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MLflow v1.25.0 Release Notes

Release Date: 2022-04-11 // about 2 years ago

  • MLflow 1.25.0 includes several major features and improvements:

    🔋 Features:

    • [Tracking] Introduce a new fluent API mlflow.last_active_run() that provides the most recent fluent active run (#5584, @MarkYHZhang)
    • [Tracking] Add experiment_names argument to the mlflow.search_runs() API to support searching runs by experiment names (#5564, @r3stl355)
    • [Tracking] Add a description parameter to mlflow.start_run() (#5534, @dogeplusplus)
    • [Tracking] Add log_every_n_step parameter to mlflow.pytorch.autolog() to control metric logging frequency (#5516, @adamreeve)
    • 🌲 [Tracking] Log pyspark.ml.param.Params values as MLflow parameters during PySpark autologging (#5481, @serena-ruan)
    • 👍 [Tracking] Add support for pyspark.ml.Transformers to PySpark autologging (#5466, @serena-ruan)
    • [Tracking] Add input example and signature autologging for Keras models (#5461, @bali0019)
    • ✅ [Models] Introduce mlflow.diviner flavor for large-scale time series forecasting (#5553, @BenWilson2)
    • [Models] Add pyfunc.get_model_dependencies() API to retrieve reproducible environment specifications for MLflow Models with the pyfunc flavor (#5503, @WeichenXu123)
    • 👍 [Models] Add code_paths argument to all model flavors to support packaging custom module code with MLflow Models (#5448, @stevenchen-db)
    • 👍 [Models] Support creating custom artifacts when evaluating models with mlflow.evaluate() (#5405, #5476 @MarkYHZhang)
    • [Models] Add mlflow_version field to MLModel specification (#5515, #5576, @r3stl355)
    • 🌲 [Models] Add support for logging models to preexisting destination directories (#5572, @akshaya-a)
    • 🔧 [Scoring / Projects] Introduce --env-manager configuration for specifying environment restoration tools (e.g. conda) and deprecate --no-conda (#5567, @harupy)
    • 👍 [Scoring] Support restoring model dependencies in mlflow.pyfunc.spark_udf() to ensure accurate predictions (#5487, #5561, @WeichenXu123)
    • 👍 [Scoring] Add support for numpy.ndarray type inputs to the TensorFlow pyfunc predict() function (#5545, @WeichenXu123)
    • 🚀 [Scoring] Support deployment of MLflow Models to Sagemaker Serverless (#5610, @matthewmayo)
    • 💻 [UI] Add MLflow version to header beneath logo (#5504, @adamreeve)
    • [Artifacts] Introduce a mlflow.artifacts.download_artifacts() API mirroring the functionality of the mlflow artifacts download CLI (#5585, @dbczumar)
    • [Artifacts] Introduce environment variables for controlling GCS artifact upload/download chunk size and timeouts (#5438, #5483, @mokrueger)

    🐛 Bug fixes and documentation updates:

    • 🐎 [Tracking/SQLAlchemy] Create an index on run_uuid for PostgreSQL to improve query performance (#5446, @harupy)
    • 🚚 [Tracking] Remove client-side validation of metric, param, tag, and experiment fields (#5593, @BenWilson2)
    • 👍 [Projects] Support setting the name of the MLflow Run when executing an MLflow Project (#5187, @bramrodenburg)
    • 🚀 [Scoring] Use pandas split orientation for DataFrame inputs to SageMaker deployment predict() API to preserve column ordering (#5522, @dbczumar)
    • [Server-Infra] Fix runs search compatibility bugs with PostgreSQL, MySQL, and MSSQL (#5540, @harupy)
    • [CLI] Fix a bug in the mlflow-skinny client that caused mlflow --version to fail (#5573, @BenWilson2)
    • 🚀 [Docs] Update guidance and examples for model deployment to AzureML to recommend using the mlflow-azureml package (#5491, @santiagxf)

    ⚡️ Small bug fixes and doc updates (#5591, #5629, #5597, #5592, #5562, #5477, @BenWilson2; #5554, @juntai-zheng; #5570, @tahesse; #5605, @guelate; #5633, #5632, #5625, #5623, #5615, #5608, #5600, #5603, #5602, #5596, #5587, #5586, #5580, #5577, #5568, #5290, #5556, #5560, #5557, #5548, #5547, #5538, #5513, #5505, #5464, #5495, #5488, #5485, #5468, #5455, #5453, #5454, #5452, #5445, #5431, @harupy; #5640, @nchittela; #5520, #5422, @Ark-kun; #5639, #5604, @nishipy; #5543, #5532, #5447, #5435, @WeichenXu123; #5502, @singankit; #5500, @Sohamkayal4103; #5449, #5442, @apurva-koti; #5552, @vinijaiswal; #5511, @adamreeve; #5428, @jinzhang21; #5309, @sunishsheth2009; #5581, #5559, @Kr4is; #5626, #5618, #5529, @sisp; #5652, #5624, #5622, #5613, #5509, #5459, #5437, @dbczumar; #5616, @liangz1)