1.47.0
New Features
- Experiment Tracking: Added
ExperimentTracking.list_model_versions to retrieve the model versions that were
logged under a run. Models logged via log_model inside a run are linked to that run through Snowflake lineage,
and this method traverses that lineage to return the corresponding ModelVersion objects.
from snowflake.ml.experiment import ExperimentTracking
exp = ExperimentTracking(session)
exp.set_experiment("MY_EXPERIMENT")
with exp.start_run(run_name="MY_RUN"):
exp.log_model(model, model_name="MY_MODEL", sample_input_data=X)
model_versions = exp.list_model_versions(run_name="MY_RUN")
Bug Fixes
- Experiment Tracking: Fix a bug where
.set_experiment does not recreate an experiment deleted in Snowsight
Behavior Changes
- Registry:
enable_explainability now defaults to False for all model types when logging a model. Previously it
defaulted to True for XGBoost, LightGBM, and CatBoost models and was auto-enabled for supported scikit-learn and
Snowpark ML modeling models when running in the Warehouse. To generate an explain method, explicitly pass
options={"enable_explainability": True} to log_model (this requires sample_input_data for supported model
types).
Deprecations