CHANGELOG.md

# Changelog

## v3.28.0 (2026-10-29)

### New Features

- feat(mlops): Add AthenaStep pipeline step (#6508)
- add: metadata for huggingface vllm v0.30 and v0.31 (#6526)
- change: add eusc-de-east-1 to PyTorch inference 2.6.0 image URI config (#6538)
- change: add sa-west-1 to PyTorch training image URI config (#6516)

### Bug Fixes

- fix(codegen): restore codestyle-doc-tests compliance after botocore sync (#6523)
- fix: set VolumeKmsKeyId on ModelStep runtime repack job (#6537)
- fix: use pipeline code_hash for FrameworkProcessor sourcedir upload (#6494)
- fix: keep job name in pipeline request for ModelTrainer and HyperparameterTuner (#6323)
- Fix s3 sse kms validate path (#5931)
- fix: preserve volume KMS key in HyperparameterTuner training job definition (#6522)
- fix: close the remaining gaps in optional torch support (#6531)
- fix(serve): pin pandas below 3.1.0 to unblock serve unit tests (#6524)
- fix(serve): decouple the SMD orchestrator entrypoint from the container's sagemaker (#6200) (#6534)

### Tests

- test(train): make SFT recipe-override integ tests recipe-proof (#6548)


## v3.27.0 (2026-10-21)

### New Features

- feat(mlops): Add ForEach pipeline step (#6473)
- feat(mlops): Add CleanupStep pipeline step (#6468)

### Bug Fixes

- fix: keep the Transformer's configured session when waiting on or stopping a transform job (#6509)
- fix: add g7e, p6-b200 and trn2 to volume size unsupported instance families (#6505)
- fix: carry ModelTrainer checkpoint and retry config into the tuning job definition (#6511)
- fix: discover base models by Training Sessions capability (#6506)
- fix: don't treat SageMaker model-package ARN as a HuggingFace model ID (#6513)
- fix: let ModelBuilder.build() tag the SageMaker Model it creates (#6510)
- fix: make sagemaker-serve test tooling and serving backends optional (#6512)


## v3.26.0 (2026-10-19)

### New Features

- Add sa-west-1 to JumpStart region_config and djl-neuronx image_uri config (#6478)
- Add me-west-1 (RUH) JumpStart bucket info to region_config.json (#6455)
- feat(mlops): Add run conditions to step dependencies (#6475)

### Bug Fixes

- fix: emit boto-style tag keys in ModelTrainer pipeline requests (#6485)
- fix: normalize ModelTrainer Tag objects inherited by HyperparameterTuner (#6482)
- fix: pass the configured session to ModelBuilder's Model reloads (#6487)
- fix: preserve all core container fields in ModelBuilder CreateModel requests (#6488)
- fix: accept core shapes and omitted content types in ModelBuilder.register (#6489)
- fix(serve): restore JumpStart default instance type from model spec (#6045)
- fix: put the check steps' output KMS key on ProcessingOutputConfig and send CheckJobConfig tags (#6497)
- fix: generate repack step for ModelBuilder.register/build in ModelStep (#5828, #5829) (#6338)
- fix: keep source_code for a pipeline-variable model URI and stop repack mutating caller source (#6490)

### Tests

- test(train): patch mocks at the lookup site so unit tests stop calling AWS (#6491)
- test(serve): stop unit tests resolving IAM roles over the network (#6496)


## v3.25.0 (2026-10-13)

### New Features

- feat(train): add the interactive Training Sessions client surface (#6452)

### Bug Fixes

- fix(core): prevent false-positive RoleValidationError under conditional access (#6029)
- fix(core): resolve HuggingFace version alias in image URI tag (#5722)
- fix(local): align local mode with the SageMaker service (#6317)
- fix: make local mode health-check timeout configurable via session config (#5778)
- fix(model-monitor): honor base_job_name for job definition names (#6372)
- fix(processing): fix V3 shape regressions + KMS/requirements gaps in processors (#6364)
- fix: accept CUSTOMIZATION capability in JumpStart hub documents (#6456)
- fix(train): bound pydantic to <3.0.0 for cross-package consistency (#6363)
- fix(train): set input_data_config to None (#6154)

### Tests

- chore(core): sync the bundled SageMaker service model with botocore (#6453)
- test(train): bound capacity wait in gated JumpStart train test (#6397)
- test(train): bound capacity wait in SMTJ SFT integ test (#6409)
- test(train): fail fast in HyperPod SFT integ tests (#6449)
- test(serve): fix Bedrock resource leaks in Nova integ tests (#6398)


## v3.24.0 (2026-10-07)

### New Features

- feat(core): add image_uris list_frameworks/list_versions/list_py_versions helpers (#6357)
- feat(train): add args field to SourceCode for command-based training (#6356)
- feat(train): add output_data property to ModelTrainer (#6355)
- feat(train): allow configurable S3 key prefix for ModelTrainer input uploads (#6354)
- feat(mlops): add JobStep and shared pipeline capture for CreateJob producers (#6292)
- feat: advertise Python 3.13 support (#6348)

### Bug Fixes

- fix(core): fall back to ARN in ModelPackage.refresh for versioned packages (#6378)
- fix(core): allow Constraints.set_monitoring to disable monitoring for non-string features (#6312)
- fix(core): respect session region when waiting for processing jobs (#6369)
- fix(core): reject unsupported container_version instead of returning a bad URI (#6376)
- fix(core): SageMakerClient honors the passed boto3 session and config (#6273)
- fix(core): close temp tarball before reading it (#6319)
- fix(core): make all pipeline Parameters hashable (#6351)
- fix(core): stop LineIterator hanging when the stream ends without a trailing newline (#6279)
- fix(core): stop mutating global logging state on import (#6341)
- fix(core): freeze credentials before signing bearer token (#6360)
- fix(core): make DataCaptureConfigSummary.kms_key_id optional (#6346)
- fix(core): lazily initialize DEFAULT_JUMPSTART_SAGEMAKER_SESSION (#6330)
- fix(core): add PyTorch 2.6 graviton (arm64) inference image (#6342)
- fix(train): fix incorrect model_trainer method call to load hyperparameters from file (#5771)
- fix(train): handle CRLF line endings (#6088)
- fix(train): preserve content_type when HyperparameterTuner converts InputData to Channel (#6321)
- fix(train): allow PipelineVariable keys in HyperparameterTuner hyperparameter_ranges annotation (#6314)
- fix(train): accept a PipelineVariable for HyperparameterTuner random_seed (#6320)
- fix(train): apply output KMS key to ModelTrainer source-code S3 uploads (#6339)
- fix(train): do not apply user ignore_patterns to the sm_drivers driver channel (#6316)
- fix(serve): stop deploy waits hanging; follow empty list pages (#6367)
- fix(serve): pass instance_type to _deploy once when creating an inference component (#6203)
- fix(serve): support pipeline variable image_uri in ModelBuilder.build (#6347)
- fix(serve): default AsyncPredictor upload prefix to endpoint name (#6336)
- fix(serve): keep AsyncPredictor serializers in sync with wrapped predictor (#6335)
- fix(mlops): clean up temp CSV in AthenaQuery.as_dataframe (#6344)
- fix(mlops): set full s3_input fields on QualityCheckStep baseline_dataset pipeline-variable input (#6322)
- fix(mlops): convert ParallelismConfiguration to request dict before boto pipeline calls (#6315)
- fix(mlops): write repack launcher with LF endings so pipelines built on Windows work (#6313)

### Tests

- test(image_uris): derive pytorch-amzn2023 versions from config (#6385)
- test(train): serialize Nova serverless integ jobs (#6387)
- test(train): stop MTRL training integ tests churning fixture MPG (#6362)
- test(train): stop test_sourcecode_args from depending on an ambient HOME (#6383)
- test(serve): skip hang-prone endpoint integ tests in PR check (#6332)
- style(serve): drop unused pytest imports in integ tests (#6361)

### Other

- change: update image_uri_configs (#6374)
- docs: fix typo in shapes.py docstring (#5545)


## v3.23.0 (2026-09-24)

### New Features

- feat(pipeline): add inference and lineage step types (#6224)
- feat(train): finetuningoptions validation telemetry (#6286)
- feat(train): apply constructor hyperparameters in fine-tuning trainers (#6293)
- feat(serve): update SDK to use latest LMI v29 image for sdk v3.x (#6301)

### Bug Fixes

- fix(core): recognize new duplicate-name wording; actionable train() errors (#6256)
- fix(train): raise on invalid constructor hyperparameters (#6306)
- fix(core): keep environment variable names intact when parsing private hub model documents (#6204)
- fix: migrate llama-cpp-arm64 to cpu processor schema and align image_uri unit tests (#6290)
- fix(serve): use the correct AMI when on cu130 to avoid crashes at launch (#6281)

### Other

- change: update image_uri_configs 09-23-2026 (#6308)
- change: update image_uri_configs 09-22-2026 (#6304)
- add: metadata for huggingface vllm v0.29 (#6300)

### Tests

- fix PR check tests (#6272)
- fix: codestyle-doc-tests pass in all four submodules (#6294)


## v3.22.1 (2026-09-17)

### Bug Fixes

- fix(jumpstart): name JumpStart in the content bucket error (#6243)
- fix(core): send NextToken when Hub.list_models pages through hub contents (#6263)
- fix(train): enforce S3 ownership on ai_registry default bucket (#6275)
- fix: vllm and vllm-omni tasks in routing logic (#6007)
- fix: restore model customization reuse state (#6264)

### Other

- add: metadata for hf-vllm 0.22.1, 0.25.1, 0.26, 0.27.1 and 0.28 (#6060)
- add sklearn 1.9-0 image URI config (#6037)


## v3.22.0 (2026-09-14)

### New Features

- feat(train): add list_hyperparameters() for pre-trainer hyperparameter discovery (#6149)
- feat(train): validate raw base model names in SageMaker Hub (#6227)
- feat(core,train): add InstancePreferences for multi-instance-type training and processing (#6249)
- feat(feature-store): add UpdateRecord API and Standard_V2 storage type (#6247)

