You could be right, I just had a couple of packages with this issue so I just removed the version requirement for now. Another issue that might be the case, might be that I'm on ubuntu some of the packages might've been for windows thus the different versions not existing

It was nargs="?" I think

I've also mentioned it on the issue I created but I had the issue even when I set the type to bool in parser.add_argument(type=bool)

Yeah

Alright. Can you guide me on how to edit the task configuration object? Is it done via the UI or programatically? Is there a config file and can it work with any config file I create or is it a specific config file? Sorry for the barrage of questions.

This is the task scheduler btw which will run a function every 6 hours.

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

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

I'll look into it. Thank you everyone.

{"meta":{"id":"c3edee177ae348e5a92b65604b1c7f58","trx":"c3edee177ae348e5a92b65604b1c7f58","endpoint":{"name":"","requested_version":1.0,"actual_version":null},"result_code":400,"result_subcode":0,"result_msg":"Invalid request path /","error_stack":null,"error_data":{}},"data":{}}

Basically when I have to re run the experiment with different hyperparameters, I should clone the previous experiment and change the hyperparameters then before putting it in the queue?

I've finally gotten the triton engine to run. I'll be going through nvidia triton docs to find how to make an inference request. If you have an example inference request, I'll appreciate if you can share it with me.

Quick follow up question. Once I parse args, should they be directly available for i even enque the project for the first time or will i be able to access hyperparameters after running it once?

I followed the instructions here at https://allegro.ai/clearml/docs/docs/deploying_clearml/clearml_server_linux_mac.html

If it helps, I can try and record my steps in a video.

Ok so update. It works now. last steps I did I can remember to fix it are.

Or is there any specific link you can recommend to try and create my own server.

Also my execution just completed and as of yet, I can only see the hyperparameters as a report. not in a configurable form. I've just started with ClearML and am having these issues.

I just copied the commands in order from the page and pasted them. All of the linux ones specifically.

the one mentioned on the page.

Thank you for the help.

This is the original repo which I've slightly modified.

I'm using clear-ml agent right now. I just upload the task inside a project. I've used arg parse as well however as of yet, I have not been able find writable hyperparameters in the UI. Is there any tutorial video you can recommend that deals with this or something? I was following https://www.youtube.com/watch?v=Y5tPfUm9Ghg&t=1100s this one on youtube but I can't seem to recreate his steps as he sifts through his code.

when i pass the repo in clearml-task with the parameters, it runs fine and finishes. Basically when I clone and attempt the task again, I get the above assert error I don't know why.

Anyway in the resume argument, there is a default=False however const=True, what's up with that, or is const a separate parameter

so when I run the task using clearml-task --repo and create a task, it runs fine. It runs into the above error when I clone the task or reset it.

I'm dumping a dict to json, how can i register that dict as an artifact

Basically if I pass an arg with a default value of False, which is a bool, it'll run fine originally, since it just accepted the default value.

is this the correct way to upload an artifact?

checkpoint.split('.')[0] is the name that I want it assigned and the second argument is the path to the file.

Thus I wanted to pass the model id from the prior step to the next one.