Pynb-dag-runner

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MLflow 1.23.1 is a patch release containing the following bug fixes:

- [Models] Fix a directory creation failure when loading PySpark ML models (5299, arjundc-db)
- [Model Registry] Revert to using case-insensitive validation logic for stage names in ``models:/`` URIs (5312, lichenran1234)
- [Projects] Fix a race condition during Project tar file creation (5303, dbczumar)

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MLflow 1.23.0 includes several major features and improvements:

Features:

- [Models] Introduce an ``mlflow.evaluate()`` API for evaluating MLflow Models, providing performance and explainability insights. For an overview, see https://mlflow.org/docs/latest/models.html#model-evaluation (5069, 5092, 5256, WeichenXu123)
- [Models] ``log_model()`` APIs now return information about the logged MLflow Model, including artifact location, flavors, and schema (5230, liangz1)
- [Models] Introduce an ``mlflow.models.Model.load_input_example()`` Python API for loading MLflow Model input examples (5212, maitre-matt)
- [Models] Add a UUID field to the MLflow Model specification. MLflow Models now have a unique identifier (5149, 5167, WeichenXu123)
- [Models] Support passing SciPy CSC and CSR matrices as MLflow Model input examples (5016, WeichenXu123)
- [Model Registry] Support specifying ``latest`` in model URI to get the latest version of a model regardless of the stage (5027, lichenran1234)
- [Tracking] Add support for LightGBM scikit-learn models to ``mlflow.lightgbm.autolog()`` (5130, 5200, 5271 jwyyy)
- [Tracking] Improve S3 artifact download speed by caching boto clients (4695, Samreay)
- [UI] Automatically update metric plots for in-progress runs (5017, cedkoffeto, harupy)

Bug fixes and documentation updates:

- [Models] Fix a bug in MLflow Model schema enforcement where strings were incorrectly cast to Pandas objects (5134, stevenchen-db)
- [Models] Fix a bug where keyword arguments passed to ``mlflow.pytorch.load_model()`` were not applied for scripted models (5163, schmidt-jake)
- [Model Registry][R] Fix bug in R client ``mlflow_create_model_version()`` API that caused model ``source`` to be set incorrectly (5185, bramrodenburg)
- [Projects] Fix parsing behavior for Project URIs containing quotes (5117, dinaldoap)
- [Scoring] Use the correct 400-level error code for malformed MLflow Model Server requests (5003, abatomunkuev)
- [Tracking] Fix a bug where ``mlflow.start_run()`` modified user-supplied tags dictionary (5191, matheusMoreno)
- [UI] Fix a bug causing redundant scroll bars to be displayed on the Experiment Page (5159, sunishsheth2009)

Small bug fixes and doc updates (5275, 5264, 5244, 5249, 5255, 5248, 5243, 5240, 5239, 5232, 5234, 5235, 5082, 5220, 5219, 5226, 5217, 5194, 5188, 5132, 5182, 5183, 5180, 5177, 5165, 5164, 5162, 5015, 5136, 5065, 5125, 5106, 5127, 5120, harupy; 5045, BenWilson2; 5156, pbezglasny; 5202, jwyyy; 3863, JoshuaAnickat; 5205, abhiramr; 4604, OSobky; 4256, einsmein; 5140, AveshCSingh; 5273, 5186, 5176, WeichenXu123; 5260, 5229, 5206, 5174, 5160, liangz1)

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MLflow 1.22.0 includes several major features and improvements:

Features:

- [UI] Add a share button to the Experiment page (4936, marijncv)
- [UI] Improve readability of column sorting dropdown on Experiment page (5022, WeichenXu123; 5018, NieuweNils, coder-freestyle)
- [Tracking] Mark all autologging integrations as stable by removing ``experimental`` decorators (5028, liangz1)
- [Tracking] Add optional ``experiment_id`` parameter to ``mlflow.set_experiment()`` (5012, dbczumar)
- [Tracking] Add support for XGBoost scikit-learn models to ``mlflow.xgboost.autolog()`` (5078, jwyyy)
- [Tracking] Improve statsmodels autologging performance by removing unnecessary metrics (4942, WeichenXu123)
- [Tracking] Update R client to tag nested runs with parent run ID (4197, yitao-li)
- [Models] Support saving and loading all XGBoost model types (4954, jwyyy)
- [Scoring] Support specifying AWS account and role when deploying models to SageMaker (4923, andresionek91)
- [Scoring] Support serving MLflow models with MLServer (4963, adriangonz)

Bug fixes and documentation updates:

- [UI] Fix bug causing Metric Plot page to crash when metric values are too large (4947, ianshan0915)
- [UI] Fix bug causing parallel coordinate curves to vanish (5087, harupy)
- [UI] Remove ``Creator`` field from Model Version page if user information is absent (5089, jinzhang21)
- [UI] Fix model loading instructions for non-pyfunc models in Artifact Viewer (5006, harupy)
- [Models] Fix a bug that added ``mlflow`` to ``conda.yaml`` even if a hashed version was already present (5058, maitre-matt)
- [Docs] Add Python documentation for metric, parameter, and tag key / value length limits (4991, westford14)
- [Examples] Update Python version used in Prophet example to fix installation errors (5101, BenWilson2)
- [Examples] Fix Kubernetes ``resources`` specification in MLflow Projects + Kubernetes example (4948, jianyuan)

