Pynb-dag-runner

-------------------
MLflow 1.14.1 is a patch release containing the following bug fix:

- Fix issues in handling flexible numpy datatypes in TensorSpec (4147, arjundc-db)

-------------------
MLflow 1.14.0 includes several major features and improvements:

- MLflow's model inference APIs (``mlflow.pyfunc.predict``), built-in model serving tools (``mlflow models serve``), and model signatures now support tensor inputs. In particular, MLflow now provides built-in support for scoring PyTorch, TensorFlow, Keras, ONNX, and Gluon models with tensor inputs. For more information, see https://mlflow.org/docs/latest/models.html#deploy-mlflow-models (3808, 3894, 4084, 4068 wentinghu; 4041 tomasatdatabricks, 4099, arjundc-db)
- Add new ``mlflow.shap.log_explainer``, ``mlflow.shap.load_explainer`` APIs for logging and loading ``shap.Explainer`` instances (3989, vivekchettiar)
- The MLflow Python client is now available with a reduced dependency set via the ``mlflow-skinny`` PyPI package (4049, eedeleon)
- Add new ``RequestHeaderProvider`` plugin interface for passing custom request headers with REST API requests made by the MLflow Python client (4042, jimmyxu-db)
- ``mlflow.keras.log_model`` now saves models in the TensorFlow SavedModel format by default instead of the older Keras H5 format (4043, harupy)
- ``mlflow_log_model`` now supports logging MLeap models in R (3819, yitao-li)
- Add ``mlflow.pytorch.log_state_dict``, ``mlflow.pytorch.load_state_dict`` for logging and loading PyTorch state dicts (3705, shrinath-suresh)
- ``mlflow gc`` can now garbage-collect artifacts stored in S3 (3958, sklingel)

Bug fixes and documentation updates:

- Enable autologging for TensorFlow estimators that extend ``tensorflow.compat.v1.estimator.Estimator`` (4097, mohamad-arabi)
- Fix for universal autolog configs overriding integration-specific configs (4093, dbczumar)
- Allow ``mlflow.models.infer_signature`` to handle dataframes containing ``pandas.api.extensions.ExtensionDtype`` (4069, caleboverman)
- Fix bug where ``mlflow_restore_run`` doesn't propagate the ``client`` parameter to ``mlflow_get_run`` (4003, yitao-li)
- Fix bug where scoring on served model fails when request data contains a string that looks like URL and pandas version is later than 1.1.0 (3921, Secbone)
- Fix bug causing ``mlflow_list_experiments`` to fail listing experiments with tags (3942, lorenzwalthert)
- Fix bug where metrics plots are computed from incorrect target values in scikit-learn autologging (3993, mtrencseni)
- Remove redundant / verbose Python event logging message in autologging (3978, dbczumar)
- Fix bug where ``mlflow_load_model`` doesn't load metadata associated to MLflow model flavor in R (3872, yitao-li)
- Fix ``mlflow.spark.log_model``, ``mlflow.spark.load_model`` APIs on passthrough-enabled environments against ACL'd artifact locations (3443, smurching)

Small bug fixes and doc updates (4102, 4101, 4096, 4091, 4067, 4059, 4016, 4054, 4052, 4051, 4038, 3992, 3990, 3981, 3949, 3948, 3937, 3834, 3906, 3774, 3916, 3907, 3938, 3929, 3900, 3902, 3899, 3901, 3891, 3889, harupy; 4014, 4001, dmatrix; 4028, 3957, dbczumar; 3816, lorenzwalthert; 3939, pauldj54; 3740, jkthompson; 4070, 3946, jimmyxu-db; 3836, t-henri; 3982, neo-anderson; 3972, 3687, 3922, eedeleon; 4044, WeichenXu123; 4063, yitao-li; 3976, whiteh; 4110, tomasatdatabricks; 4050, apurva-koti; 4100, 4084, wentinghu; 3947, vperiyasamy; 4021, trangevi; 3773, ankan94; 4090, jinzhang21; 3918, danielfrg)

-----------------
MLflow 1.13.1 is a patch release containing bug fixes and small changes:

- Fix bug causing Spark autologging to ignore configuration options specified by ``mlflow.autolog()`` (3917, dbczumar)
- Fix bugs causing metrics to be dropped during TensorFlow autologging (3913, 3914, dbczumar)
- Fix incorrect value of optimizer name parameter in autologging PyTorch Lightning (3901, harupy)
- Fix model registry database ``allow_null_for_run_id`` migration failure affecting MySQL databases (3836, t-henri)
- Fix failure in ``transition_model_version_stage`` when uncanonical stage name is passed (3929, harupy)
- Fix an undefined variable error causing AzureML model deployment to fail (3922, eedeleon)
- Reclassify scikit-learn as a pip dependency in MLflow Model conda environments (3896, harupy)
- Fix experiment view crash and artifact view inconsistency caused by artifact URIs with redundant slashes (3928, dbczumar)

