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When Use Gcp Bucket As Files_Server + Yolov5 Train For Now Its Upload The Model In The End To

when use gcp bucket as files_server + yolov5 train
for now its upload the model in the end to
is there option to omit the task_id so the final output will be deterministic and know prior to the task run?


Posted one year ago
Votes Newest

Answers 6

Hi AstonishingRabbit13

is there option to omit the task_id so the final output will be deterministic and know prior to the task run?

Actually no 😞 the full path is unique for the run, so you do not end up overwriting models.
You can get the full path from the UI (Models Tab) or programmatically with Models.query_models or using the Task.get_task methods.
What's the idea behind a fixed location for the model?

Posted one year ago

so other process can use it

This is why there is a model repository, so you can query the last model created, or by name or tag or query the Task that created it and then via the Task the model and it's location.
This is a stable way to make sure your application code (the one using the model) will get to use stable models regardless of the training processes.
I would add a Tag to the model and then search based on the project and the tag, wdyt?

Posted one year ago

Hi Martin
thanks for the quick replay

the use is fixed path for the end model on the bucket after the training
so other process can use it

Posted one year ago

Yes, or at least credentials and API...
Maybe inside your code you can later copy the model into fixed location ?
This way you have the model in the model repository and a copy in a fixed location (StorageManager can upload to a specific bucket/folder with the same credentials you already have)
Would that work?

Posted one year ago

yes but that’s mean that the app that use the model needs clearml also..

Posted one year ago

i need to think about that..
anyway thanks a lot

Posted one year ago
6 Answers
one year ago
one year ago