### Bug Fixes

- fix(train): add PipelineSession support to SFT, DPO, RLAIF, and RLVR trainers (#6213)
- fix(feature-store): register HubContent Dataset from DatasetBuilder CSV paths (#6212)
- fix(local): detect docker compose v2+ when version has no 'v' prefix (#6231)
- fix(train): resolve private Hub models and aliased references for ModelTrainer (#6201)
- fix(core): resolve default training role from sagemaker config (#6228)
- fix(train): validate evaluator models against the live supported-model list (#6217)
- fix(train): complete PipelineSession support for SFT, DPO, RLAIF, and RLVR trainers (#6235)
- fix(train): preserve training_plan_arn during serverful compute reconstruction (#6258)

### Other

- change(core): add image URI configs for DLC serving frameworks and Amazon Linux 2023 PyTorch (#6220)
- change(core): add image URI configs for vLLM and SGLang (#6218)
- ci(core): add botocore-sync workflows (#6226)
- change(core): add TensorFlow inference 2.20 and training 2.21 image URI configs (#6230)
- change(core): add Ray/llama-cpp CPU images and device-selectable DLC serving configs (#6229)
- change(core): refresh generated image URI configs (55c2a9bd)
- change(serve): emit the JumpStart model ID in ModelBuilder telemetry (#6234)

### Tests

- fix(ci,train): stop integ tests from rerunning the shallow suite (#6216)
- docs(train): add guidance for maintaining shallow integration tests (#6219)
- fix(train): refresh MTRL attached-job integration fixtures (#6259)
- fix(train): add training_plan_arn to serverful test fixtures (#6270)

## v3.21.0 (2026-08-25)

### New Features

- feat(train): Add inherited list_supported_models to BaseTrainer (#6187)

### Bug Fixes

- fix(core,mlops): honor caller region in feature_store ingest_dataframe and stop telemetry from blocking SDK calls (#6197)
- fix(core): anchor tar member validation to extract_path (#6195)
- fix(rlaif): accept preset reward_prompt template names (#6192)
- fix(serve): pre-deploy JumpStart benchmark data + public HuggingFace download helper (#6175)
- fix(tgi): honor S3 model_path as weight source for TGI builds (#5964)

### Tests

- change(train): gate deep integ tests behind gpu_intensive, add shallow submit-then-stop suite (#6176)
- fix(ci,train): run fast-integ-tests in CodeBuild and give shallow RLVR cases a reward signal (#6207)
- fix(train): make CPT integ tests dry run for optimize for capacity constraints (#6194)
- test(serve): add skip_in_pr_check marker for hang-prone integ tests (#6190)
- test(train): add unit test to prevent future regression of preset reward function (#6182)


## v3.20.0 (2026-08-14)

### New Features

- feat(serve): list/filter jobs, deploy from recommendation row, compare benchmarks, DataFrame views (#6148)

### Bug Fixes

- fix(train): revert preset reward function deletion from hyperparams dict (#6181)
- fix(serve): validate ECR registry host before docker login (#6160)
- fix(mlops): Add pre-validation for Bedrock and MLflow role permissions (#6162)
- fix(core): propagate user-supplied tags to created resources (#6167)

### Tests

- test(train): Fix RLVR integ test (#6183)
- test(train): update timeout of RLVR sequence_length test (#6180)
- test(serve): SD/KT-IC integ must use g6.2xlarge, not g4dn (#6141)


## v3.19.0 (2026-08-10)

### New Features

- feat(train): Add SequenceLength support for SFT, DPO, RLVR, RLAIF trainers (#5965)
- feat(train): Job notifications, log streaming, and metrics visualization for training jobs (#6051)
- feat(serve): Model Reuse — reuse previously built models across deployments (#6051)
- feat(core): Nova follow-ups — IAM role resolution and training utils (#6051)

### Bug Fixes

- fix(serve): propagate additional_model_data_sources for JumpStart models (#6151)
- fix(serve): forward tolerance flags from get_jumpstart_configs (#6137)
- fix(serve): create local model_path dir before using it as download dir (#6147)
- fix(serve): remove IC data-source collapse hack from recommendation deploy (#6101)


## v3.18.0 (2026-07-30)

### New Features

- feat(serve): make BenchmarkResult sweep-aware for concurrency search runs (#6098)
- feat(feature-store): Add lineage registration to DatasetBuilder (#6014)

### Bug Fixes

- fix(sagemaker-core): remove dev-only endpoint override and fix client singleton pinning (#6120)
- fix(sagemaker-core): use caller session for sagemaker control-plane client (#6107)
- fix(sagemaker-core): drop tags before rebuilding TransformJob in transform() (#6110)
- fix(train): assign SDK-managed channels to instance groups on heterogeneous clusters (#6116)
- fix: infer logic of agent_run_time from the attached input trainer (#6115)
- fix(serve): repack source_code for image_uri/ModelTrainer builds (#6112)
- fix: Telemetry INFO logging to print only once per process (#6083)


## v3.17.0 (2026-07-24)

### New Features

- feat: update SDK to use latest LMI v27 image for sdk v3.x (#5976)
- feat(serve): support fine-tuned models in deployment-config API (#6041)
- feat: Wire BatchWriteRecord and ListRecords into ingest_dataframe (#6026)

### Bug Fixes

- fix: Fix source_dir in FrameworkProcessor (#6047)
- fix(train): correct Networking field names in ModelTrainer intelligent defaults (#6064)
- fix: resolve MTRL eval base-model ARN against the configured hub (#6040)
- fix(train): Fall back to public hub when private hub lacks base model (#6092)
- fix: datamixing recipe path fix (#6073)
- fix: Fix private hub (#6036)
- fix(serve): support aliased hub content names in private hub deploys (#6039)
- fix(serve): dedicated INFERENCE_RECOMMENDER telemetry feature + type workload param (#6028)
- fix: Fixing EULA check, relying on HostingEulaUri field (#6077)

### Tests

- test: Doc update and added SFT integ test (#6018)
- test: Fix role issue in mtrl integ tests (#6070)
- test: Fix gpu integ test failure due to outdated MPG (#6097)
- test: move two tests in serve to gpu-integ-tests (#6096)
- test(feature-processor): Isolate pipeline names to fix flaky integ tests (#6095)
- test(integ): absorb iam:SimulatePrincipalPolicy throttling across suites (#6081)
- test(integ): let exhausted IAM throttling fail instead of skipping (#6094)

## v3.16.0 (2026-07-15)

### New Features

- feat: actionable guidance for removed v2 interfaces (#6004)
- feat(serve): add SageMaker GenAI inference benchmarking and recommendation (#5874)
- feat(feature-store): add BatchWriteRecord and ListRecords to FeatureGroup (#5983)

### Bug Fixes

- fix(iam): scope repo-level ECR actions to prevent false deny in preflight validation (#6024)
- fix: filter full recipe template from serverless train() (#6021)
- Fix sm-train unit tests + use single logger in base trainer (#6030)

### Tests

- test(mlops): Skip non-PEP440 version keys in sklearn_latest_version (#6022)

## v3.15.1 (2026-07-09)

### New Features

- feat: Add granular telemetry signals decorator params and error classification (#5963)

### Bug Fixes

- fix: always apply evaluator identity keywords and allow explicit domain_id (#5989)
- fix: ModelBuilder resolves private hub artifacts correctly (#5985)
- fix: refresh LLMAsJudgeEvaluator allowed evaluator models (#5987)
- fix: define LAMBDA_ARN_REGEX in finetune_utils to fix RLVRTrainer NameError (#5988)
- fix: RLVR validation bugfix (#6000)
- fix: drop claude-sonnet-4-20250514 from evaluator allowlist (#6009)
- fix(serve): Invoke pip without shell in xgboost install_package (#5981)
- fix: Correct DJL-LMI ISO/ADC accounts + add THF/ISO-E (djl-lmi, huggingface-llm-neuronx) (#5980)

### Documentation

- docs: Add AGENTS.md and llms.txt for AI agent v3 guidance (#5982)
- docs: Add SDK-first guidance to AGENTS.md and llms.txt (#5997)
- docs: Add Version Lifecycle page under Getting Started (#5994)
- docs: serve robots.txt opting V2 docs out of AI training crawls (#6003)

### Other

- Add Triton Server v26.05 image URI config (#5999)
- Add sklearn 1.4-2-py312 and xgboost 3.2-0 image URI configs (#6008)
- test: Fix/v3 tests (#5996)
- test: wip nova hyperpod integ tests (#5990)

## v3.15.0 (2026-06-22)

### New Features

- **feat: Training — Recipes** - Add 3-level recipe override support with `get_resolved_recipe()`
- **feat: Training — Recipes** - Recipe override handling
- **feat: Training — Recipes** - Add Nova-specific recipe validations
- **feat: Training — Recipes** - Auto-resolve HyperPod recipe from Hub
- **feat: Training — Compute/Infra** - Add Serverless / SMTJ / HyperPod support to trainers and evaluators
- **feat: Training — Compute/Infra** - Add infra validation
- **feat: Training — Methods & Data** - Enable Data Mixing for Nova models
- **feat: Training — Methods & Data** - Add `is_multimodal` utils function (multimodal data auto-detection)
- **feat: Training — Methods & Data** - RLVRTrainer Lambda ARN support
- **feat: Training — Methods & Data** - RLVR reward Lambda validation
- **feat: Evaluation** - InspectAI evaluator
- **feat: Evaluation** - Add Nova as a target for LLM-as-a-Judge (LLMAJ)
- **feat: Evaluation** - Support serverful training job checkpoint resolution in InspectAI evaluator
- **feat: Deploy/Setup/Validation** - Add Nova SMI config bounds validation to ModelBuilder
- **feat: Deploy/Setup/Validation** - IAM role creation (auto-create least-privilege execution roles, SDK-wide)
- **feat: Deploy/Setup/Validation** - HyperPod IAM creation

### Bug Fixes

- fix: Reject unknown recipe overrides (serverless + serverful) and untrusted IAM roles
- fix: Apply recipe overrides to hyperparameters in SMTJ serverful path
- fix: Recipe override errors in evaluator
- fix: Hub-content IAM perms, recipe dataset paths, and log markup escaping
- fix: Harden auto-created IAM roles and protect curated recipe keys
- fix: Add HyperPod validation in train and evaluate
- fix: Evaluation on HyperPod
- fix: Resolve HyperPod training image from EKS payload template
- fix: Skip `model_package_group` validation when HyperPod compute is provided in CPTTrainer
- fix: Use compute param in get fine-tuning utils
- fix: Set Converse as S3DataType for Nova models in SMTJ Serverful for SFT and DPO
- fix: Use Converse S3DataType for Nova SFT/DPO in serverless flow
- fix: MLflow error causing OSS model eval to fail
- fix: RLVR setup and reward Lambda handling

## v3.14.0 (2026-06-18)

### Other

- chore: deprecate Python 3.9 support (#5941)
- chore: update SDK to use latest LMI image for v3.x (#5954)

## v3.13.1 (2026-06-04)

### New Features

- feat: add import job polling and provisioned throughput for Bedrock OSS deployments

### Bug Fixes

- fix: Address MTRL Eval Hyperparameters issue

## v3.13.0 (2026-06-02)
### New Features

- **feat: Model customization** - Add new finetuning Trainer - MultiTurnRLTrainer(Multi-Turn Reinforcement Learning)
- **feat: Model customization** - Add new evaluator - MultiTurnRLEvaluator
- **feat: Deployment** - Add MTRL support for BedrockModelBuilder and ModelBuilder.

