1.4.0

1.4.0

Bug Fixes

• Registry: Fix a bug when multiple models are being called from the same query, models other than the first one will
  have incorrect result. This fix only works for newly logged model.
• Modeling: When registering a model, only method(s) that is mentioned in save_model would be added to model signature
  in SnowML models.
• Modeling: Fix a bug that when n_jobs is not 1, model cannot execute methods such as
  predict, predict_log_proba, and other batch inference methods. The n_jobs would automatically
  set to 1 because vectorized udf currently doesn't support joblib parallel backend.
• Modeling: Fix a bug that batch inference methods cannot infer the datatype when the first row of data contains NULL.
• Modeling: Matches Distributed HPO output column names with the snowflake identifier.
• Modeling: Relax package versions for all Distributed HPO methods if the installed version
  is not available in the Snowflake conda channel
• Modeling: Add sklearn as required dependency for LightGBM package.

Behavior Changes

• Registry: apply method is no longer by default logged when logging a xgboost model. If that is required, it could
  be specified manually when logging the model by log_model(..., options={"target_methods": ["apply", ...]}).

New Features

• Registry: Add support for sentence-transformers model (sentence_transformers.SentenceTransformer).
• Registry: Now version name is no longer required when logging a model. If not provided, a random human readable ID
  will be generated.