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

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