### Documentation

- Add details for MTRL trainer along with other finetuning interfaces under Model customization Section - https://sagemaker.readthedocs.io/en/stable/model_customization/model_customization.html
- Add details for MTRL evaluator along with existing evaluators.

### Bug Fixes

- fix: set sagemaker_config=None on mock session in test_from_jumpstart_config_applies_volume_size
- Restore BatchTransformInput.destination attribute in v3

## v3.12.0 (2026-05-19)

### New Features
- **SageMaker Token Generator** (#5868): Embed the `aws-sagemaker-token-generator` library into `sagemaker.core` so users can generate SageMaker bearer tokens without installing a separate wheel. Usage: `from sagemaker.core.aws_sagemaker_token_generator import provide_token`
- **Feature Processor - Lake Formation credential vending** (#5816): Add configurable `use_lake_formation_credentials` parameter to the `@feature_processor` decorator, enabling Lake Formation credential vending when set to `True`.
- **Feature Processor - Spark 3.5 / Python 3.12 support** (#5816): Dynamic Spark image resolution based on installed PySpark and Python versions. Supports Spark 3.1/3.2/3.3/3.5 with Python 3.9 and 3.12. Auto-installs `sagemaker-feature-store-pyspark` for Spark remote jobs.
- **Feature Processor - Stored function signing key** (#5816): Generate ECDSA signing key in `ConfigUploader` for function payload signature verification.
- **Feature Store - Export IcebergProperties** (#5816): Add `IcebergProperties` to the `feature_store` public API surface.

### Documentation
- None

### Bug Fixes
- **Networking** `vpc_config` AttributeError and telemetry region fallback (#5839): Fix `AttributeError` on `vpc_config` in networking and telemetry region fallback for classmethods.
- **Add CustomAttributes field to DefaultPayloadsModel** (#5870): Add missing `CustomAttributes` field to `DefaultPayloadsModel`.
- **sagemaker-core**: Preserve falsy values in `serialize()` output (#5860): Fix bug where `False`, `0`, and `""` were silently dropped by `serialize()` due to truthy check. This caused issues like `optimize_model=False` being sent as `True`.
- **serve**: Prevent code injection in `capture_dependencies` path interpolation (#5792): Security fix — use `repr()` escaping to prevent code injection via crafted directory names in `ModelBuilder` with `dependencies={"auto": True}`. (CWE-94, P414309851)
- **VolumeSizeInGB** missing from v3 deploy for JumpStart models (#5847): Fix `VolumeSizeInGB` not being passed through when deploying models with `inference_volume_size` from JumpStart config.

## v3.11.0 (2026-05-12)

### New Features
- Auto-detect subscription recipe hyperparameters in SFTTrainer for Nova Forge datamix support
- Create asymmetric ECDSA signing key in feature processor step compiler for remote function payload verification

### Documentation
- Add Feature Store reference to Implement MLOps page
- Replace internal S3 URIs with user placeholders in SFT notebook

## v3.10.1 (2026-05-07)

### Bug Fixes
- Fix KMS key propagation in check steps (QualityCheckStep, ClarifyCheckStep)
- Fix JumpStart network isolation in ModelBuilder
- Fix base_model_arn construction to use private hub when SAGEMAKER_HUB_NAME is set
- Fix imports for Model Customization interfaces
- Fix handling of unrecognized JumpStart container images in ModelBuilder
- Increase default timeout for training jobs

## v3.10.0 (2026-05-01)

### New Features
- Make _PipelineExecution a public class
- Add CodeArtifact support for ModelTrainer and FrameworkProcessor requirements.txt installation

### Bug Fixes
- Fix S3 bucket operations
- Fix potential S3 path traversal
- Wire FrameworkProcessor code_location into code upload paths
- Improve subprocess exception handling in git_utils

### Other
- Update service-2.json with latest public botocore service model

## v3.9.0 (2026-04-23)

### New Features
- **Train**: Add `wait_timeout` parameter to `train()` for SFT, DPO, RLAIF, RLVR, and BaseTrainer
- **Evaluate**: Add MLflow experiment link to eval output
- **JumpStart**: Allow `SAGEMAKER_HUB_NAME` environment variable to override the `HUB_NAME` constant

### Bug Fixes
- **HyperparameterTuner**: Pass through full `OutputDataConfig` from `ModelTrainer` so `kms_key_id`, `compression_type`, and other fields are preserved
- **HyperparameterTuner / ModelTrainer**: Propagate environment variables that were previously dropped
- **sagemaker-core**: Improve error messages for waiter timeouts
- **ModelBuilder**: Stop overwriting user-provided `HF_MODEL_ID` for DJL Serving
- **ModelBuilder**: Keep `/opt/ml/model` writable when using `source_code` with DJL LMI
- **Evaluate**: Skip `None` hyperparameters in `to_dict` instead of converting them to the string `"None"`
- **Nova**: Add `us-west-2` to Nova supported regions
- **DJL LMI**: Update ISO account mappings

## v3.8.0 (2026-04-16)

### New Features
- **Feature Group Manager**: Feature Group Manager support
- **Image Upgrades**: Image upgrades

### Bug Fixes
- **ModelBuilder**: Add MLFlowConfig to Base Model
- **Docker**: Support for docker compose > v2
- **HuggingFace**: Improve SDK v3 Hugging Face support
- **Dependencies**: Remove Pytorch hard dependency
  
## v3.7.1 (2026-03-31)

### Features
- **Telemetry**: Added telemetry emitter to `ScriptProcessor` and `FrameworkProcessor`, enabling SDK usage tracking for processing jobs via the telemetry attribution module (new `PROCESSING` feature enum added to telemetry constants)

### Fixes
- **ModelBuilder**: Fixed `accept_eula` handling in ModelBuilder's LoRA deployment path — previously hardcoded to `True`, now respects the user-provided value and raises a `ValueError` if not explicitly set to `True`
- **Evaluate**: Fixed Lambda handler name derivation in the Evaluator — hardcoded the handler to `lambda_function.lambda_handler` instead of deriving it from the source filename, which caused invocation failures when the source file had a non-default name

## v3.7.0 (2026-03-25)

### Fixes
- **ModelBuilder**: Sync Nova hosting configs with AGISageMakerInference (#5664)
- **Evaluate**: Remove GPT OSS model evaluation restriction (#5658)

### Features
- **AWS Batch**: Add support for Quota Management job submission and job priority update (#5659)
- **AWS Batch**: Extend list_jobs_by_share for quota_share_name (#5669)
- **Evaluate**: Support IAM role for BaseEvaluator (#5671)
- **Telemetry**: Add telemetry attribution module for SDK usage provenance (#5661)
- **MLflow**: Metrics visualization, enhanced wait UI, and eval job links (#5662)

### Chores
- Updated SDK to use latest LMIv22 image for v3.x (#5640)
- Migration guide update (#5655)
- AWS Batch integ test resources are now uniquely named by test run (#5666)

## v3.6.0 (2026-03-19)

### Fixes
- **HyperparameterTuner**: Include sm_drivers channel in HyperparameterTuner jobs (#5516)
- **Pipeline**: Fix handling of training step dependencies to allow successful pipeline creation
- **ModelBuilder**: Fix the bug in deploy from LORA finetuning job

### Features
- **Feature Processor**: Port feature processor to v3
- **Jumpstart**: Add EUSC region config for JumpStart
  
## v3.5.0 (2026-03-02)

### Features
- **Feature Store v3**: New version of Feature Store functionality
- **Batch job listing by share identifier**: Added support for listing Batch jobs filtered by share identifier
- **Stop condition for model customization trainers**: Added stopping condition support to model customization trainers
- **EMRStep smart output**: Enhanced EMR step output handling with smart output capabilities
- **Transform AMI version support**: Added support for specifying AMI version in SageMaker transform jobs

### Enhancements
- **Inference pipeline notebook example**: Added example notebook demonstrating inference pipeline usage
- **Migration documentation**: Added migration documentation

### Bug Fixes
- **Model Customization bugs**: Fixed multiple issues in Model Customization functionality
- **Default stopping condition removal**: Removed default stopping condition for MC trainer to prevent conflicts
- **Instance groups parameter handling**: Fixed issue where default instance_type/instance_count were incorrectly applied when instance_groups was set
- **JumpStart alt config resolution**: Resolved alternative configuration resolution for JumpStart models
- **Inference processor naming**: Updated inference processor identifier from 'inf2' to 'neuronx'
- **HuggingFace Neuronx PyTorch version**: Corrected the PyTorch version for HuggingFace Neuronx
- **License additions**: Added license to sagemaker-mlops and sagemaker-serve packages

## v3.4.1 (2026-02-10)

### Fixes
- **Pipelines**: Correct Tag class usage in pipeline creation (#5526)
- **ModelTrainer**: Support PipelineVariables in hyperparameters (#5519)
- **HyperparameterTuner**: Include ModelTrainer internal channels (#5516)
- **Experiments**: Don't apply default experiment config for pipelines in non-Eureka GA
regions (#5500)

### Features
- **JumpStart**: Added ISO regions support (#5505)
- **JumpStart**: Added version 1.4 and 1.5 (#5538)

### Chores
- Added unit and integration tests for JumpStart search functionality (#5544)
- Removed java-kotlin from CodeQL workflow (#5517)

## v3.4.0 (2026-01-22)

### Features
  - feat: add emr-serverless step for SageMaker Pipelines

### Bug fixes and Other Changes
  - Add Nova recipe training support in ModelTrainer 
  - Add Partner-app Auth provider
  - Add sagemaker dependency for remote function by default V3


## v3.3.1 (2026-01-12)
### Bug fixes and Other Changes
  * ProcessingJob fix - Remove tags in Processor while Job creation
  * Telemetry Updates
  * sagemaker-mlops bug fix - Correct source code 'dependencies' parameter to 'requirements'
  * aws_batch bug fix - remove experiment config parameter as it Estimator is deprecated.


