Hi @<1523701070390366208:profile|CostlyOstrich36> ,
The idea is indeed to control the object via API, but in that particular case, if I don't want the seed to be specified by the API but just set it to be current timestamp.
Could you think of a better use?

Anyway, when I add the binary's path to PATH, it still won't work.
I call
task.set_base_docker(docker_image='my/docker/image', docker_setup_bash_script= ["export PATH=""/workspace/miniconda/bin:$PATH"])just after Task.init.
On execution, the agent installs all pip requirements with python binary at /usr/bin/python3.6
but eventually the task fails with, /workspace/miniconda/bin/python3: No module named clearml_agent

Yes.

Its kwcoco

This is my conda env export :
name: clearml
channels:

• defaults
  dependencies:
• ca-certificates=2021.10.26=hecd8cb5_2
• certifi=2021.10.8=py39hecd8cb5_0
• libcxx=12.0.0=h2f01273_0
• libffi=3.3=hb1e8313_2
• ncurses=6.3=hca72f7f_2
• openssl=1.1.1l=h9ed2024_0
• pip=21.2.4=py39hecd8cb5_0
• python=3.9.7=h88f2d9e_1
• readline=8.1=h9ed2024_0
• setuptools=58.0.4=py39hecd8cb5_0
• sqlite=3.36.0=hce871da_0
• tk=8.6.11=h7bc2e8c_0
• tzdata=2021e=hda174b...

SweetBadger76
It’s not a credential issue, because I do upload artifacts manually with tsk.upload_artifact(...)
I’ll try changing the extension, but I have to admit that in the past (I havn’t used clearml for a while and updated it recently to the latest verion) it did got this file extension right

AgitatedDove14 , here's the log

AgitatedDove14
It was installed by 'pip install kwcoco' while my conda env was active.
Not sure if it answers your question..

Its mounted automatically.
The local .ssh folder is copied to a temp folder which is mounted by the agent in the docker run command -
Executing: ['docker', 'run', '-t', ......., '-v', '/tmp/clearml_agent.ssh.fuu4r8ta:/root/.ssh', .... , '--rm', 'nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04', ....]

This is actually in runtime (i.e. when running the code),

My script looks like that
` import clearml
clearml.Task.force_requirements_env_freeze(force=False, requirements_file="requirements.txt")
task = clearml.Task.init(...)
task.set_script(working_dir=dir, entry_point="my_script.py")
task.execute_remotely(queue_name='default')

rest of script goes here.... `When you refer to runtime, do you mean when the script is executed remotely, or when I run my_script.py locally (in order to ...

what does that actually mean?
2022-07-17 07:59:40,339 - clearml.storage - ERROR - Failed uploading: Parameter validation failed: Invalid type for parameter ContentType, value: None, type: <class 'NoneType'>, valid types: <class 'str'>

Thanks ExasperatedCrab78
AgitatedDove14 - attached

AgitatedDove14 its running inside a docker based worker.
Are you interested in the full pip freeze of that docker?

That would be a very useful feature.
What is the status of that issue? I havn't found it on github.

After signing with google, the login page is stuck at this

UnevenDolphin73 Thanks! Ill look into and reach out if needed

/mnt/clearml_storage is the mount point of the NAS on one linux machine.
On macos it would be /Volumes/clearml_storage,
On windows - //NAS/clearml_storage

Oh wow AgitatedDove14 . Appreciate it!
Are you sure it’s just a matter of the python version?
The same experiment script, was working on the exact docker image in the past (with older clearml versions though…).
For example this experiment log:

And I'm using the latest clearml / clearml-agent
@<1523701070390366208:profile|CostlyOstrich36>

AgitatedDove14 , did you test it using a worker, or with local execution?
I just tested https://github.com/allegroai/clearml/blob/master/examples/frameworks/pytorch/pytorch_mnist.py with a (docker based) worker and it yields the same error
` 2022-07-17 07:59:40,330 - clearml.Task - INFO - Waiting to finish uploads
2022-07-17 07:59:40,330 - clearml.storage - INFO - Starting upload: /tmp/.clearml.upload_model_0_4d_ikk.tmp => tapsff.local:9000/clearml/examples/PyTorch MNIST train.02ed1df11bf54...

Thanks

AgitatedDove14 Yes, thats correct.
It's in my local conda environment though.

Why do you have this part? isn’t it the same code, the script entry point is auto detected ?

Because I don’t always run the script locally from it’s directory and I have additional modules in the same directory that I import.

Sure this will work

I’ll make sure to update it

Thanks

So I run the same script as part of a git repo - but unfortunately the package is still missing.
I'm not sure if it matters but 'kwcoco' is being imported inside one of the repo's functions and not on the script's header.

Thanks

AgitatedDove14
I'm not sure.
In my case I'm not trying to reproduce a local environment in the agent, but to run a script inside a docker which already has the environment built in.
The environment is conda based.

No. But this isn't the only package that was installd using pip inside a conda env.
Compare it with Pandas as an example - was installed using pip nad it's actually instaled inside the worker as well (using pip).

CLEARML-AGENT version 1.1.1
conda 4.8.4

Yes you are right.
This is the default docker image from clearml, and I was thinking that the agent will install conda if it's not already there (like it installs pip...) Isn't it?

It didn't work either. Still same error.
conda command was already in PATH and the conda activate is executed properly, but it prompts to run conda init (i.e conda wasn't configures at that shell):
` You should consider upgrading via the '/usr/bin/python3 -m pip install --upgrade pip' command.
CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'.
To initialize your shell, run
$ conda init <SHELL_NAME>
Currently supported shells are:

• ba...

AgitatedDove14 .
Note that the actual error is /workspace/miniconda/bin/python3: No module named clearml_agent since all the packages (including clearml_agent) were already installed by the agent on the default (non conda) python binary.