Multi-Platform Configuration Synchronization Solution
When migrating between Linux/Windows:
- Environmental standardization::
- Unified use of Python 3.10+ and CUDA 12.1
- pass (a bill or inspection etc)
pip freeze > requirements.txtGenerate precise dependencies
- path conversion::
- Change the path in the configuration file to a relative path (e.g.
./dataset/) - utilization
os.path.join()Compatible with different system slashes
- Change the path in the configuration file to a relative path (e.g.
- special handling::
- Windows requires additional installation
Visual C++ 14+Building Tools - Linux needs to be set up
LD_LIBRARY_PATHIncludes CUDA library paths
- Windows requires additional installation
Recommended Tool:
1. Packaging the training environment with Docker containers
2. Adoptionconda env export > environment.ymlCreating cross-platform environments
This answer comes from the articleAI Toolkit by Ostris: Stable Diffusion with FLUX.1 Model Training ToolkitThe
May not be reproduced without permission:AI productivity tools " How do you achieve cross-platform migration of training configurations?
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