## v3.3.0 (2025-12-19)

### Features
  * AWS_Batch: queueing of training jobs with ModelTrainer
### Bug fixes and Other Changes
  * Fixes for model registry with ModelBuilder

## v3.2.0 (2025-12-18)

### Features
  * Evaluator handshake with trainer
  * Datasets Format validation
### Bug fixes and Other Changes
  * Add xgboost 3.0-5 to release
  * Fix get_child_process_ids parsing issue

## v3.1.1 (2025-12-10)

### Bug fixes and Other Changes
* Add validation to bedrock reward models
* Hyperparameter issue fixes, Add validation s3 output path
* Fix the recipe selection for multiple recipe scenario
* Train wait() timeout exception handling
* Update example notebooks to reflect recent code changes
* Update `model_package_group_name`  param to `model_package_group`  in finetuning interfaces
* remove `dataset` param for benchmark evaluator

## v3.1.0 (2025-12-03)

### Features

* Fine-tuning SDK: SFT, RLVR, and RLAIF techniques with standardized parameter design
* AIRegistry Integration: Added CRUD operations for datasets and evaluators
* Enhanced Training Experience: Implemented MLFlow metrics tracking and deployment workflows

## v3.0.1 (2025-11-19)

* Update project dependencies to include submodules: sagemaker-core, sagemaker-train, sagemaker-serve, sagemaker-mlops

## v3.0.0 (2025-11-19)

### Major Version Release

#### ⚠️ Breaking Changes

#### Important: Please review these breaking changes before upgrading.

* Version 3.0.0 represents a significant milestone in our product's evolution. This major release introduces a modernized architecture, enhanced performance, and powerful new features while maintaining our commitment to user experience and reliability.
* Older interfaces such as Estimator, Model, Predictor and all their subclasses will not be supported in V3. 
* Please review documentation of interfaces for parameters support (especially ModelBuilder)

## v2.254.1 (2025-10-31)

### Bug Fixes and Other Changes

 * update get_execution_role to directly return the ExecutionRoleArn if it presents in the resource metadata file
 * [hf] HF PT Training DLCs

## v2.254.0 (2025-10-29)

### Features

 * Triton v25.09 DLC

### Bug Fixes and Other Changes

 * Add Numpy 2.0 support
 * add HF Optimum Neuron DLCs
 * [Hugging Face][Pytorch] Inference DLC 4.51.3
 * [hf] HF Inference TGI

## v2.253.1 (2025-10-14)

### Bug Fixes and Other Changes

 * Update instance type regex to also include hyphens
 * Revert the change "Add Numpy 2.0 support"
 * [hf-tei] add image uri to utils
 * add TEI 1.8.2

## v2.253.0 (2025-10-10)

### Features

 * Added condition to allow eval recipe.
 * add model_type hyperparameter support for Nova recipes

### Bug Fixes and Other Changes

 * Fix for a failed slow test: numpy fix
 * Add numpy 2.0 support
 * chore: domain support for eu-isoe-west-1
 * Adding default identity implementations to InferenceSpec
 * djl regions fixes #5273
 * Fix flaky integ test

## v2.252.0 (2025-09-29)

### Features

 * change S3 endpoint env name
 * add eval custom lambda arn to hyperparameters

### Bug Fixes and Other Changes

 * merge rba without the iso region changes
 * handle trial component status message longer than API supports
 * Add nova custom lambda in hyperparameter from estimator
 * add retryable option to emr step in SageMaker Pipelines
 * Feature/js mlops telemetry
 * latest tgi

## v2.251.1 (2025-08-29)

### Bug Fixes and Other Changes

 * chore: onboard tei 1.8.0

## v2.251.0 (2025-08-21)

### Features

 * support pipeline versioning

### Bug Fixes and Other Changes

 * GPT OSS Hotfix
 * dockerfile stuck on interactive shell
 * add sleep for model deployment

## v2.250.0 (2025-08-08)

### Features

 * Add support for InstancePlacementConfig in Estimator for training jobs running on ultraserver capacity

### Bug Fixes and Other Changes

 * Add more constraints to test requirements

## v2.249.0 (2025-07-31)

### Features

 * AWS Batch for SageMaker Training jobs

### Bug Fixes and Other Changes

 * Directly use customer-provided endpoint name for ModelBuilder deployment.
 * update image_uri_configs 07-23-2025 07:18:25 PST

## v2.248.2 (2025-07-22)

### Bug Fixes and Other Changes

 * Relax boto3 version requirement
 * update image_uri_configs 07-22-2025 07:18:25 PST
 * update image_uri_configs 07-18-2025 07:18:28 PST
 * add hard dependency on sagemaker-core pypi lib
 * When rootlessDocker is enabled, return a fixed SageMaker IP

## v2.248.1 (2025-07-16)

### Bug Fixes and Other Changes

 * Nova training support

## v2.248.0 (2025-07-15)

### Features

 * integrate amtviz for visualization of tuning jobs

### Bug Fixes and Other Changes

 * build(deps): bump requests in /tests/data/serve_resources/mlflow/pytorch
 * build(deps): bump protobuf from 4.25.5 to 4.25.8 in /requirements/extras
 * build(deps): bump mlflow in /tests/data/serve_resources/mlflow/xgboost
 * build(deps): bump torch in /tests/data/modules/script_mode
 * sanitize git clone repo input url
 * Adding Hyperpod feature to enable hyperpod telemetry
 * Adding Hyperpod feature to enable hyperpod telemetry
 * Bump SMD version to enable custom workflow deployment.
 * Update TF DLC python version to py312
 * update image_uri_configs 07-04-2025 07:18:27 PST
 * update image_uri_configs 06-26-2025 07:18:35 PST
 * relax protobuf to <6.32

## v2.247.1 (2025-06-23)

### Bug Fixes and Other Changes

 * update image_uri_configs 06-19-2025 07:18:34 PST

## v2.247.0 (2025-06-13)

### Features

 * Add support for MetricDefinitions in ModelTrainer

### Bug Fixes and Other Changes

 * update jumpstart region_config, update image_uri_configs 06-12-2025 07:18:12 PST
 * Add ignore_patterns in ModelTrainer to ignore specific files/folders
 * Allow import failure for internal _hashlib module

## v2.246.0 (2025-06-04)

### Features

 * Triton v25.04 DLC

### Bug Fixes and Other Changes

 * Update Attrs version to widen support
 * update estimator documentation regarding hyperparameters for source_dir

## v2.245.0 (2025-05-28)

### Features

 * Correct mypy type checking through PEP 561

### Bug Fixes and Other Changes

 * MLFLow update for dependabot
 * addWaiterTimeoutHandling
 * merge method inputs with class inputs
 * update image_uri_configs 05-20-2025 07:18:17 PST

## v2.244.2 (2025-05-19)

### Bug Fixes and Other Changes

 * include model channel for gated uncompressed models
 * clarify model monitor one time schedule bug
 * update jumpstart region_config 05-15-2025 07:18:15 PST
 * update image_uri_configs 05-14-2025 07:18:16 PST
 * Add image configs and region config for TPE (ap-east-2)
 * Improve defaults handling in ModelTrainer

## v2.244.1 (2025-05-15)

### Bug Fixes and Other Changes

 * Fix Flask-Limiter version
 * Fix test_huggingface_tei_uris()
 * huggingface-llm-neuronx dlc
 * huggingface-neuronx dlc image_uri
 * huggingface-tei dlc image_uri
 * Fix test_deploy_with_update_endpoint()
 * add AG v1.3
 * parameter mismatch in update_endpoint
 * remove --strip-component for untar source tar.gz
 * Fix type annotations
 * chore: Allow omegaconf >=2.2,<3
 * honor json serialization of HPs
 * Map llama models to correct script
 * pin test dependency
 * fix bad initialization script error message
 * Improve error logging and documentation for issue 4007
 * build(deps): bump scikit-learn
 * build(deps): bump mlflow
 * build(deps): bump mlflow in /tests/data/serve_resources/mlflow/pytorch
 * chore: Add tei 1.6.0 image

## v2.244.0 (2025-05-02)

### Features

 * support custom workflow deployment in ModelBuilder using SMD image.

### Bug Fixes and Other Changes

 * Add Owner ID check for bucket with path when prefix is provided
 * Add model server timeout
 * pin mamba version to 24.11.3-2 to avoid inconsistent test runs
 * Update ModelTrainer to support s3 uri and tar.gz file as source_dir
 * chore: add huggingface images

## v2.243.3 (2025-04-23)

### Bug Fixes and Other Changes

 * update readme to reflect py312 upgrade
 * Revert the PR changes 5122
 * Py312 upgrade step 2: Update dependencies, integ tests and unit tests
 * update pr test to deprecate py38 and add py312
 * update image_uri_configs 04-16-2025 07:18:18 PST
 * update image_uri_configs 04-15-2025 07:18:10 PST
 * update image_uri_configs 04-11-2025 07:18:19 PST

## v2.243.2 (2025-04-16)

### Bug Fixes and Other Changes

 * tgi image uri unit tests
 * Fix deepdiff dependencies

## v2.243.1 (2025-04-11)

### Bug Fixes and Other Changes

 * Added handler for pipeline variable while creating process job
 * Fix issue #4856 by copying environment variables
 * remove historical job_name caching which causes long job name
 * Update instance gpu info
 * Master
 * Add mlflow tracking arn telemetry
 * chore: fix semantic versioning for wildcard identifier
 * flaky test

### Documentation Changes

 * update pipelines step caching examples to include more steps
 * update ModelStep data dependency info

