Also I just want to say thanks for all the help. And this tool is brilliant how it supports an end to end pipeline in this completely new space for MLOps. You guys have been incredibly helpful and what you've made is incredible.

They want to start integrating MLOps into the ML projects here at our company for reproducibility and continual training. ClearML popped up as a potential option so they want me to design a complete pipeline for one of our projects currently being worked on. They're ...

Understandable.

I'll create a github issue. Overall I hope you understand.

I did this but this gets me an InputModel. I went through the InputModel class but I'm still unsure how to get the actual tensorflow model.

Not sure myself. I have a pipeline step now, that'll return either clearml dataset id or -1. I want to stop the pipeline execution if I get -1 in the output of that step but I'm not sure how to achieve that

I'm assuming

I download the dataset and model, and load them. Before training them again.

For anyone who's struggling with this. This is how I solved it. I'd personally not worked with GRPC so I instead looked at the HTTP docs and that one was much simpler to use.

I'll take a look.

The situation is such that I needed a continuous training pipeline to train a detector, the detector being Ultralytics Yolo V5.

To me, it made sense that I would have a training task. The whole training code seemed complex to me so I just modified it just a bit to fit my needs of it getting dataset and model from clearml. Nothing more.

I think created a task using clearml-task and pointed it towards the repo I had created. The task runs fine.

I am unsure at the details of the training code...

Any way to make it automatically install any packages it finds that it requires? Or do I have to explicitly pass them in packages?

SuccessfulKoala55 Sorry to ping you like this. I have to ask. What's the minimum requirements for clear ml installation. Excluding requirements for databases or file server

The server is on a different machine. I'm experimenting on the same machine though.

Even though I ended my schedulers and triggers, the anonymous tasks keep increasing.

Thank you, I'll start reading up on this once I've finished setting up the basic pipeline

keeps retrying and failing when I use Dataset.get

I'm getting this error.

clearml_agent: ERROR: Failed cloning repository.

1. Make sure you pushed the requested commit:
2. Check if remote worker has valid credentials

You mean I should set it to this?

Thanks for the help.

So I got my answer, for the first one. I found where the data is stored in the server

I've tried the ip of the ClearML Server and the IP of my local machine on which the agent is also running on and none of the two work.

then I use trigger_scheduler.start()

I'm currently installing nvidia docker on my machine, where the agent resides. I was also getting an error regarding gpu not being available in docker since the agent was running on docker mode. I'll share update in a bit. Trying to re run the whole set up

Can you please share the endpoint link?

Yeah, I kept seeing the message but I was sure there were files in the location.

I just realized, I hadn't worked with the Datasets api for a while and I forgot that I'm supposed to call add_files(location) and then upload, not upload(location). My bad.

Ok this worked. Thank you.

TimelyPenguin76 Bump

Alright, but is it saved as a text file or pickle file?

This is the simplest I could get for the inference request. The model and input and output names are the ones that the server wanted.

And given that I want have artifacts = task.get_registered_artifacts()