Releases: aws/sagemaker-python-sdk
Releases · aws/sagemaker-python-sdk
v2.101.1
Bug Fixes and Other Changes
- added more ml frameworks supported by SageMaker Workflows
- test: Vspecinteg2
- Add PipelineVariable annotation in amazon models
v2.101.0
Features
- Algorithms region launch on CGK
- enhance-bucket-override-support
- infer framework and version
- support clarify bias detection when facets not included
- Add CGK region to frameworks by DLC
Bug Fixes and Other Changes
- Make repack step output path align with model repack path
- Support parameterized source code input for TrainingStep
Documentation Changes
- heterogeneous cluster api doc fix
- smdmp v1.10 release note
v2.100.0
Features
- upgrade to support python 3.10
- Add target_model to support multi-model endpoints
- Added support for feature group schema change and feature parameters
Bug Fixes and Other Changes
- enable model.register without 'inference' & 'transform' instances
- rename RegisterModel inner steps to prevent duplicate step names
- remove primitive_or_expr() from conditions
- support pipeline variables for spark processors run arguments
- make 'ModelInput' field optional for inference recommendation
- Fix processing image uri param
- fix: neo inferentia as compilation target not using framework ver
Documentation Changes
- SageMaker model parallel library v1.10.0 documentation
- add detail & links to clarify docstrings
v2.99.0
Features
- heterogeneous cluster set up in distribution config
- support heterogeneous cluster for training
- include fields to work with inference recommender
Bug Fixes and Other Changes
- Moving the newly added field instance_group to the end of method
- image_uri does not need to be specified with instance_groups
- Loosen version of attrs dependency
- Add PipelineVariable annotation in estimatory, processing, tuner, transformer base classes
- model table link
Documentation Changes
- documentation for heterogeneous cluster
v2.98.0
Features
- Adding deepar image
Documentation Changes
- edit to clarify how to use inference.py
v2.97.0
Deprecations and Removals
- remove support for python 3.6
Features
- update prebuilt models documentation
Bug Fixes and Other Changes
- Skipping test_candidate_estimator_default_rerun_and_deploy
- Update model name from 'compiled.pt' to 'model.pth' for neo
- update pytest, skip hf integ temp
- Add override_pipeline_parameter_var decorator to give grace period to update invalid pipeline var args
v2.96.0
Features
- Add helper method to generate pipeline adjacency list
Bug Fixes and Other Changes
- changing trcomp integ tests to be able to run in all regions
v2.95.0
Features
- Adding Training Compiler support for TensorFlow estimator starting TF 2.9
- Add support for TF 2.9 training
Bug Fixes and Other Changes
- integs fallback from p3 to p2 instance
- bucket exists check for session.default_bucket
- make instance type fields as optional
Documentation Changes
- improvements on the docstring of ModelStep
- Add XGBoostProcessor
v2.94.0
Features
- AutoGluon 0.4.2 image_uris support
v2.93.1
Bug Fixes and Other Changes
- add input parameterization tests for workflow job steps
- add parameterized tests to transformer