Mlflow

Features:

- [Pipelines] Improve performance and fidelity of dataset profiling in the scikit-learn regression Pipeline (6792, sunishsheth2009)
- [Pipelines] Add an `mlflow pipelines get-artifact` CLI for retrieving Pipeline artifacts (6517, prithvikannan)
- [Pipelines] Introduce an option for skipping dataset profiling to the scikit-learn regression Pipeline (6456, apurva-koti)
- [Pipelines / UI] Display an `mlflow pipelines` CLI command for reproducing a Pipeline run in the MLflow UI (6376, hubertzub-db)
- [Tracking] Automatically generate friendly names for Runs if not supplied by the user (6736, BenWilson2)
- [Tracking] Add `load_text()`, `load_image()` and `load_dict()` fluent APIs for convenient artifact loading (6475, subramaniam02)
- [Tracking] Add `creation_time` and `last_update_time` attributes to the Experiment class (6756, subramaniam02)
- [Tracking] Add official MLflow Tracking Server Dockerfiles to the MLflow repository (6731, oojo12)
- [Tracking] Add `searchExperiments` API to Java client and deprecate `listExperiments` (6561, dbczumar)
- [Tracking] Add `mlflow_search_experiments` API to R client and deprecate `mlflow_list_experiments` (6576, dbczumar)
- [UI] Make URLs clickable in the MLflow Tracking UI (6526, marijncv)
- [UI] Introduce support for csv data preview within the artifact viewer pane (6567, nnethery)
- [Model Registry / Models] Introduce `mlflow.models.add_libraries_to_model()` API for adding libraries to an MLflow Model (6586, arjundc-db)
- [Models] Add model validation support to `mlflow.evaluate()` (6582, jerrylian-db)
- [Models] Introduce `sample_weights` support to `mlflow.evaluate()` (6806, dbczumar)
- [Models] Add `pos_label` support to `mlflow.evaluate()` for identifying the positive class (6696, harupy)
- [Models] Make the metric name prefix and dataset info configurable in `mlflow.evaluate()` (6593, dbczumar)
- [Models] Add utility for validating the compatibility of a dataset with a model signature (6494, serena-ruan)
- [Models] Add `predict_proba()` support to the pyfunc representation of scikit-learn models (6631, skylarbpayne)
- [Models] Add support for Decimal type inference to MLflow Model schemas (6600, shitaoli-db)
- [Models] Add new CLI command for generating Dockerfiles for model serving (6591, anuarkaliyev23)
- [Scoring] Add `/health` endpoint to scoring server (6574, gabriel-milan)
- [Scoring] Support specifying a `variant_name` during Sagemaker deployment (6486, nfarley-soaren)
- [Scoring] Support specifying a `data_capture_config` during SageMaker deployment (6423, jonwiggins)

Bug fixes:

- [Tracking] Make Run and Experiment deletion and restoration idempotent (6641, dbczumar)
- [UI] Fix an alignment bug affecting the Experiments list in the MLflow UI (6569, sunishsheth2009)
- [Models] Fix a regression in the directory path structure of logged Spark Models that occurred in MLflow 1.28.0 (6683, gwy1995)
- [Models] No longer reload the `__main__` module when loading model code (6647, Jooakim)
- [Artifacts] Fix an `mlflow server` compatibility issue with HDFS when running in `--serve-artifacts` mode (6482, shidianshifen)
- [Scoring] Fix an inference failure with 1-dimensional tensor inputs in TensorFlow and Keras (6796, LiamConnell)

Documentation updates:

- [Tracking] Mark the SearchExperiments API as stable (6551, dbczumar)
- [Tracking / Model Registry] Deprecate the ListExperiments, ListRegisteredModels, and `list_run_infos()` APIs (6550, dbczumar)
- [Scoring] Deprecate `mlflow.sagemaker.deploy()` in favor of `SageMakerDeploymentClient.create()` (6651, dbczumar)

Small bug fixes and documentation updates:

