An improved Lightning mlflow logger. Works seamlessly with PyTorch Lightning on Databricks and offers more control compared to the mlflow.pytorch.autolog
function.
- Makes
MLflow
logging work withlightning
and Databricks
With pip
:
python -m pip install lit-mlflow
With poetry
:
poetry add lit-mlflow
Replace mlflow.autolog()
with the MlFlowAutoCallback
:
from lit_mlflow import MlFlowAutoCallback
import lightning.pytorch as pl
trainer = pl.Trainer(
callbacks=[
MlFlowAutoCallback()
]
)
To support Databricks mlflow, use the DbxMLFlowLogger
instead of the MlFlowLogger
:
from lit_mlflow import DbxMLFlowLogger
import lightning.pytorch as pl
trainer = pl.Trainer(
logger=[
DbxMLFlowLogger()
]
)
poetry run mkdocs build -f ./docs/mkdocs.yml -d ./_build/
copier update --trust -A --vcs-ref=HEAD