How do I reproduce it? When I use add_step with the wrong parameter it throws an exception before the pipeline even starts ...

Notice both needs to be str
btw, if you need the entire folder just use StorageManager.upload_folder

ShallowCat10 try something similar to this one, due notice that it might take a while to get all the task objects, so I would start with a single one 🙂

`
from trains import Task
tasks = Task.get_tasks(project_name='my_project')
for task in tasks:
scalars = task.get_reported_scalars()
for x, y in zip(scalars['title']['original_series']['x'], scalars['title']['original_series']['y']):
task.get_logger().report_scalar(title='title', series='new_series', value=y, iteration=...

You might be able to write a script to override the links ... wdyt?

Hi @<1542316991337992192:profile|AverageMoth57>
is this a follow up of this thread? None

Hi AstonishingSwan80 , what do you mean by "ec2 API"?

• but the

pytorch/main.py

file doesn't run.

What do you have on the Task itself? is this the correct script ?
Any chance you can send a full log ? (you can DM it if it helps)

(This code sample should work on your setup with your installed packages without a problem)

It is available of course, but I think you have to have clearmls-server 1.9+
Which version are you running ?

but this is not different from not using clearml-data,

ReassuredTiger98 just making sure we are on the same page. clearml-data immutability is fixed, the user cannot change the content of the dataset (it is actually compressed and uploaded). If you want to change it, you create a new child version

@<1523705099182936064:profile|GrievingDeer61> if you see them in your Tensorboard they will be captured in ClearML as well.
wdyt?

EDIT
examples (tensorboard or tensorboardX):
None
None

(Caused by SSLError(SSLError(1, '[SSL: DECRYPTION_FAILED_OR_BAD_RECORD_MAC] decryption failed or bad record macWhere is the code running (agent) GCP instance ? your machine ?

@<1523707653782507520:profile|MelancholyElk85> I just run a single step pipeline and it seemed to use the "base_task_id" without cloning it...
Any insight on how to reproduce ?

I wonder if this hack would work
Assume you upload an artifact/model to ' s3://storage.yandexcloud.net:443/clearml-models ' notice the port is added. Would that trigger a popup in the UI?
Also what happens if you add tge credential manually in the profile page?

@<1542316991337992192:profile|AverageMoth57> it sounds like you should use SSH authentication for the agent, just set
force_git_ssh_protocol: true
None
And make sure you have the SSH kets on the agent's machine

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

default is clearml data server

Yes the default is the clearml files server, what did you configure it to ? (e.g. should be something like None )

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)

ssh: Could not resolve hostname

: Name or service not known

@<1542316991337992192:profile|AverageMoth57> so is this the main issue? this seems unrelated to the Gerrit thing, just missing configuration of the .ssh on the agent machine, is that correct?

The pipeline itself is also a task, so this line works in a pipeline. Task.current_task is a class method that returns the running task (pipeline in our case), then then the usual interface. BTW what are you having in the conf file ?

PanickyAnt52 when the docker is loaded, it will search for the highest python version to use for the agent. Then when it is launching the Task itself, it will first try to match the python version requested by the Task. It does so by looking for "python3.7" ,
what are you getting when running "which python3.7" inside the docker ? Could it be you have a venv inside the docker with the diff python version ?

Hi FierceHamster54
Sure just do
dataset = Dataset.get(dataset_project="project", dataset_name="name")This will by default fetch the latest version

Hi MistakenDragonfly51

Is it possible to use it without using the clearml agent system?

Yes it is, which would mean everything is executed locally
basically:
an_optimizer.start_locally()instead of this line
https://github.com/allegroai/clearml/blob/51af6e833ddc5a8ba1efaaf75980f58616b25e85/examples/optimization/hyper-parameter-optimization/hyper_parameter_optimizer.py#L121

Since pytorch is a special example (the agent will pick the correct pytorch based on the installed CUDA) , the agent will first make sure the file is downloaded, and then pass the resolving for pip to decide if it necessary to install. (bottom line, we downloaded the torch for no reason but it is cached so no real harm done) It might be the second package needs a specific numpy version... this resolving is don't by pip, not the agent specifically. Anyhow --system-site-packages is applicable o...

Maybe we should add it to Storage Manager? What do you think?

GrievingTurkey78 did you open the 8008 / 8080 / 8081 ports on your GCP instance (I have to admit I can't remember where exactly in the admin panel you do that, but I can assure you it is there :)

YEY! 🚀 🎉

current task fetches the good Task

Assuming you fork the process than the gloabl instance" is passed to the subprocess. Assuming the sub-process was spawned (e.g. POpen) then an environement variable with the Task's unique ID is passed. then when you call the "Task.current_task" it "knows" the Task was already created and it will fetch the state from the clearml-server and create a new Task object for you to work with.
BTW: please use the latest RC (we fixed an issue with exactly this...

FlatStarfish45

In the parent task, the libs appear installed.

What do you mean by "parent Task"? Is this the base task we are optimizing (i.e. the experiment / model we are optimizing) ?
Or is it the "Optimization Task" itself?

Hi TenseOstrich47
Does the .ssh folder on the user running the agent contain the correct credentials ?
Basically from the user running the agent on the agent's machine can you clone the repo with:
ssh://git@github.com/15gifts/py-db.git