6803, 6804, 6801, 6791, 6772, 6745, 6762, 6760, 6761, 6741, 6725, 6720, 6666, 6708, 6717, 6704, 6711, 6710, 6706, 6699, 6700, 6702, 6701, 6685, 6664, 6644, 6653, 6629, 6639, 6624, 6565, 6558, 6557, 6552, 6549, 6534, 6533, 6516, 6514, 6506, 6509, 6505, 6492, 6490, 6478, 6481, 6464, 6463, 6460, 6461, harupy; 6810, 6809, 6727, 6648, BenWilson2; 6808, 6766, 6729, jerrylian-db; 6781, 6694, marijncv; 6580, 6661, bbarnes52; 6778, 6687, 6623, shraddhafalane; 6662, 6737, 6612, 6595, sunishsheth2009; 6777, aviralsharma07; 6665, 6743, 6573, liangz1; 6784, apurva-koti; 6753, 6751, mingyu89; 6690, 6455, 6484, kriscon-db; 6465, 6689, hubertzub-db; 6721, WeichenXu123; 6722, 6718, 6668, 6663, 6621, 6547, 6508, 6474, 6452, dbczumar; 6555, 6584, 6543, 6542, 6521, dsgibbons; 6634, 6596, 6563, 6495, prithvikannan; 6571, smurching; 6630, 6483, serena-ruan; 6642, thinkall; 6614, 6597, jinzhang21; 6457, cnphil; 6570, 6559, kumaryogesh17; 6560, 6540, iamthen0ise; 6544, Monkero; 6438, ahlag; 3292, dolfinus; 6637, ninabacc-db; 6632, arpitjasa-db

Features:

- [Pipelines] Log the full Pipeline runtime configuration to MLflow Tracking during Pipeline execution (6359, jinzhang21)
- [Pipelines] Add ``pipeline.yaml`` configurations to specify the Model Registry backend used for model registration (6284, sunishsheth2009)
- [Pipelines] Support optionally skipping the ``transform`` step of the scikit-learn regression pipeline (6362, sunishsheth2009)
- [Pipelines] Add UI links to Runs and Models in Pipeline Step Cards on Databricks (6294, dbczumar)
- [Tracking] Introduce ``mlflow.search_experiments()`` API for searching experiments by name and by tags (6333, WeichenXu123; 6227, 6172, 6154, harupy)
- [Tracking] Increase the maximum parameter value length supported by File and SQL backends to 500 characters (6358, johnyNJ)
- [Tracking] Introduce an ``--older-than`` flag to ``mlflow gc`` for removing runs based on deletion time (6354, Jason-CKY)
- [Tracking] Add ``MLFLOW_SQLALCHEMYSTORE_POOL_RECYCLE`` environment variable for recycling SQLAlchemy connections (6344, postrational)
- [UI] Display deeply nested runs in the Runs Table on the Experiment Page (6065, tospe)
- [UI] Add box plot visualization for metrics to the Compare Runs page (6308, ahlag)
- [UI] Display tags on the Compare Runs page (6164, CaioCavalcanti)
- [UI] Use scientific notation for axes when viewing metric plots in log scale (6176, RajezMariner)
- [UI] Add button to Metrics page for downloading metrics as CSV (6048, rafaelvp-db)
- [UI] Include NaN and +/- infinity values in plots on the Metrics page (6422, hubertzub-db)
- [Tracking / Model Registry] Introduce environment variables to control retry behavior and timeouts for REST API requests (5745, peterdhansen)
- [Tracking / Model Registry] Make ``MlflowClient`` importable as ``mlflow.MlflowClient`` (6085, subramaniam02)
- [Model Registry] Add support for searching registered models and model versions by tags (6413, 6411, 6320, WeichenXu123)
- [Model Registry] Add ``stage`` parameter to ``set_model_version_tag()`` (6185, subramaniam02)
- [Model Registry] Add ``--registry-store-uri`` flag to ``mlflow server`` for specifying the Model Registry backend URI (6142, Secbone)
- [Models] Improve performance of Spark Model logging on Databricks (6282, bbarnes52)
- [Models] Include Pandas Series names in inferred model schemas (6361, RynoXLI)
- [Scoring] Make ``model_uri`` optional in ``mlflow models build-docker`` to support building generic model serving images (6302, harupy)
- [R] Support logging of NA and NaN parameter values (6263, nathaneastwood)

Bug fixes and documentation updates:

- [Pipelines] Improve scikit-learn regression pipeline latency by limiting dataset profiling to the first 100 columns (6297, sunishsheth2009)
- [Pipelines] Use ``xdg-open`` instead of ``open`` for viewing Pipeline results on Linux systems (6326, strangiato)
- [Pipelines] Fix a bug that skipped Step Card rendering in Jupyter Notebooks (6378, apurva-koti)
- [Tracking] Use the 401 HTTP response code in authorization failure REST API responses, instead of 500 (6106, balvisio)
- [Tracking] Correctly classify artifacts as files and directories when using Azure Blob Storage (6237, nerdinand)
- [Tracking] Fix a bug in the File backend that caused run metadata to be lost in the event of a failed write (6388, dbczumar)
- [Tracking] Adjust ``mlflow.pyspark.ml.autolog()`` to only log model signatures for supported input / output data types (6365, harupy)
- [Tracking] Adjust ``mlflow.tensorflow.autolog()`` to log TensorFlow early stopping callback info when ``log_models=False`` is specified (6170, WeichenXu123)
- [Tracking] Fix signature and input example logging errors in ``mlflow.sklearn.autolog()`` for models containing transformers (6230, dbczumar)
- [Tracking] Fix a failure in ``mlflow gc`` that occurred when removing a run whose artifacts had been previously deleted (6165, dbczumar)
- [Tracking] Add missing ``sqlparse`` library to MLflow Skinny client, which is required for search support (6174, dbczumar)
- [Tracking / Model Registry] Fix an ``mlflow server`` bug that rejected parameters and tags with empty string values (6179, dbczumar)
- [Model Registry] Fix a failure preventing model version schemas from being downloaded with ``--serve-arifacts`` enabled (6355, abbas123456)
- [Scoring] Patch the Java Model Server to support MLflow Models logged on recent versions of the Databricks Runtime (6337, dbczumar)
- [Scoring] Verify that either the deployment name or endpoint is specified when invoking the ``mlflow deployments predict`` CLI (6323, dbczumar)
- [Scoring] Properly encode datetime columns when performing batch inference with ``mlflow.pyfunc.spark_udf()`` (6244, harupy)
- [Projects] Fix an issue where local directory paths were misclassified as Git URIs when running Projects (6218, ElefHead)
- [R] Fix metric logging behavior for +/- infinity values (6271, nathaneastwood)
- [Docs] Move Python API docs for ``MlflowClient`` from ``mlflow.tracking`` to ``mlflow.client`` (6405, dbczumar)
- [Docs] Document that MLflow Pipelines requires Make (6216, dbczumar)
- [Docs] Improve documentation for developing and testing MLflow JS changes in ``CONTRIBUTING.rst`` (6330, ahlag)

Small bug fixes and doc updates (6322, 6321, 6213, KarthikKothareddy; 6409, 6408, 6396, 6402, 6399, 6398, 6397, 6390, 6381, 6386, 6385, 6373, 6375, 6380, 6374, 6372, 6363, 6353, 6352, 6350, 6351, 6349, 6347, 6287, 6341, 6342, 6340, 6338, 6319, 6314, 6316, 6317, 6318, 6315, 6313, 6311, 6300, 6292, 6291, 6289, 6290, 6278, 6279, 6276, 6272, 6252, 6243, 6250, 6242, 6241, 6240, 6224, 6220, 6208, 6219, 6207, 6171, 6206, 6199, 6196, 6191, 6190, 6175, 6167, 6161, 6160, 6153, harupy; 6193, jwgwalton; 6304, 6239, 6234, 6229, sunishsheth2009; 6258, xanderwebs; 6106, balvisio; 6303, bbarnes52; 6117, wenfeiy-db; 6389, 6214, apurva-koti; 6412, 6420, 6277, 6266, 6260, 6148, WeichenXu123; 6120, ameya-parab; 6281, nathaneastwood; 6426, 6415, 6417, 6418, 6257, 6182, 6157, dbczumar; 6189, shrinath-suresh; 6309, SamirPS; 5897, temporaer; 6251, herrmann; 6198, sniafas; 6368, 6158, jinzhang21; 6236, subramaniam02; 6036, serena-ruan; 6430, ninabacc-db)

- [**Pipelines**] With MLflow 1.27.0, we are excited to announce the release of
[**MLflow Pipelines**](https://mlflow.org/docs/latest/pipelines.html), an opinionated framework for
structuring MLOps workflows that simplifies and standardizes machine learning application development
and productionization. MLflow Pipelines makes it easy for data scientists to follow best practices
for creating production-ready ML deliverables, allowing them to focus on developing excellent models.
MLflow Pipelines also enables ML engineers and DevOps teams to seamlessly deploy models to production
and incorporate them into applications. To get started with MLflow Pipelines, check out the docs at
https://mlflow.org/docs/latest/pipelines.html. (#6115)

- [UI] Introduce UI support for searching and comparing runs across multiple Experiments (5971, r3stl355)

More features:

- [Tracking] When using batch logging APIs, automatically split large sets of metrics, tags, and params into multiple requests (6052, nzw0301)
- [Tracking] When an Experiment is deleted, SQL-based backends also move the associate Runs to the "deleted" lifecycle stage (6064, AdityaIyengar27)
- [Tracking] Add support for logging single-element ``ndarray`` and tensor instances as metrics via the ``mlflow.log_metric()`` API (5756, ntakouris)
- [Models] Add support for ``CatBoostRanker`` models to the ``mlflow.catboost`` flavor (6032, danielgafni)
- [Models] Integrate SHAP's ``KernelExplainer`` with ``mlflow.evaluate()``, enabling model explanations on categorical data (6044, 5920, WeichenXu123)
- [Models] Extend ``mlflow.evaluate()`` to automatically log the ``score()`` outputs of scikit-learn models as metrics (5935, 5903, WeichenXu123)

