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Train different tasks at same time #20
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Hello @acai66, thank you for your interest in our work! Please visit our Custom Training Tutorial to get started, and see our Google Colab Notebook, Docker Image, and GCP Quickstart Guide for example environments. If this is a bug report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom model or data training question, please note that Ultralytics does not provide free personal support. As a leader in vision ML and AI, we do offer professional consulting, from simple expert advice up to delivery of fully customized, end-to-end production solutions for our clients, such as:
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@acai66 yes you make a good point. We use multiple docker containers on a single machine to exploit multiple single-gpu trainings simultaneously. Without docker containers you might simply copy the directory, one per gpu. For a more comprehensive solution, we might be better off depositing all run-related items (jpgs, results.txt, checkpoints etc.) into the unique ./runs directory already created automatically by tensorboard when a training run starts. What do you think? |
good idea, thanks |
The unique directory is defined in Lines 394 to 399 in b810b21
tb_writer.log_dir
Out[3]: 'runs/Jun07_09-10-55_Glenns-MBP.attlocal.net' |
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. |
speed up evaluation
🚀 Feature
Train different tasks at same time.
Motivation
there always are multi gpu in a machine, We should have been able to train different models at same time, but outputs and results are stored in same directory now, it may be conflict.
Pitch
split outputs and results include weights in separate directories.
Alternatives
Additional context
I made a temporary change to
train.py
so i can train different tasks, but i really hope this funiction will be official support.tkanks.
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