-----------------
MLflow 1.13 includes several major features and improvements:

Features:

New fluent APIs for logging in-memory objects as artifacts:

- Add ``mlflow.log_text`` which logs text as an artifact (3678, harupy)
- Add ``mlflow.log_dict`` which logs a dictionary as an artifact (3685, harupy)
- Add ``mlflow.log_figure`` which logs a figure object as an artifact (3707, harupy)
- Add ``mlflow.log_image`` which logs an image object as an artifact (3728, harupy)

UI updates / fixes (3867, smurching):

- Add model version link in compact experiment table view
- Add logged/registered model links in experiment runs page view
- Enhance artifact viewer for MLflow models
- Model registry UI settings are now persisted across browser sessions
- Add model version ``description`` field to model version table

Autologging enhancements:

- Improve robustness of autologging integrations to exceptions (3682, 3815, dbczumar; 3860, mohamad-arabi; 3854, 3855, 3861, harupy)
- Add ``disable`` configuration option for autologging (3682, 3815, dbczumar; 3838, mohamad-arabi; 3854, 3855, 3861, harupy)
- Add ``exclusive`` configuration option for autologging (3851, apurva-koti; 3869, dbczumar)
- Add ``log_models`` configuration option for autologging (3663, mohamad-arabi)
- Set tags on autologged runs for easy identification (and add tags to start_run) (3847, dbczumar)

More features and improvements:

- Allow Keras models to be saved with ``SavedModel`` format (3552, skylarbpayne)
- Add support for ``statsmodels`` flavor (3304, olbapjose)
- Add support for nested-run in mlflow R client (3765, yitao-li)
- Deploying a model using ``mlflow.azureml.deploy`` now integrates better with the AzureML tracking/registry. (3419, trangevi)
- Update schema enforcement to handle integers with missing values (3798, tomasatdatabricks)

Bug fixes and documentation updates:

- When running an MLflow Project on Databricks, the version of MLflow installed on the Databricks cluster will now match the version used to run the Project (3880, FlorisHoogenboom)
- Fix bug where metrics are not logged for single-epoch ``tf.keras`` training sessions (3853, dbczumar)
- Reject boolean types when logging MLflow metrics (3822, HCoban)
- Fix alignment of Keras / ``tf.Keras`` metric history entries when ``initial_epoch`` is different from zero. (3575, garciparedes)
- Fix bugs in autologging integrations for newer versions of TensorFlow and Keras (3735, dbczumar)
- Drop global ``filterwwarnings`` module at import time (3621, jogo)
- Fix bug that caused preexisting Python loggers to be disabled when using MLflow with the SQLAlchemyStore (3653, arthury1n)
- Fix ``h5py`` library incompatibility for exported Keras models (3667, tomasatdatabricks)

Small changes, bug fixes and doc updates (3887, 3882, 3845, 3833, 3830, 3828, 3826, 3825, 3800, 3809, 3807, 3786, 3794, 3731, 3776, 3760, 3771, 3754, 3750, 3749, 3747, 3736, 3701, 3699, 3698, 3658, 3675, harupy; 3723, mohamad-arabi; 3650, 3655, shrinath-suresh; 3850, 3753, 3725, dmatrix; 3867, 3670, 3664, smurching; 3681, sueann; 3619, andrewnitu; 3837, javierluraschi; 3721, szczeles; 3653, arthury1n; 3883, 3874, 3870, 3877, 3878, 3815, 3859, 3844, 3703, dbczumar; 3768, wentinghu; 3784, HCoban; 3643, 3649, arjundc-db; 3864, AveshCSingh, 3756, yitao-li)

-------------------
MLflow 1.12.1 is a patch release containing bug fixes and small changes:

- Fix ``run_link`` for cross-workspace model versions (3681, sueann)
- Remove hard dependency on matplotlib for sklearn autologging (3703, dbczumar)
- Do not disable existing loggers when initializing alembic (3653, arthury1n)

-------------------
MLflow 1.12.0 includes several major features and improvements, in particular a number of improvements to autologging and MLflow's Pytorch integrations:

Features:
~~~~~~~~~

Autologging:

- Add universal ``mlflow.autolog`` which enables autologging for all supported integrations (3561, 3590, andrewnitu)
- Add ``mlflow.pytorch.autolog`` API for automatic logging of metrics, params, and models from Pytorch Lightning training (3601, shrinath-suresh, 3636, karthik-77). This API is also enabled by ``mlflow.autolog``.
- Scikit-learn, XGBoost, and LightGBM autologging now support logging model signatures and input examples (3386, 3403, 3449, andrewnitu)
- ``mlflow.sklearn.autolog`` now supports logging metrics (e.g. accuracy) and plots (e.g. confusion matrix heat map) (3423, 3327, willzhan-db, harupy)

PyTorch:

- ``mlflow.pytorch.log_model``, ``mlflow.pytorch.load_model`` now support logging/loading TorchScript models (3557, shrinath-suresh)
- ``mlflow.pytorch.log_model`` supports passing ``requirements_file`` & ``extra_files`` arguments to log additional artifacts along with a model (3436, shrinath-suresh)


More features and improvements:

- Add ``mlflow.shap.log_explanation`` for logging model explanations generated by SHAP (3513, harupy)
- ``log_model`` and ``create_model_version`` now supports an ``await_creation_for`` argument (3376, andychow-db)
- Put preview paths before non-preview paths for backwards compatibility (3648, sueann)
- Clean up model registry endpoint and client method definitions (3610, sueann)
- MLflow deployments plugin now supports 'predict' CLI command (3597, shrinath-suresh)
- Support H2O for R (3416, yitao-li)
- Add ``MLFLOW_S3_IGNORE_TLS`` environment variable to enable skipping TLS verification of S3 endpoint (3345, dolfinus)

Bug fixes and documentation updates:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

- Ensure that results are synced across distributed processes if ddp enabled (no-op else) (3651, SeanNaren)
- Remove optimizer step override to ensure that all accelerator cases are covered by base module (3635, SeanNaren)
- Fix ``AttributeError`` in keras autologgging (3611, sephib)
- Scikit-learn autologging: Exclude feature extraction / selection estimator (3600, dbczumar)
- Scikit-learn autologging: Fix behavior when a child and its parent are both patched (3582, dbczumar)
- Fix a bug where ``lightgbm.Dataset(None)`` fails after running ``mlflow.lightgbm.autolog`` (3594, harupy)
- Fix a bug where ``xgboost.DMatrix(None)`` fails after running ``mlflow.xgboost.autolog`` (3584, harupy)
- Pass ``docker_args`` in non-synchronous mlflow project runs (3563, alfozan)
- Fix a bug of ``FTPArtifactRepository.log_artifacts`` with ``artifact_path`` keyword argument (issue 3388) (3391, kzm4269)
- Exclude preprocessing & imputation steps from scikit-learn autologging (3491, dbczumar)
- Fix duplicate stderr logging during artifact logging and project execution in the R client (3145, yitao-li)
- Don't call ``atexit.register(_flush_queue)`` in ``__main__`` scope of ``mlflow/tensorflow.py`` (3410, harupy)
- Fix for restarting terminated run not setting status correctly (3329, apurva-koti)
- Fix model version run_link URL for some Databricks regions (3417, sueann)
- Skip JSON validation when endpoint is not MLflow REST API (3405, harupy)
- Document ``mlflow-torchserve`` plugin (3634, karthik-77)
- Add ``mlflow-elasticsearchstore`` to the doc (3462, AxelVivien25)
- Add code snippets for fluent and MlflowClient APIs (3385, 3437, 3489 3573, dmatrix)
- Document ``mlflow-yarn`` backend (3373, fhoering)
- Fix a breakage in loading Tensorflow and Keras models (3667, tomasatdatabricks)

Small bug fixes and doc updates (3607, 3616, 3534, 3598, 3542, 3568, 3349, 3554, 3544, 3541, 3533, 3535, 3516, 3512, 3497, 3522, 3521, 3492, 3502, 3434, 3422, 3394, 3387, 3294, 3324, 3654, harupy; 3451, jgc128; 3638, 3632, 3608, 3452, 3399, shrinath-suresh; 3495, 3459, 3662, 3668, 3670 smurching; 3488, edgan8; 3639, karthik-77; 3589, 3444, 3276, lorenzwalthert; 3538, 3506, 3509, 3507, 3510, 3508, rahulporuri; 3504, sbrugman; 3486, 3466, apurva-koti; 3477, juntai-zheng; 3617, 3609, 3605, 3603, 3560, dbczumar; 3411, danielvdende; 3377, willzhan-db; 3420, 3404, andrewnitu; 3591, mateiz; 3465, abawchen; 3543, emptalk; 3302, bramrodenburg; 3468, ghisvail; 3496, extrospective; 3549, 3501, 3435, yitao-li; 3243, OlivierBondu; 3439, andrewnitu; 3651, 3635 SeanNaren, 3470, ankit-db)