Thanks, I got that issue resolved

So, one of my tasks requires GCP credentials json file, is there a way that I can pass in the json file and set the environment variable for that?

Ok I'll try that out, enable_git_ask_pass: true is not working

File "/opt/conda/envs/bumlo/lib/python3.10/site-packages/clearml/binding/artifacts.py", line 745, in upload_artifact
pickle.dump(artifact_object, f)
_pickle.PicklingError: Can't pickle <class 'mongoengine.base.metaclasses.samples.6627e5ecc60879fe5e49cee6'>: attribute lookup samples.6627e5ecc60879fe5e49cee6 on mongoengine.base.metaclasses failed

dataset = fo.Dataset.from_dir(
labels_path=labels_path,
dataset_type=fo.types.COCODetectionDataset,
label_field="ground_truth",
use_polylines=True
)
task.upload_artifact(
name="Dataset",
artifact_object=dataset,
)

My git repo only contains the hash-ids which are used to download the dataset into my local machine

One more thing in my git repo there is a dataset folder that contains hash-ids, these hash-ids are used to download the dataset. When I am running the pipeline remotely the files/images are downloaded in the cloned git repo inside the .clearml/venvs but when I check inside that venvs folder there are not images present.

So the issue I am facing is, I am running the pipeline controller task on my local system agent and the steps of the pipeline on an agent running on GCP VM, the first step of the pipeline is failing showing clearml_agent: ERROR: Failed cloning repository.

Do I need not make changes into clearml.conf so that it doesn't ask for my credentials or is there another way around

I have a pipeline which I am able to run locally, the pipeline has a pipeline controller along with 4 tasks, download data, training, testing and predict. How do I run execute this whole pipeline remotely so that each task is executed sequentially?

Can you explain how running two agents would help me run the whole pipeline remotely? Sorry if its a very basic question

Is there a way to clone the whole pipeline, just like we clone tasks

Okk, thanks!

because when I was running both agents on my local machine everything was working perfectly fine

While creating a GCP credentials using None
What values should I insert in the following step so that the autoscaler has access, as of now I left this field blank

while we spin up the autoscaler instance

Note: switching to 'commit_id'.
You are in 'detached HEAD' state. You can look around, make experimental
changes and commit them, and you can discard any commits you make in this
state without impacting any branches by switching back to a branch.
If you want to create a new branch to retain commits you create, you may
do so (now or later) by using -c with the switch command. Example:
git switch -c <new-branch-name>
Or undo this operation with:
git switch -
Turn off this advice by setting ...

Ok I was able to resolve the above issue, but now I am getting the following error while executing a task

import cv2
File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/cv2/init.py", line 181, in <module>
bootstrap()
File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/cv2/init.py", line 153, in bootstrap
native_module = importlib.import_module("cv2")
File "/usr/lib/python3.8/importlib/init.py", line 127, in import_module
return _boots...

I provided the credentials while setting up the autoscaler instance, where can I look for the clearml.conf. When I ssh into the instance, spin up by the autoscaler, I am not able to see the clearml.conf

So funny thing I was making a typo while writing the GPU type, I was writing NVIDIA T4 instead of nvidia-tesla-t4

Let me know if this is enough information or not

I don't think it has issues with this

Can you tell me how clearml get access to my repo even if I didn't pass any information about it?

I am uploading the dataset (for Yolov8 training) as an artifact, when I am downloading the artifact (.zip file) from the UI the path to images is something like /Users/adityachaudhry/.clearml/cache/......, but when I am doing .get_local_copy() I am getting the local folder structure where I have my images locally in my system as path. For running the pipeline remotely I want the path to be like /Users/adityachaudhry/.clearml/cache/......

So I am running a pipeline on a GCP VM, my VM has 1 NVIDIA GPU, and my requirements.txt has torch==1.13.1+cu117
torchvision==0.14.1+cu117

When I am running the Yolo training step I am getting the above error.

I want to understand what's happening at the backend. I want to know how running the pipeline logic and the tasks on separate agents gonna sync everything up

When the package installation is done in the task

@<1523701205467926528:profile|AgitatedDove14> I was able to resolve that, but now I am having issues with fiftyone, it's showing me the following error

import fiftyone as fo
File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/fiftyone/init.py", line 25, in <module>
from fiftyone.public import *
File "/root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages/fiftyone/public.py", line 15, in <module>
_foo.establish_db_conn(config)
File "/root/.clearml...