An improved Lightning mlflow logger. Works seamlessly with PyTorch Lightning on Databricks and offers more control compared to the mlflow.pytorch.autolog function.
- Makes
MLflowlogging work withlightningand Databricks
With pip:
python -m pip install lit-mlflowWith poetry:
poetry add lit-mlflowReplace 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