Dynamic Versioning¶
Overview¶
The Dynamic Versioning system in Fine-Tuning Scheduler (FTS) enables constrained self-modification of
the finetuning-scheduler package itself. The initial application of this feature is to dynamically orchestrate
management of Lightning package imports, making it easy to switch between the unified lightning package and the
standalone pytorch-lightning package.
This feature is particularly useful for:
Adapting existing code to work with different Lightning package import styles
Testing compatibility with both unified and standalone Lightning
Migrating projects from one import style to another
Toggling Lightning Import Styles¶
After installing FTS, you can switch between unified and standalone imports using the toggle-lightning-mode
command-line tool:
# Switch to standalone imports (pytorch_lightning)
toggle-lightning-mode --mode standalone
# Switch back to unified imports (lightning.pytorch)
toggle-lightning-mode --mode unified
The tool performs the following actions:
Checks if the requested package is installed
Scans all Python files in the FTS package
Updates import statements to match the requested style
Preserves functionality while changing only the import paths
Note
You must have the target package installed before toggling. For example, to toggle to unified mode,
the lightning package must be installed, and to toggle to standalone mode, the pytorch-lightning
package must be installed.
Implementation Details¶
The dynamic versioning system:
Uses pattern matching to identify Lightning imports
Excludes certain files from modification to prevent self-modification
Supports both source and installed package directories
Automatically handles all import variations (direct imports, from imports, etc.)
The conversion operations are individually idempotent and mutually reversible, making it safe to run the toggle command multiple times.
Using Lightning CI Commit Pinning¶
For development and testing, FTS supports pinning to a specific Lightning commit via the USE_CI_COMMIT_PIN
environment variable. This approach is similar to PyTorch’s approach with Triton:
# Enable Lightning CI commit pinning during installation
export USE_CI_COMMIT_PIN="1"
# Install FTS with pinned Lightning commit
pip install finetuning-scheduler
# Or for development installation
git clone https://github.com/speediedan/finetuning-scheduler.git
cd finetuning-scheduler
python -m pip install -e ".[all]"
The specific Lightning commit is defined in requirements/lightning_pin.txt and is used by the CI system to
ensure consistent testing.
