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GitOrigin-RevId: d17260ac6975c1e08f99814664db8e67f613b37e Co-authored-by: Snowflake Authors <[email protected]>
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# Release History | ||
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## 1.0.1 (2023-06-16) | ||
### Behavior Changes | ||
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- Model Development: Changed Metrics APIs to imitate sklearn metrics modules: | ||
- `accuracy_score()`, `confusion_matrix()`, `precision_recall_fscore_support()`, `precision_score()` methods move from respective modules to `metrics.classification`. | ||
- Model Registry: The dafault table/stage created by the Registry now uses "_SYSTEM_" as a prefix. | ||
- Model Registry: `get_model_history()` method as been enhanced to include the history of model deployment. | ||
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### New Features | ||
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- Model Registry: A default `False` flag named `replace_udf` has been added to the options of `deploy()`. Setting this to `True` will allow overwrite existing UDF with the same name when deploying. | ||
- Model Development: Added metrics: | ||
- f1_score | ||
- fbeta_score | ||
- recall_score | ||
- roc_auc_score | ||
- roc_curve | ||
- log_loss | ||
- precision_recall_curve | ||
- Model Registry: A new argument named `permanent` has been added to the arguemnt of `deploy()`. Setting this to `True` allows the creation of a permanent deployment without needing to specify the UDF location. | ||
- Model Registry: A new method `list_deployments()` has been added to enumerate all permanent deployments originating from a specific model. | ||
- Model Registry: A new method `get_deployment()` has been added to fetch a deployment by its deployment name. | ||
- Model Registry: A new method `delete_deployment()` has been added to remove an existing permanent deployment. | ||
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## 1.0.0 (2023-06-09) | ||
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### Behavior Changes | ||
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- Model Registry: `predict()` method moves from Registry to ModelReference. | ||
- Model Registry: `_snowml_wheel_path` parameter in options of `deploy()`, is replaced with `_use_local_snowml` with default value of `False`. Setting this to `True` will have the same effect of uploading local SnowML code when executing model in the warehouse. | ||
- Model Registry: Removed `id` field from `ModelReference` constructor. | ||
- Model Development: Preprocessing and Metrics move to the modeling package: `snowflake.ml.modeling.preprocessing` and `snowflake.ml.modeling.metrics`. | ||
- Model Development: `get_sklearn_object()` method is renamed to `to_sklearn()`, `to_xgboost()`, and `to_lightgbm()` for respective native models. | ||
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### New Features | ||
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- Added PolynomialFeatures transformer to the snowflake.ml.modeling.preprocessing module. | ||
- Added metrics: | ||
- accuracy_score | ||
- confusion_matrix | ||
- precision_recall_fscore_support | ||
- precision_score | ||
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### Bug Fixes | ||
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- Model Registry: Model version can now be any string (not required to be a valid identifier) | ||
- Model Deployment: `deploy()` & `predict()` methods now correctly escapes identifiers | ||
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## 0.3.2 (2023-05-23) | ||
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### Behavior Changes | ||
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- Use cloudpickle to serialize and deserialize models throughout the codebase and removed dependency on joblib. | ||
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### New Features | ||
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- Model Deployment: Added support for snowflake.ml models. | ||
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## 0.3.1 (2023-05-18) | ||
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### Behavior Changes | ||
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- Standardized registry API with following | ||
- Create & open registry taking same set of arguments | ||
- Create & Open can choose schema to use | ||
- Set_tag, set_metric, etc now explicitly calls out arg name as metric_name, tag_name, metric_name, etc. | ||
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### New Features | ||
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- Changes to support python 3.9, 3.10 | ||
- Added kBinsDiscretizer | ||
- Support for deployment of XGBoost models & int8 types of data | ||
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## 0.3.0 (2023-05-11) | ||
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### Behavior Changes | ||
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- Big Model Registry Refresh | ||
- Fixed API discrepancies between register_model & log_model. | ||
- Model can be referred by Name + Version (no opaque internal id is required) | ||
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### New Features | ||
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- Model Registry: Added support save/load/deploy SKL & XGB Models | ||
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## 0.2.3 (2023-04-27) | ||
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### Bug Fixes | ||
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- Allow using OneHotEncoder along with sklearn style estimators in a pipeline. | ||
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### New Features | ||
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- Model Registry: Added support for delete_model. Use delete_artifact = False to not delete the underlying model data but just unregister. | ||
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## 0.2.2 (2023-04-11) | ||
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### New Features | ||
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- Initial version of snowflake-ml modeling package. | ||
- Provide support for training most of scikit-learn and xgboost estimators and transformers. | ||
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### Bug Fixes | ||
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- Minor fixes in preprocessing package. | ||
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## 0.2.1 (2023-03-23) | ||
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### New Features | ||
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- New in Preprocessing: | ||
- SimpleImputer | ||
- Covariance Matrix | ||
- Optimization of Ordinal Encoder client computations. | ||
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### Bug Fixes | ||
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- Minor fixes in OneHotEncoder. | ||
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## 0.2.0 (2023-02-27) | ||
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### New Features | ||
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- Model Registry | ||
- PyTorch & Tensorflow connector file generic FileSet API | ||
- New to Preprocessing: | ||
- Binarizer | ||
- Normalizer | ||
- Pearson correlation Matrix | ||
- Optimization in Ordinal Encoder to cache vocabulary in temp tables. | ||
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## 0.1.3 (2023-02-02) | ||
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### New Features | ||
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- Initial version of transformers including: | ||
- Label Encoder | ||
- Max Abs Scaler | ||
- Min Max Scaler | ||
- One Hot Encoder | ||
- Ordinal Encoder | ||
- Robust Scaler | ||
- Standard Scaler |