## v2.243.0 (2025-03-27)

### Features

 * Enabled update_endpoint through model_builder

### Bug Fixes and Other Changes

 * Update for PT 2.5.1, SMP 2.8.0
 * chore: move jumpstart region definitions to json file
 * fix flaky clarify model monitor test
 * fix flaky spark processor integ
 * use temp file in unit tests
 * Update transformers version
 * Aligned disable_output_compression for @remote with Estimator
 * Update Jinja version
 * update image_uri_configs  03-26-2025 07:18:16 PST
 * chore: fix integ tests to use latest version of model
 * update image_uri_configs  03-25-2025 07:18:13 PST
 * Skip tests failed due to deprecated instance type
 * update image_uri_configs  03-21-2025 07:17:55 PST
 * factor in set instance type when building JumpStart models in ModelBuilder.
 * ADD Documentation to ReadtheDocs for Upgrading torch versions
 * add new regions to JUMPSTART_LAUNCHED_REGIONS

## v2.242.0 (2025-03-14)

### Features

 * add integ tests for training JumpStart models in private hub

### Bug Fixes and Other Changes

 * Torch upgrade
 * Prevent RunContext overlap between test_run tests
 * remove s3 output location requirement from hub class init
 * Fixing Pytorch training python version in tests
 * update image_uri_configs  03-11-2025 07:18:09 PST
 * resolve infinite loop in _find_config on Windows systems
 * pipeline definition function doc update

## v2.241.0 (2025-03-06)

### Features

 * Make DistributedConfig Extensible
 * support training for JumpStart model references as part of Curated Hub Phase 2
 * Allow ModelTrainer to accept hyperparameters file

### Bug Fixes and Other Changes

 * Skip tests with deprecated instance type
 * Ensure Model.is_repack() returns a boolean
 * Fix error when there is no session to call _create_model_request()
 * Use sagemaker session's s3_resource in download_folder
 * Added check for the presence of model package group before creating one
 * Fix key error in _send_metrics()

## v2.240.0 (2025-02-25)

### Features

 * Add support for TGI Neuronx 0.0.27 and HF PT 2.3.0 image in PySDK

### Bug Fixes and Other Changes

 * Remove main function entrypoint in ModelBuilder dependency manager.
 * forbid extras in Configs
 * altconfig hubcontent and reenable integ test
 * Merge branch 'master-rba' into local_merge
 * py_version doc fixes
 * Add backward compatbility for RecordSerializer and RecordDeserializer
 * update image_uri_configs  02-21-2025 06:18:10 PST
 * update image_uri_configs  02-20-2025 06:18:08 PST

### Documentation Changes

 * Removed a line about python version requirements of training script which can misguide users.

## v2.239.3 (2025-02-19)

### Bug Fixes and Other Changes

 * added ap-southeast-7 and mx-central-1 for Jumpstart
 * update image_uri_configs  02-19-2025 06:18:15 PST

## v2.239.2 (2025-02-18)

### Bug Fixes and Other Changes

 * Add warning about not supporting torch.nn.SyncBatchNorm
 * pass in inference_ami_version to model_based endpoint type
 * Fix hyperparameter strategy docs
 * Add framework_version to all TensorFlowModel examples
 * Move RecordSerializer and RecordDeserializer to sagemaker.serializers and sagemaker.deserialzers

## v2.239.1 (2025-02-14)

### Bug Fixes and Other Changes

 * keep sagemaker_session from being overridden to None
 * Fix all type hint and docstrings for callable
 * Fix the workshop link for Step Functions
 * Fix Tensorflow doc link
 * Fix FeatureGroup docstring
 * Add type hint for ProcessingOutput
 * Fix sourcedir.tar.gz filenames in docstrings
 * Fix documentation for local mode
 * bug in get latest version was getting the max sorted alphabetically
 * Add cleanup logic to model builder integ tests for endpoints
 * Fixed pagination failing while listing collections
 * fix ValueError when updating a data quality monitoring schedule
 * Add docstring for image_uris.retrieve
 * Create GitHub action to trigger canaries
 * update image_uri_configs  02-04-2025 06:18:00 PST

## v2.239.0 (2025-02-01)

### Features

 * Add support for deepseek recipes

### Bug Fixes and Other Changes

 * mpirun protocol - distributed training with @remote decorator
 * Allow telemetry only in supported regions
 * Fix ssh host policy

## v2.238.0 (2025-01-29)

### Features

 * use jumpstart deployment config image as default optimization image

### Bug Fixes and Other Changes

 * chore: add new images for HF TGI
 * update image_uri_configs  01-29-2025 06:18:08 PST
 * skip TF tests for unsupported versions
 * Merge branch 'master-rba' into local_merge
 * Add missing attributes to local resourceconfig
 * update image_uri_configs  01-27-2025 06:18:13 PST
 * update image_uri_configs  01-24-2025 06:18:11 PST
 * add missing schema definition in docs
 * Omegaconf upgrade
 * SageMaker @remote function: Added multi-node functionality
 * remove option
 * fix typo
 * fix tests
 * Add an option for user to remove inputs and container artifacts when using local model trainer

## v2.237.3 (2025-01-09)

### Bug Fixes and Other Changes

 * pin metadata-version to 2.3
 * model server might have already done a serialization. honor that by not decoding the request again if it is not already bytes or bytestream
 * Disable jumpstart tests missing clean up logic
 * Jumpstart ap southeast 5
 * add autogluon 1.2
 * updated inference script to cover context
 * security update -> use sha256 instead of md5 for file hashing
 * Fix Flake8 Violations
 * Added parsing string support for situations where custom code might be used (ie. mlflow)
 * Updating Inference Optimization Validations

## v2.237.2 (2024-12-17)

### Bug Fixes and Other Changes

 * update image_uri_configs  12-13-2024 17:07:12 PST
 * Cloudpickle upgrade

## v2.237.1 (2024-12-12)

### Bug Fixes and Other Changes

 * chore: remove support for ecr spec fallbacks for jumpstart models
 * Cloudpickle Revert
 * Cloudpickle update
 * Numpy update
 * Protobuf update
 * Update to fetch latest Cloudpickle version

## v2.237.0 (2024-12-05)

### Features

 * Support SageMakerTrainingPlan for training jobs
 * AMI support for BRM
 * Adding Bedrock Store model support for HubService

### Bug Fixes and Other Changes

 * Fix unit tests
 * update boto3 and sagemaker-core version
 * fix gpu_image uri
 * Hotfix to construct rubik uri correctly
 * fix codestyles
 * fix merge artifact
 * fix merge artifact
 * fix test_requiremenets.txt
 * chore: Merge from main

## v2.236.0 (2024-12-04)

### Features

 * Partner App Auth Provider for SDK support
 * add pre-processing and post-processing logic to inference_spec
 * add utility function to capture local snapshot
 * support script mode with local train.sh

### Bug Fixes and Other Changes

 * Add graphene to doc requirements
 * Add graphne to the doc requirements
 * Enable the Recipe tests marked with @pytest.mark.skip(reason="Hyperpod recipe code unavailable"
 * Add model trainer documentation
 * Usage docs for training recipes
 * Neuron URIs update
 * Update URIs to public for training recipes
 * Changes for SMP v2.7.0
 * Change default source directory to current, add option to specify source dir
 * Remove default values for fields in recipe_overrides and fix recipe path.
 * Update MANIFEST.in so that wheel builds correctly
 * fix the file uploading signature verification error
 * remove example notebooks artifacts
 * Morpheus tests
 * Integ tests for local mode model trainer
 * Update hyperpod recipe uris
 * Add interface units for ModelTrainer
 * Model Trainer Bucket improvements
 * Update ModelTrainer Interface Parameters
 * add in-process mode definition to docs
 * Intelligent defaults for Model Trainer
 * Fix tests and codestyle
 * add integ test for base_model_builder_deploy and remove print statement
 * Revert image builder
 * pin xgboost dlc to 1.7.1 to fix test
 * Skip JS model mapping with env vars or image URI provided
 * Use sagemaker core Session
 * Integration tests for Model Builder Handshake
 * [Updated] Add telemetry to ModelTrainer, Estimator and ModelBuilder
 * Update kandinsky in ModelTrainer and allow setting requirements
 * add modelID support to model builder InProcess model
 * Add Rich Logging to Model Builder
 * Notebooks update for Bugbash
 * Add bugbash bootstrapping
 * add inference morpheus nbs
 * Update ModelTrainer Notebooks
 * Bug fixes
 * Single container local training
 * update notebooks
 * update notebooks
 * Add recipes examples
 * Unified Deployment interface in Model Builder
 * Use exact python path in trainer template
 * Support building image from Dockerfile
 * Add Support for Training Recipes
 * Trainer handshake
 * Pass hyperparameters as CLI args
 * Add in_process mode support for DJL and TorchServe servers
 * Remove ignored files
 * Simplify Config Class Names and DistributedRunner structures
 * Fix bug in script mode setup ModelTrainer
 * Mask Sensitive Env Logs in Container
 * Add path to set Additional Settings in ModelTrainer
 * Add Distributed Training Support Model Trainer
 * Cleanup ModelTrainer code
 * Latest Container Image
 * General image builder
 * Cleanup ModelTrainer
 * Revert Image Spec
 * Support intelligent parameters
 * Add enviornment variable bootstrapping script
 * Add example notebook
 * Add unit tests for ModelTrainer
 * Image Spec refactoring and updates
 * Base model trainer

## v2.235.2 (2024-11-22)

## v2.235.1 (2024-11-20)

### Bug Fixes and Other Changes

 * Update sagemaker-core dep
 * update image_uri_configs  11-20-2024 06:17:41 PST

## v2.235.0 (2024-11-19)

### Features

 * Optimize() validations across TRT, VLLM, Neuron container optimizations

### Bug Fixes and Other Changes

 * update image_uri_configs  11-19-2024 06:17:58 PST

## v2.234.0 (2024-11-19)

### Features

 * optimization technique related validations.

