MLflow v1.29.0 Release Notes
Release Date: 2022-09-16 // over 1 year ago-
MLflow 1.29.0 includes several major features and improvements
๐ Features:
- ๐ [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)
- ๐ป [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()
andload_dict()
fluent APIs for convenient artifact loading (#6475, @subramaniam02) - [Tracking] Add
creation_time
andlast_update_time
attributes to the Experiment class (#6756, @subramaniam02) - ๐ณ [Tracking] Add official MLflow Tracking Server Dockerfiles to the MLflow repository (#6731, @oojo12)
- ๐ [Tracking] Add
searchExperiments
API to Java client and deprecatelistExperiments
(#6561, @dbczumar) - [Tracking] Add
mlflow_search_experiments
API to R client and deprecatemlflow_list_experiments
(#6576, @dbczumar) - ๐ป [UI] Make URLs clickable in the MLflow Tracking UI (#6526, @marijncv)
- ๐ป [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) - ๐ [Models] Add model validation support to
mlflow.evaluate()
(#6582, @jerrylian-db) - ๐ [Models] Introduce
sample_weights
support tomlflow.evaluate()
(#6806, @dbczumar) - ๐ [Models] Add
pos_label
support tomlflow.evaluate()
for identifying the positive class (#6696, @harupy) - ๐ง [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)
- ๐ [Models] Add
predict_proba()
support to the pyfunc representation of scikit-learn models (#6631, @skylarbpayne) - ๐ [Models] Add support for Decimal type inference to MLflow Model schemas (#6600, @shitaoli-db)
- ๐ณ [Models] Add new CLI command for generating Dockerfiles for model serving (#6591, @anuarkaliyev23)
- [Scoring] Add
/health
endpoint to scoring server (#6574, @gabriel-milan) - ๐ [Scoring] Support specifying a
variant_name
during Sagemaker deployment (#6486, @nfarley-soaren) - [Scoring] Support specifying a
data_capture_config
during SageMaker deployment (#6423, @jonwiggins)
๐ Bug fixes:
- [Tracking] Make Run and Experiment deletion and restoration idempotent (#6641, @dbczumar)
- ๐ป [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)
๐ Documentation updates:
- [Tracking] Mark the SearchExperiments API as stable (#6551, @dbczumar)
- โ [Tracking / Model Registry] Deprecate the ListExperiments, ListRegisteredModels, and
list_run_infos()
APIs (#6550, @dbczumar) - ๐ [Scoring] Deprecate
mlflow.sagemaker.deploy()
in favor ofSageMakerDeploymentClient.create()
(#6651, @dbczumar)
๐ 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