Small bug fixes and doc updates (5119, 5107, 5105, 5103, 5085, 5088, 5051, 5081, 5039, 5073, 5072, 5066, 5064, 5063, 5060, 4718, 5053, 5052, 5041, 5043, 5047, 5036, 5037, 5029, 5031, 5032, 5030, 5007, 5019, 5014, 5008, 4998, 4985, 4984, 4970, 4966, 4980, 4967, 4978, 4979, 4968, 4976, 4975, 4934, 4956, 4938, 4950, 4946, 4939, 4913, 4940, 4935, harupy; 5095, 5070, 5002, 4958, 4945, BenWilson2; 5099, chaosddp; 5005, you-n-g; 5042, 4952, shrinath-suresh; 4962, 4995, WeichenXu123; 5010, lichenran1234; 5000, wentinghu; 5111, alexott; 5102, 5024, 5011, 4959, dbczumar; 5075, 5044, 5026, 4997, 4964, 4989, liangz1; 4999, stevenchen-db)

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MLflow 1.21.0 includes several major features and improvements:

Features:

- [UI] Add a diff-only toggle to the runs table for filtering out columns with constant values (4862, marijncv)
- [UI] Add a duration column to the runs table (4840, marijncv)
- [UI] Display the default column sorting order in the runs table (4847, marijncv)
- [UI] Add `start_time` and `duration` information to exported runs CSV (4851, marijncv)
- [UI] Add lifecycle stage information to the run page (4848, marijncv)
- [UI] Collapse run page sections by default for space efficiency, limit artifact previews to 50MB (4917, dbczumar)
- [Tracking] Introduce autologging capabilities for PaddlePaddle model training (4751, jinminhao)
- [Tracking] Add an optional tags field to the CreateExperiment API (4788, dbczumar; 4795, apurva-koti)
- [Tracking] Add support for deleting artifacts from SFTP stores via the `mlflow gc` CLI (4670, afaul)
- [Tracking] Support AzureDefaultCredential for authenticating with Azure artifact storage backends (4002, marijncv)
- [Models] Upgrade the fastai model flavor to support fastai V2 (`>=2.4.1`) (4715, jinzhang21)
- [Models] Introduce an `mlflow.prophet` model flavor for Prophet time series models (4773, BenWilson2)
- [Models] Introduce a CLI for publishing MLflow Models to the SageMaker Model Registry (4669, jinnig)
- [Models] Print a warning when inferred model dependencies are not available on PyPI (4891, dbczumar)
- [Models, Projects] Add `MLFLOW_CONDA_CREATE_ENV_CMD` for customizing Conda environment creation (4746, giacomov)

Bug fixes and documentation updates:

- [UI] Fix an issue where column selections made in the runs table were persisted across experiments (4926, sunishsheth2009)
- [UI] Fix an issue where the text `null` was displayed in the runs table column ordering dropdown (4924, harupy)
- [UI] Fix a bug causing the metric plot view to display NaN values upon click (4858, arpitjasa-db)
- [Tracking] Fix a model load failure for paths containing spaces or special characters on UNIX systems (4890, BenWilson2)
- [Tracking] Correct a migration issue that impacted usage of MLflow Tracking with SQL Server (4880, marijncv)
- [Tracking] Spark datasource autologging tags now respect the maximum allowable size for MLflow Tracking (4809, dbczumar)
- [Model Registry] Add previously-missing certificate sources for Model Registry REST API requests (4731, ericgosno91)
- [Model Registry] Throw an exception when users supply invalid Model Registry URIs for Databricks (4877, yunpark93)
- [Scoring] Fix a schema enforcement error that incorrectly cast date-like strings to datetime objects (4902, wentinghu)
- [Docs] Expand the documentation for the MLflow Skinny Client (4113, eedeleon)

Small bug fixes and doc updates (4928, 4919, 4927, 4922, 4914, 4899, 4893, 4894, 4884, 4864, 4823, 4841, 4817, 4796, 4797, 4767, 4768, 4757, harupy; 4863, 4838, marijncv; 4834, ksaur; 4772, louisguitton; 4801, twsl; 4929, 4887, 4856, 4843, 4789, 4780, WeichenXu123; 4769, Ark-kun; 4898, 4756, apurva-koti; 4784, lakshikaparihar; 4855, ianshan0915; 4790, eedeleon; 4931, 4857, 4846, 4777, 4748, dbczumar)

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MLflow 1.20.2 is a patch release containing the following features and bug fixes:

Features:

- Enabled auto dependency inference in spark flavor in autologging (4759, harupy)

Bug fixes and documentation updates:

- Increased MLflow client HTTP request timeout from 10s to 120s (4764, jinzhang21)
- Fixed autologging compatibility bugs with TensorFlow and Keras version `2.6.0` (4766, dbczumar)

Small bug fixes and doc updates (4770, WeichenXu123)

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MLflow 1.20.1 is a patch release containing the following bug fixes:

- Avoid calling `importlib_metadata.packages_distributions` upon `mlflow.utils.requirements_utils` import (4741, dbczumar)
- Avoid depending on `importlib_metadata==4.7.0` (4740, dbczumar)