Sagemaker

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

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

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

Bug Fixes and Other Changes

* added more ml frameworks supported by SageMaker Workflows
* test: Vspecinteg2
* Add PipelineVariable annotation in amazon models

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

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