Bug fixes and documentation updates:

- [UI] Fix broken model links in the Runs table on the MLflow Experiment Page (6014, hctpbl)
- [Tracking/Installation] Require ``sqlalchemy>=1.4.0`` upon MLflow installation, which is necessary for usage of SQL-based MLflow Tracking backends (6024, sniafas)
- [Tracking] Fix a regression that caused ``mlflow server`` to reject ``LogParam`` API requests containing empty string values (6031, harupy)
- [Tracking] Fix a failure in scikit-learn autologging that occurred when ``matplotlib`` was not installed on the host system (5995, fa9r)
- [Tracking] Fix a failure in TensorFlow autologging that occurred when training models on ``tf.data.Dataset`` inputs (6061, dbczumar)
- [Artifacts] Address artifact download failures from SFTP locations that occurred due to mismanaged concurrency (5840, rsundqvist)
- [Models] Fix a bug where MLflow Models did not restore bundled code properly if multiple models use the same code module name (5926, BFAnas)
- [Models] Address an issue where ``mlflow.sklearn.model()`` did not properly restore bundled model code (6037, WeichenXu123)
- [Models] Fix a bug in ``mlflow.evaluate()`` that caused input data objects to be mutated when evaluating certain scikit-learn models (6141, dbczumar)
- [Models] Fix a failure in ``mlflow.pyfunc.spark_udf`` that occurred when the UDF was invoked on an empty RDD partition (6063, WeichenXu123)
- [Models] Fix a failure in ``mlflow models build-docker`` that occurred when ``env-manager=local`` was specified (6046, bneijt)
- [Projects] Improve robustness of the git repository check that occurs prior to MLflow Project execution (6000, dkapur17)
- [Projects] Address a failure that arose when running a Project that does not have a ``master`` branch (5889, harupy)
- [Docs] Correct several typos throughout the MLflow docs (5959, ryanrussell)

Small bug fixes and doc updates (6041, drsantos89; 6138, 6137, 6132, sunishsheth2009; 6144, 6124, 6125, 6123, 6057, 6060, 6050, 6038, 6029, 6030, 6025, 6018, 6019, 5962, 5974, 5972, 5957, 5947, 5907, 5938, 5906, 5932, 5919, 5914, 5888, 5890, 5886, 5873, 5865, 5843, harupy; 6113, comojin1994; 5930, yashaswikakumanu; 5837, shrinath-suresh; 6067, deepyaman; 5997, idlefella; 6021, BenWilson2; 5984, Sumanth077; 5929, krunal16-c; 5879, kugland; 5875, ognis1205; 6006, ryanrussell; 6140, jinzhang21; 5983, elk15; 6022, apurva-koti; 5982, EB-Joel; 5981, 5980, punitkashyup; 6103, ikrizanic; 5988, 5969, SaumyaBhushan; 6020, 5991, WeichenXu123; 5910, 5912, Dark-Knight11; 6005, Asinsa; 6023, subramaniam02; 5999, Regis-Caelum; 6007, CaioCavalcanti; 5943, kvaithin; 6017, 6002, NeoKish; 6111, T1b4lt; 5986, seyyidibrahimgulec; 6053, Zohair-coder; 6146, 6145, 6143, 6139, 6134, 6136, 6135, 6133, 6071, 6070, dbczumar; 6026, rotate2050)

- [Installation] Fix compatibility issue with ``protobuf >= 4.21.0`` (5945, harupy)
- [Models] Fix ``get_model_dependencies`` behavior for ``models:`` URIs containing artifact paths (5921, harupy)
- [Models] Revert a problematic change to ``artifacts`` persistence in ``mlflow.pyfunc.log_model()`` that was introduced in MLflow 1.25.0 (5891, kyle-jarvis)
- [Models] Close associated image files when ``EvaluationArtifact`` outputs from ``mlflow.evaluate()`` are garbage collected (5900, WeichenXu123)

Small bug fixes and updates (5874, 5942, 5941, 5940, 5938, harupy; 5893, PrajwalBorkar; 5909, yashaswikakumanu; 5937, BenWilson2)

Features:

- [CLI] Add endpoint naming and options configuration to the deployment CLI (5731, trangevi)
- [Build,Doc] Add development environment setup script for Linux and MacOS x86 Operating Systems (5717, BenWilson2)
- [Tracking] Update `mlflow.set_tracking_uri` to add support for paths defined as `pathlib.Path` in addition to existing `str` path declarations (5824, cacharle)
- [Scoring] Add custom timeout override option to the scoring server CLI to support high latency models (5663, sniafas)
- [UI] Add sticky header to experiment run list table to support column name visibility when scrolling beyond page fold (5818, hubertzub-db)
- [Artifacts] Add GCS support for MLflow garbage collection (5811, aditya-iyengar-rtl-de)
- [Evaluate] Add `pos_label` argument for `eval_and_log_metrics` API to support accurate binary classifier evaluation metrics (5807, yxiong)
- [UI] Add fields for latest, minimum and maximum metric values on metric display page (5574, adamreeve)
- [Models] Add support for `input_example` and `signature` logging for pyspark ml flavor when using autologging (5719, bali0019)
- [Models] Add `virtualenv` environment manager support for `mlflow models docker-build` CLI (5728, harupy)
- [Models] Add support for wildcard module matching in log_model_allowlist for PySpark models (5723, serena-ruan)
- [Projects] Add `virtualenv` environment manager support for MLflow projects (5631, harupy)
- [Models] Add `virtualenv` environment manager support for MLflow Models (5380, harupy)
- [Models] Add `virtualenv` environment manager support for `mlflow.pyfunc.spark_udf` (5676, WeichenXu123)
- [Models] Add support for `input_example` and `signature` logging for `tensorflow` flavor when using autologging (5510, bali0019)
- [Server-infra] Add JSON Schema Type Validation to enable raising 400 errors on malformed requests to REST API endpoints (5458, mrkaye97)
- [Scoring] Introduce abstract `endpoint` interface for mlflow deployments (5378, trangevi)
- [UI] Add `End Time` and `Duration` fields to run comparison page (3378, RealArpanBhattacharya)
- [Serving] Add schema validation support when parsing input csv data for model serving (5531, vvijay-bolt)

Bug fixes and documentation updates:

- [Models] Fix REPL ID propagation from datasource listener to publisher for Spark data sources (5826, dbczumar)
- [UI] Update `ag-grid` and implement `getRowId` to improve performance in the runs table visualization (5725, adamreeve)
- [Serving] Fix `tf-serving` parsing to support columnar-based formatting (5825, arjundc-db)
- [Artifacts] Update `log_artifact` to support models larger than 2GB in HDFS (5812, hitchhicker)
- [Models] Fix autologging to support `lightgbm` metric names with "" symbols within their names (5785, mengchendd)
- [Models] Pyfunc: Fix code directory resolution of subdirectories (5806, dbczumar)
- [Server-Infra] Fix mlflow-R server starting failure on windows (5767, serena-ruan)
- [Docs] Add documentation for `virtualenv` environment manager support for MLflow projects (5727, harupy)
- [UI] Fix artifacts display sizing to support full width rendering in preview pane (5606, szczeles)
- [Models] Fix local hostname issues when loading spark model by binding driver address to localhost (5753, WeichenXu123)
- [Models] Fix autologging validation and batch_size calculations for `tensorflow` flavor (5683, MarkYHZhang)
- [Artifacts] Fix `SqlAlchemyStore.log_batch` implementation to make it log data in batches (5460, erensahin)

Small bug fixes and doc updates (5858, 5859, 5853, 5854, 5845, 5829, 5842, 5834, 5795, 5777, 5794, 5766, 5778, 5765, 5763, 5768, 5769, 5760, 5727, 5748, 5726, 5721, 5711, 5710, 5708, 5703, 5702, 5696, 5695, 5669, 5670, 5668, 5661, 5638, harupy; 5749, arpitjasa-db; 5675, Davidswinkels; 5803, 5797, ahlag; 5743, kzhang01; 5650, 5805, 5724, 5720, 5662, BenWilson2; 5627, cterrelljones; 5646, kutal10; 5758, davideli-db; 5810, rahulporuri; 5816, 5764, shrinath-suresh; 5869, 5715, 5737, 5752, 5677, 5636, WeichenXu123; 5735, subramaniam02; 5746, akaigraham; 5734, 5685, lucalves; 5761, marcelatoffernet; 5707, aashish-khub; 5808, ketangangal; 5730, 5700, shaikmoeed; 5775, dbczumar; 5747, zhixuanevelynwu)

- [Models] Fix a `pyfunc` artifact overwrite bug for when multiple artifacts are saved in sub-directories (5657, kyle-jarvis)
- [Scoring] Fix permissions issue for Spark workers accessing model artifacts from a temp directory created by the driver (5684, WeichenXu123)