### Bug Fixes and Other Changes

 * Revert "change: add TGI 2.4.0 image uri (#4922)"
 * pin testing deps
 * add TGI 2.4.0 image uri
 * add jumpstart ap-southeast-5
 * Move sagemaker-mlflow to extras

## v2.233.0 (2024-11-04)

### Features

 * triton v24.09
 * Marketplace model support in HubService

### Bug Fixes and Other Changes

 * Fixing JumpStart Tests
 * bumping smp version from 2.6.0 to 2.6.1
 * Updates for DJL 0.30.0 release

## v2.232.3 (2024-10-30)

### Bug Fixes and Other Changes

 * update image_uri_configs  10-29-2024 07:17:56 PST
 * Skip pytorch tests incompatible with latest version 2.4.0
 * adding eu-central-2 bucket info to JS constants
 * update image_uri_configs  10-23-2024 11:26:03 PST
 * update image_uri_configs  10-17-2024 07:17:55 PST
 * update image_uri_configs  10-03-2024 07:17:59 PST
 * update image_uri_configs  09-27-2024 07:18:01 PST
 * modified pull request template
 * fixing typo in dependecy setup
 * release: huggingface tgi neuronx 0.0.25 image
 * Revert "update cloudpickle version to >=2.2.1 in pyproject.toml (#4899)"
 * update cloudpickle version to >=2.2.1 in pyproject.toml
 * update cloudpickle version to >=2.2.1
 * chore(deps): bump pyspark from 3.3.1 to 3.3.2 in /requirements/extras
 * changes for PT 2.4 currency upgrade
 * chore: add lmi image config in me-central-1
 * tests: Implement integration tests covering JumpStart PrivateHub workflows
 * Use Miniforge to replace MambaForge

## v2.232.2 (2024-10-03)

### Bug Fixes and Other Changes

 * Pass kwargs to HuggingFaceModel.deploy()
 * improve logging and exception messages
 * remove deprecated distutils
 * update image_uri_configs  09-24-2024 07:18:00 PST

## v2.232.1 (2024-09-19)

### Bug Fixes and Other Changes

 * update image_uri_configs  09-17-2024 07:17:54 PST
 * support latest container version in image_uris and DJLModel for lmi c…

## v2.232.0 (2024-09-12)

### Features

 * add deployment config name in modelbuilder telemetry
 * add Clarify image URIs for us-isof

### Bug Fixes and Other Changes

 * chore: add flaky test markers & skip region with low P3 instance capacity
 * update image_uri_configs  09-11-2024 11:54:11 PST
 * update image_uri_configs  09-10-2024 07:18:01 PST
 * [change] add us-gov and cn region repo accounts to djl and hugging face image metadata
 * update image_uri_configs  09-06-2024 07:17:55 PST
 * add us-gov region repo accounts to djl image metadata
 * pass name from modelbuilder constructor to created model

## v2.231.0 (2024-08-30)

### Features

 * Add SageMaker Core to the dependency

### Bug Fixes and Other Changes

 * Disable test_mnist_async
 * SMP v2.5
 * update image_uri_configs  08-29-2024 07:17:59 PST

## v2.230.0 (2024-08-28)

### Features

 * FastAPI integration for In_Process Mode (2/2)

### Bug Fixes and Other Changes

 * chore: add HF LLM neuronx 0.0.24 image
 * TF-2.16 test modification and handling
 * fix test fail
 * Add troubleshooting links to exceptions
 * cross account private hub model fine-tuning
 * chore: cleanup jumpstart factory
 * disable failing integration tests

## v2.229.0 (2024-08-15)

### Features

 * Support for ModelBuilder In_Process Mode (1/2)
 * Pulling in dependencies (in_process mode) using conda environment
 * Add optional CodeArtifact login to FrameworkProcessing job script
 * implemented security-monitoring to send metrics to CW #1510

### Bug Fixes and Other Changes

 * alt configs model deployment and training issues
 * fix keras extension in integ test
 * update image_uri_configs  08-13-2024 07:17:54 PST
 * trn1 instance family does not support volume size
 * Update model.py
 * removed log statement
 * update image_uri_configs  08-09-2024 07:18:00 PST
 * Added torchrun compatibility for distributet training across multiple GPUs in a single node (single instance)
 * BiasConfig type hint
 * add model monitor image accounts for ap-southeast-5 and eu-central-2
 * aligned UTC times with PST
 * ensure hpt jobs inherit tags from config
 * add JumpStart PDT and OSU regions
 * chore(deps): bump certifi in /src/sagemaker/serve/utils
 * Updates for DJL 0.29.0 release
 * chore(deps): bump apache-airflow from 2.9.2 to 2.9.3 in /requirements/extras
 * chore(deps): bump torch from 2.0.1 to 2.2.0 in /tests/data/serve_resources/mlflow/pytorch
 * avoided printing stack trace and escaped input
 * removing kwargs as this is breaking predictor_cls param for mode…

## v2.228.0 (2024-08-06)

### Features

 * triton v24.05

### Bug Fixes and Other Changes

 * chore: telemetry for deployment configs
 * censoring sensitive values from being logged
 * update image_uri_configs  08-05-2024 07:17:38 PST
 * enable uncompressed model artifacts upload to S3 for SAGEMAKER_ENDPOINT overwrite for TGI, TEI, MMS model servers
 * ModelReference deployment for Alt Configs models
 * Add optional typecheck for nullable parameters
 * Update package metadata
 * release TEI 1.4.0

## v2.227.0 (2024-07-30)

### Features

 * added code scanning through CodeQL

### Bug Fixes and Other Changes

 * Fixed cpu isntance type for the estimator register test
 * update image_uri_configs  07-29-2024 11:28:28 PST
 * avoid AccessDenied error for a while on SageMaker Studio wtih do…
 * SMP PT 2.3 Fix
 * chore: pin framework version in serverless inference tests
 * image uri in TGI 2.2.0 image
 * explicitly access enum member values to avoid Python version related regression
 * chore: add huggingface TGI 2.2.0 config
 * update image_uri_configs  07-22-2024 11:53:54 PST
 * update image_uri_configs  07-17-2024 07:17:38 PST
 * update image_uri_configs  07-16-2024 07:17:45 PST
 * add support for new regions

## v2.226.1 (2024-07-17)

## v2.226.0 (2024-07-12)

### Features

 * Curated hub improvements
 * InferenceSpec support for MMS and testing

### Bug Fixes and Other Changes

 * ModelBuilder not passing HF_TOKEN to model.
 * update image_uri_configs  07-10-2024 07:18:04 PST

## v2.225.0 (2024-07-10)

### Features

 * model optimization

### Bug Fixes and Other Changes

 * fix integ test
 * update uris for v1.1.1
 * update image_uri_configs  07-04-2024 07:17:24 PST

## v2.224.4 (2024-07-04)

### Bug Fixes and Other Changes

 * allow for inf spec and server override to be passed

## v2.224.3 (2024-07-03)

### Bug Fixes and Other Changes

 * Upgrade local dependencies
 * Improve docstrings for estimator tags

## v2.224.2 (2024-06-27)

### Bug Fixes and Other Changes

 * Update DJLModel class for latest container releases
 * list_models() for python3.8

## v2.224.1 (2024-06-21)

### Bug Fixes and Other Changes

 * JumpStart CuratedHub Launch
 * Update README.rst to show conda-forge version of SageMaker SDK
 * Update tox.ini
 * chore(deps): bump apache-airflow from 2.9.1 to 2.9.2 in /requirements/extras
 * Model server override logic

## v2.224.0 (2024-06-19)

### Features

 * JumpStartModel attach

### Bug Fixes and Other Changes

 * feat(sagemaker-mlflow): New features for SageMaker MLflow
 * Upgrading to PT 2.3 for release
 * chore: use ml.g5.2xlarge for integ test
 * Enable telemetry logging for Remote function
 * Fix Dependabot Issues - MLFlow Version

## v2.223.0 (2024-06-13)

### Features

 * add 'ModelCard' property to Register step

### Bug Fixes and Other Changes

 * Fix Sniping bug fix
 * Implement custom telemetry logging in SDK
 * Fix ci unit-tests
 * update image_uri_configs  06-12-2024 07:17:03 PST

## v2.222.1 (2024-06-12)

### Bug Fixes and Other Changes

 * First changes
 * estimator.deploy not respecting instance type

## v2.222.0 (2024-06-07)

### Features

 * jumpstart telemetry

### Bug Fixes and Other Changes

 * update image_uri_configs  06-06-2024 07:17:31 PST
 * bump requests from 2.31.0 to 2.32.2 in /requirements/extras
 * chore: add HF LLM neuronx 0.0.23 image
 * Updates for DJL 0.28.0 release
 * chore(deps): bump mlflow from 2.11.1 to 2.12.1 in /tests/data/serve_resources/mlflow/tensorflow
 * chore(deps): bump mlflow from 2.11.1 to 2.12.1 in /tests/data/serve_resources/mlflow/xgboost
 * chore(deps): bump mlflow from 2.10.2 to 2.12.1 in /tests/data/serve_resources/mlflow/pytorch
 * chore(deps): bump apache-airflow from 2.9.0 to 2.9.1 in /requirements/extras
 * chore(deps): bump requests from 2.31.0 to 2.32.2 in /tests/data/serve_resources/mlflow/pytorch
 * Fix ci unit-tests
 * Making project name in workflow files dynamic
 * update image_uri_configs  05-29-2024 07:17:35 PST
 * Update: SM Endpoint Routing Strategy Support.

