Full Changelog: https://github.com/OpenBMB/BMTrain/compare/0.2.0...0.2.3
Before 0.2.3, the installation of BMTrain requires the torch cpp extension, which is not friendly to some users (it requires CUDA Runtime fits with torch). Now we get rid of the torch cpp extension when compiling BMTrain, which makes the source-code way installation of BMTrain more convenient.
Just run pip install .
to install BMTrain using source code.
In 0.2.3, we bring the Github action CICD to BMTrain. Now we can run the CI/CD pipeline on Github to ensure the quality of the code. CICD will run the test cases and compile the source code into wheel packages.
In 0.2.3, we add the min and max loss scale to the loss scale manager. The loss scale manager can adjust the loss scale dynamically according to the loss scale's min and max value. This feature can help users to avoid the loss scale being too large or too small.
- Fix
bmt.load(model)
OOM when meets torch >= 1.12 AdamOffloadOptimizer
can choose avx flag automatically in runtime- Now BMTrain is fully compatible with torch 2.0