Releases: aws/sagemaker-python-sdk
Releases · aws/sagemaker-python-sdk
v2.108.0
Features
- Adding support in HuggingFace estimator for Training Compiler enhanced PyTorch 1.11
Bug Fixes and Other Changes
- add sagemaker clarify image account for cgk region
- set PYTHONHASHSEED env variable to fixed value to fix intermittent failures in release pipeline
- trcomp fixtures to override default fixtures for integ tests
Documentation Changes
- add more info about volume_size
v2.107.0
Features
- support python 3.10, update airflow dependency
Bug Fixes and Other Changes
- Add retry in session.py to check if training is finished
Documentation Changes
- remove Other tab in Built-in algorithms section and mi…
v2.106.0
Features
- Implement Kendra Search in RTD website
Bug Fixes and Other Changes
- Add primitive_or_expr() back to conditions
- remove specifying env-vars when creating model from model package
- Add CGK in config for Spark Image
v2.105.0
Features
- Added endpoint_name to clarify.ModelConfig
- adding workgroup functionality to athena query
Bug Fixes and Other Changes
- disable debugger/profiler in cgk region
- using unique name for lineage test to unblock PR checks
Documentation Changes
- update first-party algorithms and structural updates
v2.104.0
Features
- local mode executor implementation
- Pipelines local mode setup
- Add PT 1.12 support
- added _AnalysisConfigGenerator for clarify
Bug Fixes and Other Changes
- yaml safe_load sagemaker config
- pipelines local mode minor bug fixes
- add local mode integ tests
- implement local JsonGet function
- Add Pipeline annotation in model base class and tensorflow estimator
- Allow users to customize trial component display names for pipeline launched jobs
- Update localmode code to decode urllib response as UTF8
Documentation Changes
- New content for Pipelines local mode
- Correct documentation error
v2.103.0
Features
- AutoGluon 0.4.3 and 0.5.2 image_uris
Bug Fixes and Other Changes
- Revert "change: add a check to prevent launching a modelparallel job on CPU only instances"
- Add gpu capability to local
- Link PyTorch 1.11 to 1.11.0
v2.102.0
Features
- add warnings for xgboost specific rules in debugger rules
- Add PyTorch DDP distribution support
- Add test for profiler enablement with debugger_hook false
Bug Fixes and Other Changes
- Two letter language code must be supported
- add a check to prevent launching a modelparallel job on CPU only instances
- Allow StepCollection added in ConditionStep to be depended on
- Add PipelineVariable annotation in framework models
- skip managed spot training mxnet nb
Documentation Changes
- smdistributed libraries currency updates
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