## v2.221.1 (2024-05-22)

### Bug Fixes and Other Changes

 * Convert pytorchddp distribution to smdistributed distribution
 * Add tei cpu image

## v2.221.0 (2024-05-20)

### Features

 * onboard tei image config to pysdk

### Bug Fixes and Other Changes

 * JS Model with non-TGI/non-DJL deployment failure
 * cover tei with image_uris.retrieve API
 * Add more debuging
 * model builder limited container support for endpoint mode.
 * Image URI should take precedence for HF models

## v2.220.0 (2024-05-15)

### Features

 * AutoGluon 1.1.0 image_uris update
 * add new images for HF TGI release
 * Add telemetry support for mlflow models

### Bug Fixes and Other Changes

 * add debug logs to workflow container dist creation
 * model builder race condition on sagemaker session
 * Add tensorflow_serving support for mlflow models and enable lineage tracking for mlflow models
 * update image_uri_configs  05-09-2024 07:17:41 PST
 * skip flakey tests pending investigation

## v2.219.0 (2024-05-08)

### Features

 * allow choosing js payload by alias in private method

### Bug Fixes and Other Changes

 * chore(deps): bump jinja2 from 3.1.3 to 3.1.4 in /requirements/extras
 * chore(deps): bump tqdm from 4.66.2 to 4.66.3 in /tests/data/serve_resources/mlflow/pytorch
 * chore(deps): bump jinja2 from 3.1.3 to 3.1.4 in /doc
 * Updates for SMP v2.3.1

## v2.218.1 (2024-05-03)

### Bug Fixes and Other Changes

 * Fix UserAgent logging in Python SDK
 * chore: release tgi 2.0.1
 * chore: update skipped flaky tests

## v2.218.0 (2024-05-01)

### Features

 * set default allow_pickle param to False

### Bug Fixes and Other Changes

 * properly close files in lineage queries and tests

## v2.217.0 (2024-04-24)

### Features

 * support session tag chaining for training job

### Bug Fixes and Other Changes

 * Add Triton v24.03 URI
 * mainline alt config parsing
 * Fix tox installs
 * Add PT 2.2 Graviton Inference DLC

## v2.216.1 (2024-04-22)

### Bug Fixes and Other Changes

 * add DXB and CGK to Jumpstart regions
 * chore(deps): bump apache-airflow from 2.8.4 to 2.9.0 in /requirements/extras
 * bump djl-inference 0.27.0 neuronx sdk to 2.18.1
 * chore: release TGI 2.0.0

## v2.216.0 (2024-04-17)

### Features

 * optimum 0.0.21
 * Add TF 2.14 Graviton Inference support
 * JumpStart alternative config parsing
 * TGI 1.4.5

### Bug Fixes and Other Changes

 * chore(deps): bump black from 22.3.0 to 24.3.0 in /requirements/extras
 * Add back serialization for automatic speech recognition
 * bump apache-airflow version to 2.8.4
 * remove trailing slash when uploading to S3 with dataset_builder.to_csv_file
 * Update Collaborator Check workflow to check for users which are part of collaborator team
 * forward network_isolation parameter to Estimators when False
 * Flaky slow test
 * Revert "Test SM PySDK Variations"

### Documentation Changes

 * Add supported task types to schema builder omission

## v2.215.0 (2024-04-12)

### Features

 * JumpStart Gated Model Support in ModelBuilder Local Modes
 * Changes to support remote schema retrieval for task types (question-answering, fill-mask) and added e2e tests for both local and remote hf schema logic.
 * Upgrade smp to version 2.3.0

### Bug Fixes and Other Changes

 * disable modelbuilder mlflow local integ tests
 * add integ-tests to codebuild-ci.yml
 * [Feat] Support MLflow Model Format Through ModelBuilder
 * Test SM PySDK Variations
 * typo in jumpstart manifest and refine tests
 * add kix to launched regions
 * Remove space specific business logic from Python SDK function to fetch execution role
 * Remove notebook tests from CI health check and the script

## v2.214.3 (2024-04-04)

### Bug Fixes and Other Changes

 * [Fix] Switch to subprocess in ModelBuilder when capturing dependencies
 * chore: skip flaky test

## v2.214.2 (2024-04-01)

### Bug Fixes and Other Changes

 * Skip JS Tune integration test
 * bump apache-airflow version to 2.8.3
 * bump onnx version to >=1.15.0
 * Updates for DJL 0.27.0 release
 * Tune (local mode) support for Jumpstart Models
 * attach jumpstart estimator for gated model

## v2.214.1 (2024-03-27)

### Bug Fixes and Other Changes

 * Update schema dependency version
 * remove failing deprecated tests from suite
 * update readme, trigger p311 tests
 * JumpStart list models flaky tests
 * fix badge in README

## v2.214.0 (2024-03-22)

### Features

 * add support to ``clarify.py`` for time series explainability jobs

### Bug Fixes and Other Changes

 * remove pytorch test for deprecated function
 * skip test_experiment_analytics to unblock release
 * Create workflow module scoped sagemaker_session to resolve test race condition
 * Simplify how we process test dependencies, which are supposed to include all extras.
 * skip failing feature store search integ test
 * skip failing pt test
 * list jumpstart models with invalid version strings
 * urge customers to install latest version

## v2.213.0 (2024-03-15)

### Features

 * Add support for Streaming Inference
 * tgi optimum 0.0.19, 0.0.20 releases
 * support JumpStart proprietary models
 * Add ModelDataSource and SourceUri support for model package and while registering
 * Accept user-defined env variables for the entry-point
 * Add overriding logic in ModelBuilder when task is provided

### Bug Fixes and Other Changes

 * Improvement of the tuner documentation
 * Skip of tests which are long running and causing the ResourceLimitInUse exception
 * Add AutoML -> AutoMLV2 mapper
 * add ci-health checks
 * split coverage out from testenv in tox.ini
 * add PT 2.2 support for smdistributed, pytorchddp, and torch_distributed distributions
 * sagemaker session region not being used
 * chore: emit warning when no instance specific gated training env var is available, and raise exception when accept_eula flag is not supplied
 * enable github actions for PRs
 * Move sagemaker pysdk version check after bootstrap in remote job
 * make unit tests compatible with pytest-xdist
 * Update tblib constraint

## v2.212.0 (2024-03-06)

### Features

 * Update SM Python SDK for PT 2.2.0 SM DLC

### Bug Fixes and Other Changes

 * Create custom tarfile extractall util to fix backward compatibility issue
 * Upgrade smp to version 2.2
 * Enhance model builder selection logic to include model size

## v2.211.0 (2024-03-05)

### Features

 * pin dll version to support python3.11 to the sdk
 * instance specific jumpstart host requirements
 * Add TensorFlow 2.14 image configs
 * Add AutoMLV2 support
 * Support selective pipeline execution between function step and regular step
 * Add new Triton DLC URIs

### Bug Fixes and Other Changes

 * Skip No Canvas regions for test_deploy_best_candidate
 * make sure gpus are found in local_gpu run
 * Bump Apache Airflow version to 2.8.2
 * properly close sagemaker config file after loading config
 * remove enable_network_isolation from the python doc

### Documentation Changes

 * Add doc for new feature processor APIs and classes

## v2.210.0 (2024-02-28)

### Features

 * Prepend SageMaker Studio App Type to boto3 User Agent string
 * TGI optimum 0.0.18 (general+llm)
 * TGI 1.4.2

### Bug Fixes and Other Changes

 * tolerate vulnerable old model for integ test and temporarily skip test_list_jumpstart_models_script_filter
 * add missing regions to pytorch config
 * Add validation for sagemaker version on remote job
 * fixed implementation of fail_on_violation for transform with monitoring

## v2.209.0 (2024-02-24)

### Features

 * ModelBuilder to fetch local schema when no SchemaBuilder present.
 * AutoGluon 1.0.0 image_uris update

### Bug Fixes and Other Changes

 * skip pytorch training compiler integ test
 * add fixes for tarfile extractall functionality PEP-721
 * Fix telemetry image uri option logic for ModelBuilder
 * Add telemetry metrics on usage of default images for ModelBuilder
 * Fix error message typo
 * Add "distribution" parameter into record_set

## v2.208.0 (2024-02-15)

### Features

 * Telemetry metrics
 * TGI 1.4.0
 * Support collection type and target store for feature store ingestion.

### Bug Fixes and Other Changes

 * bump jinja2 to 3.1.3 in doc/requirments.txt
 * chore(deps): bump jinja2 from 3.0.3 to 3.1.3 in /requirements/extras
 * Fix dependabot alert in transformers package
 * Bump Apache Airflow version to 2.8.0
 * skip failing mxnet tests

### Documentation Changes

 * change order of pipelines topics
 * Explain the ClarifyCheckStep and QualityCheckStep parameters
 * fix the ClarifyCheckStep documentation to mention PDP

## v2.207.1 (2024-02-06)

### Bug Fixes and Other Changes

 * Add PT 2.1 as a supported framework for the smdistributed distribution
 * Enable private docker registry support for ModelBuilder
 * HF PT 2.1 Image Configs

### Documentation Changes

 * add setup commands for documentation generation

## v2.207.0 (2024-02-05)

### Features

 * Introduce HF Transformers to ModelBuilder
 * retrieve jumpstart estimator and predictor without specifying model id (infer from tags)

### Bug Fixes and Other Changes

 * SMP PT upgrade to 2.1
 * Fetch HF metadata only when explicit type is not selected
 * relax upper bound for urllib dependency

## v2.206.0 (2024-01-31)

### Features

 * Logic to detect hardware GPU count and aggregate GPU memory size in MiB

### Bug Fixes and Other Changes

 * fixed create monitoring schedule failing after validation error
 * Support PipelineVariable for ModelQualityCheckConfig attributes
 * TGI NeuronX 0.0.17

## v2.205.0 (2024-01-25)

### Features

 * Support selective pipeline execution for function step

### Bug Fixes and Other Changes

 * remove fastapi and uvicorn dependencies
 * Support using PipelineDefinitionConfig in local mode
 * update get_execution_role_arn from metadata file if present
 * update image_uri_configs  01-24-2024 06:17:33 PST
 * Add validation for empty ParameterString value in start local pipeline

## v2.204.0 (2024-01-23)

### Features

 * add throughput management support for feature group
 * Support custom repack model settings
 * parallelize notebook search utils, add new operators

### Bug Fixes and Other Changes

 * Enable galactus integ tests
 * JumpStart - TLV region launch
 * add warning message for job-prefixed pipeline steps when no job name is provided
 * TGI NeuronX
 * Updates for DJL 0.26.0 release
 * update sphinx version
 * Add PyTorch 2.1.0 SM Training DLC to UNSUPPORTED_DLC_IMAGE_FOR_SM_PARALLELISM list
 * Huggingface glue failing tests
 * change ConditionNot incorrect property Expression to Condition

## v2.203.1 (2024-01-09)

### Bug Fixes and Other Changes

 * TGI 1.3.3
 * skip failing integs
 * query hf api for model md
 * update image_uri_configs  12-29-2023 06:17:34 PST

## v2.203.0 (2023-12-28)

### Features

 * support local mode in SageMaker Studio (#1300)
 * Supporting tbac in load_run

### Bug Fixes and Other Changes

 * update image_uri_configs  12-25-2023 06:17:33 PST
 * Disable failed test in IR
 * Raise Exception for debug
 * create role if needed in `get_execution_role`

## v2.202.1 (2023-12-22)

### Bug Fixes and Other Changes

 * update image_uri_configs  12-22-2023 06:17:35 PST
 * update model path in local mode
 * Using logging instead of prints

### Documentation Changes

 * update issue template.

