I see, so basically fix old links that are now not accessible? If this is the case you might need to manually change the document on the mongodb running in the backend

hurray 🎊

Sure. JitteryCoyote63 so what was the problem? can we fix something?

Hi UnsightlySeagull42
Just making sure, the two scripts are on your git repo ?

Hi @<1590514584836378624:profile|AmiableSeaturtle81>
I think you should use add_external_files , instead of add_files (which is for local files)
None

Yes, but does add_external_files makes chunked zips as add_files do?

No it references them, (i.e. meta-data not actually doing something with the files themselves)

I need the zipping, chunking to manage millions of files

That makes sens, if that's the case you will have to download those files anyway, and then add them with add_files
you can use the StoargeManager to download them, and then add them from the local copy (this will zip/chunk them)
[None](https://clear.ml/docs/la...

You put it there 🙂 so the assumption you know what you are looking for, or use glob? wdyt?

Hurray!

This is assuming you can just run two copies of your code, and they will become aware of one another.

Okay that means it is running in virtual environment mode.
On the original Task (the one you enqueued) what were the installed packages (specifically the torch/torchvision) ?

, I need to understand it what happens when I press "Enqueue" In web UI and set it to default queue

The Task ID is pushed into the execution queue (from the UI / backend that is it), Then you have clearml-agent running on Your machine, the agent listens on queue/s and pulls jobs from queue.
It will pull the Task ID from the queue, setup the environment according to the Task (i.e. either inside a docker container or in a new virtual-env), clone the code/apply uncommitted changes ...

Hmm, maybe the original Task was executed with older versions? (before the section names were introduced)
Let's try:
DiscreteParameterRange('epochs', values=[30]),Does that gives a warning ?

check if the fileserver docker is running with docker ps

Yep that makes sense to me too. Done

GiddyTurkey39 Just making sure, you ran ping IP not ping ip:port right ?

size 0

Hi ZippySheep23

Any ideas what might be happening?

I think you passed the upload limit (2.36 GB) 🙂

BTW:
This is very odd "~/.clearml/venvs-builds.3/3.6/bin/python" it thinks it is using "python 3.6" but it is linked with python 2.7 ...
No idea how that could happen

Could you maybe send a screenshot? This is very strange? Also what's the trains version?

My pleasure 🙂

is there a way that i can pull all scalars at once?

I guess you mean from multiple Tasks ? (if so then the answer is no, this is on a per Task basis)

Or, can i get experiments list and pull the data?

Yes, you can use Task.get_tasks to get a list of task objects, then iterate over them. Would that work for you?
https://clear.ml/docs/latest/docs/references/sdk/task/#taskget_tasks

Won't it be too harsh to have system wide restriction like that ?

to add an init script or to expand its capacity,

@<1546665634195050496:profile|SolidGoose91> I seem to see it in the wizard here, what am I missing?

try these values:

os.environ.update({
    'CLEARML_VCS_COMMIT_ID': '<commit_id>',
    'CLEARML_VCS_BRANCH': 'origin/master',
    'CLEARML_VCS_DIFF': '',
    'CLEARML_VCS_STATUS': '',
    'CLEARML_VCS_ROOT': '.',
    'CLEARML_VCS_REPO_URL': '

',
})

task = Task.init(...)

IrateBee40 I think I have an idea what's wrong, https could it be there is some firewall in the middle intercepting the entwork, and without installing SSL certificate the ssl connection is failing ?

The base task is self-contained i.e. it downloads training/eval directly data and has direct access to it

I think this is the main issue, how come it does not catch it? Are you using argparser ?

A few examples:
https://medium.com/@Sushil_Kumar/readwritemany-persistent-volumes-in-google-kubernetes-engine-a0b93e203180
https://docs.openshift.com/enterprise/3.1/install_config/storage_examples/shared_storage.html

Meaning the node restarted (or actually moved)

Hi SubstantialElk6
I think you are absolutely correct, it seems the glue pops all the arguments, when in fact it should maybe process them a,d convert the --env/-e
What do you think?
Aloso I assume if these are the default arguments they should actually be part of the k8s apply.yaml template no ?

Hi FiercePenguin76
https://allegro.ai/clearml/docs/rst/references/clearml_python_ref/model_module/model_outputmodel.html
Basically:
from clearml import OutputModel model = OutputModel() model.update_weights(weights_filename='local_file_here.bin')