FreshReindeer51
Could you provide some logs ?

DistressedGoat23 you are correct, since at the end this become a plotly object the extra_layout is for general purpose layout, but this specific entry is next to the data. Bottom line, can you open a github issue, so we do not forget to fix? In the mean time you can use the general plotly reporting as SweetBadger76 suggested

Correct,
Notice that the glue has it's own defaults and the ability to override containers from the UI

, the easiest way possible would be if could just some how run task and let the lsf manage the environment

You mean let the LSF set the conda/venv ? or do you also mean to get the code-base, changes etc ?

BTW: generally speaking the default source dir inside a docker will be:
/root/.trains/venvs-builds/<python_version>/task_repository/<repository_name>/
for example:
/root/.trains/venvs-builds/3.6/task_repository/trains.git/

If you are using the latest RC:
pip install clearml==0.17.5rc5You can pass True it will use the "files_server" as configured in your clearml.conf
I used the http link as a filler to point to the files_server.
Make sense ?

Hi FriendlyKoala70 , trains will report all the tensorboard graphs, I'm assuming that's who is creating the epoch_lr graph. On top of it, you can always report manually with logger (as you pointed). Does that make sense to you?

Actually it hasn't changed ...

You can get a mutable copy of the entire dataset (original version), with get_mutable_copy() Then change the files on the returned directory, then create a new Dataset with the parent dataset as the original verison, then sync the folder.
You can also just update the specific file (without needing to download the entire original version)

Just wanted to know how many people are actively working on clearml.

probably 30+ 🙂
ReassuredTiger98 are you afraid from lack of support? or are you offering some (it is always welcomed) ?

In the Task log itself it will say the version of all the packages, basically I wonder maybe it is using an older clearml version, and this is why I cannot reproduce it..

I was able to successfully enqueue the task but only entrypoint script is visible to it and nothing else.

So you passed a repository link is it did not show on the Task ?
What exactly is missing and how the Task was created ?

👍
Okay But we should definitely output an error on that

Hi GreasyPenguin14

clearml-data stores only the difference between versions.

Yes, it is on a file basis granularity. Meaning if you change a file (regardless of the type of the file), the new modified file will be stored. Make sense ?

My pleasure 💗

so it would be better just to use the original code files and the same conda env. if possible…

Hmm you can actually run your code in "agent mode" assuming you have everything else setup.
This basically means you set a few environment variables prior to launching the code:
Basically:
export CLEARML_TASK_ID=<The_task_id_to_run> export CLEARML_LOG_TASK_TO_BACKEND=1 export CLEARML_SIMULATE_REMOTE_TASK=1 python my_script_here.py

there is almost zero overhead if your docker container alreadyt has everything (including the agent) preinstalled and you set it with CLEARML_AGENT_SKIP_PYTHON_ENV_INSTALL=1
it then should basically just run the code.

StraightDog31 how did you get these ?
It seems like it is coming from maptplotlib, no?

BTW: if you feel like pushing forward with integration I'll be more than happy to help PRing new capabilities, even before the "official" release

ShinyLobster84

fatal: could not read Username for '

': terminal prompts disabled

This is the main issue, it needs git credentials to clone the repo code, containing the pipeline logic (this is the exact same behaviour as pipeline v1 execute_remotely(), which is now the default, could it be that before you executed the pipeline logic, locally ?)
WackyRabbit7 could the local/remote pipeline logic could apply in your case as well ?

Thanks found it!

Hi @<1523704667563888640:profile|CooperativeOtter46>

Is there a way to set the name/path of the

requirements.txt

file the agent uses to install packages?

When the agent is installing packages it takes it from the "Onstalled Packages" section of the Task. Only if it is empty it will revert to "requirements.txt" from the git repository

That said, if you can Add the following to your "Installed Pacakges"

-r my_other_requirements.txt

And the agent will `my_...

I remember being told that the ClearML.conf on the client will not be used in a remote execution like the above so I think this was the problem.

SubstantialElk6 the configuration should be set on the agent's machine (i.e. clearml.conf that is on the machine running the agent)

2. Users have no choice of defining their own repo destination of choice.

In the UI you can specify in the "Execution" tab, Output "destination", a different destination for the models/artifacts. Is this...

Hi LovelyHamster1
Could you think of a toy code that reproduces this issue ?

I can install pytorch just fine locally on the agent, when I do not use clearml(-agent)

My thinking is the issue might be on the env file we are passing to conda, I can't find any other diff.
BTW:
@<1523701868901961728:profile|ReassuredTiger98> Can I send a specific wheel with mode debug prints for you to check (basically it will print the conda env YAML it is using)?

Hi @<1523701868901961728:profile|ReassuredTiger98> when you get to it...
please download the wheel, then install it with

pip3 install -U clearml_agent-0.17.3rc0-py3-none-any.whl

Then run the daemon with the additional --debug argument, basically:

clearml-agent --debug daemon --foreground ...

Once the agent is running please send the Task's log from your console 🙂

Thanks @<1523701868901961728:profile|ReassuredTiger98>
From the log this is what conda is installing, it should have worked

/tmp/conda_env1991w09m.yml:
channels:
- defaults
- conda-forge
- pytorch
dependencies:
- blas~=1.0
- bzip2~=1.0.8
- ca-certificates~=2020.10.14
- certifi~=2020.6.20
- cloudpickle~=1.6.0
- cudatoolkit~=11.1.1
- cycler~=0.10.0
- cytoolz~=0.11.0
- dask-core~=2021.2.0
- decorator~=4.4.2
- ffmpeg~=4.3
- freetype~=2.10.4
- gmp~=6.2.1
- gnutls~=3.6.13
- imageio~=2.9.0
-...

Maybe the ~= is breaking the conda "magic" version resolver

FreshKangaroo33 you can:
from time import time Task.query_tasks(..., task_filter=dict(started=['<{}'.format(datetime.utcfromtimestamp(time())), ]))I think this should work

Even if you had any packages, I'm pretty sure there is nothing for you to worry about, it will just list them, and if they are preinstalled, the preinstalled will be used