct 🙂

I think that is good enough