## v2.202.0 (2023-12-21)

### Features

 * support remote debug for sagemaker training job

### Bug Fixes and Other Changes

 * update image_uri_configs  12-21-2023 08:32:41 PST
 * Update tblib constraint

## v2.201.0 (2023-12-20)

### Features

 * Use specific images for SMP v2 jobs
 * Added update for model package

### Bug Fixes and Other Changes

 * Add write permission to job output dirs for remote and step decorator running on non-root job user
 * Move func and args serialization of function step to step level

### Documentation Changes

 * SMP v2 doc updates (#1423)
 * fix ModelBuilder sample notebook links

## v2.200.1 (2023-12-14)

### Bug Fixes and Other Changes

 * Merge branch 'master-rba' into local_merge
 * Fix user agent tag issue
 * update image_uri_configs  12-13-2023 14:04:54 PST
 * update image_uri_configs  12-13-2023 12:23:06 PST

## v2.200.0 (2023-12-13)

### Deprecations and Removals

 * remove explicit `partitions` key requirement on pysdk side.

### Features

 * add non-repeating config logger
 * Add SageMaker Geospatial verison 1.x images
 * TGI 1.2.0 Image Uri
 * support model.register() with triton model
 * Enable retrieving function step results for local mode

### Bug Fixes and Other Changes

 * TGI 1.3.1
 * excessive jumpstart instance type logging
 * Support local mode for remote function
 * `Session.download_data` can not download nested objects
 * Fix writing into non-closed file with git clone command
 * mitigation of xgboost container incompatibility with new version
 * update image and hardware validation with inf and graviton
 * remove two setuptools deprecations
 * minor jumpstart dev ex improvements
 * save utils fix
 * Correct DJL neuronx regions
 * delete unused file inference-experience-dev-tester.sh
 * Fix Experiment Run integ test w.r.t unexpected boto3 version
 * Bump test dependencies versions
 * fast follow on js uncompressed support - ModelBuilder
 * Modify Region List for Neuron Images (HF neuron/neuronx, PT Neuron)

### Documentation Changes

 * Mention for custom Docker Image

## v2.199.0 (2023-11-30)

### Features

 * Update boto3 version to 1.33.3
 * Goldfinch InferenceComponent integration
 * Add Pipeline step decorator, NotebookJobStep, and scheduler
 * ModelBuilder for simplified model testing and deployment

### Bug Fixes and Other Changes

 * Skip failing integ tests
 * chore: add jumpstart gated model integration tests
 * disable integration tests for Inference Component based endpoint for non supported regions
 * remove unnecessary whl file - Galactus
 * refactor endpoint type enums, comments, docstrings, method names…
 * Address SA feedback regarding deployment straight to Endpoint Mode - Galactus
 * fix HuggingFace GEN2 model deployment arguments
 * when customer role does not have permission to read logs from CW, default to standard logging - Galactus
 * Add pagination for ListInferenceComponent API responses, address non-blocking comments
 * Create CSVSerializerWrapper - Galactus
 * Model builder Final Fixes
 * remote function include_local_workdir default value
 * use copy instead of move in bootstrap script
 * WaiterError on failed pipeline execution. results()
 * Add a unit test for consistency between step and remote decorator
 * merge WorkdirConfig and custom_filter_filter parameters
 * Add back mixed step type integ test
 * do not delete temp folder generated by sdist
 * make collect_parameters decorator as private
 * HMAC signing for ModelBuilder Triton python backend

### Documentation Changes

 * update docstring for Generation two endpoint and validation message
 * galactus doc updates
 * CustomFileFilter doc updates
 * NotebookJobSteps class parameter severity update

## v2.198.0 (2023-11-27)

### Features

 * re:Invent 2023 keynote1

## v2.197.0 (2023-11-07)

### Features

 * PT2.1 SM Training/Inference DLC Release

### Bug Fixes and Other Changes

 * Release HuggingFace PT Neuronx training image 1.13.1
 * HuggingFace PT Neuronx release in SDK

## v2.196.0 (2023-10-27)

### Features

 * inference instance type conditioned on training instance type

### Bug Fixes and Other Changes

 * improved jumpstart tagging

## v2.195.1 (2023-10-26)

### Bug Fixes and Other Changes

 * Allow either instance_type or instance_group to be defined in…
 * enhance image_uris unit tests

## v2.195.0 (2023-10-25)

### Features

 * jumpstart gated model artifacts
 * jumpstart extract generated text from response
 * jumpstart contruct payload utility

### Bug Fixes and Other Changes

 * relax upper bound on urllib in local mode requirements
 * bump urllib3 version
 * allow smdistributed to be enabled with torch_distributed.
 * fix URL links

### Documentation Changes

 * remove python 2 reference
 * update framework version links

## v2.194.0 (2023-10-19)

### Features

 * Added register step in Jumpstart model
 * jumpstart instance specific metric definitions

### Bug Fixes and Other Changes

 * Updates for DJL 0.24.0 Release
 * use getter for resource-metadata dict
 * add method to Model class to check if repack is needed

## v2.193.0 (2023-10-18)

### Features

 * jumpstart model artifact instance type variants
 * jumpstart instance specific hyperparameters
 * Feature Processor event based triggers (#1132)
 * Support job checkpoint in remote function
 * jumpstart model package arn instance type variants

### Bug Fixes and Other Changes

 * Fix hyperlinks in feature_processor.scheduler parameter descriptions
 * add image_uris_unit_test pytest mark
 * bump apache-airflow to `v2.7.2`
 * clone distribution in validate_distribution
 * fix flaky Inference Recommender integration tests

### Documentation Changes

 * Update PipelineModel.register documentation
 * specify that input_shape in no longer required for torch 2.0 mod…

## v2.192.1 (2023-10-13)

### Bug Fixes and Other Changes

 * update local mode schema
 * import error in unsupported js regions
 * Update Ec2 instance type to g5.4xlarge in test_huggingface_torch_distributed.py

## v2.192.0 (2023-10-11)

### Features

 * jumpstart estimator enable infra check flag
 * jumpstart default payloads
 * allow non-python files in job dependencies
 * allow configuring docker container in local mode

### Bug Fixes and Other Changes

 * js tagging s3 prefix
 * Batch transform: Add support for split_type == "None" in local mode
 * use correct line endings and s3 uris on windows
 * Fixed bug in _create_training_details
 * DJL Neuronx 0.24.0

### Documentation Changes

 * Include FeatureGroup's load_feature_definitions API documentation

## v2.191.0 (2023-10-05)

### Features

 * Selective Step Execution milestone 2 features
 * feature-processor extra data sources support

## v2.190.0 (2023-10-04)

### Features

 * Add support for in-memory feature groups and collection type features in Feature Store.

### Bug Fixes and Other Changes

 * chore: xfail resource in use failure for specific test
 * Add missing API docs for processors

### Documentation Changes

 * Bring back (de)serializers documentation
 * Add missing AirFlow operators + link to airflow documentation

## v2.189.0 (2023-10-03)

### Features

 * add feature processor APIs to public doc
 * s3 prefix model data for JumpStartModel
 * Model Package support for updating approval

### Bug Fixes and Other Changes

 * Add bucket owner check
 * transform step  unit test
 * Release TGI 1.1.0 Image

## v2.188.0 (2023-09-26)

### Features

 * jumpstart instance type variants
 * New methods to ingest and create Feature Groups

### Bug Fixes and Other Changes

 * auto ml integ tests and add flaky test markers
 * Enhance unit-tests to automatically consume image URIs config registries from config JSONs

## v2.187.0 (2023-09-19)

### Features

 * add HealthCheckConfig support
 * SkipModelValidation in modelRegistry

### Bug Fixes and Other Changes

 * Update fw_utils.py - support 2.0.1 container for DDP and Torch distri…
 * bump apache-airflow to v2.7.1

## v2.186.0 (2023-09-14)

### Features

 * TGI 1.0.3 Image URI Config

## v2.185.0 (2023-09-12)

### Features

 * Local Mode - Add Support for Docker Compose V2

### Bug Fixes and Other Changes

 * handle bad jumpstart default session
 * Add Data Wrangler TLV and version 3.x images

## v2.184.0.post0 (2023-09-11)

### Documentation Changes

 * add interactive apps rst file

## v2.184.0 (2023-09-07)

### Features

 * Enable notebook instances to get presigned url

### Bug Fixes and Other Changes

 * update scikit-learn, scipy, and apache-airflow deps for dependabot
 * log message when sdk defaults not applied

## v2.183.0 (2023-09-05)

### Deprecations and Removals

 * remove support for py37

### Features

 * Neo service GA in TLV

### Bug Fixes and Other Changes

 * Update pytorch.json with 2.0.1 for inference and training
 * get python version dynamically for remote function tests
 * HuggingFaceProcessor parameterized instance_type when image_uri is absent

## v2.182.0 (2023-08-29)

### Features

 * image url for modelmonitor in TLV region
 * Enable spot training on remote decorator and executor

## v2.181.0 (2023-08-28)

### Features

 * StabilityAI DLC Image URIs

### Bug Fixes and Other Changes

 * temporarily skip kmeans notebook

## v2.180.0 (2023-08-24)

### Features

 * Add presigned URLs for interactive apps
 * Add detail profiler V2 options and tests

## v2.179.0 (2023-08-21)

### Features

 * attach method for jumpstart estimator

### Bug Fixes and Other Changes

 * pipeline upsert failed to pass parallelism_config to update

## v2.178.0 (2023-08-17)

### Features

 * Support to get latest monitoring execution processing logs

### Bug Fixes and Other Changes

 * Add context to predict_fn example
 * gated models unsupported region
 * jumpstart cache using sagemaker session s3 client
 * add TFS 2.13 Graviton SM images
 * pipeline variable kms key
 * integration test for gated jumpstart training model
 * tags for jumpstart model package models

## v2.177.1 (2023-08-14)

### Bug Fixes and Other Changes

 * chore: excessive jumpstart bucket logging

## v2.177.0 (2023-08-11)

### Features

 * Add TLV accounts for 1P Algorithms

## v2.176.0 (2023-08-10)

### Features

 * Add TF 2.13 Training and Inference SM images

### Bug Fixes and Other Changes

 * revert-PR_3903
 * skip tensorflow local mode notebook test
 * change instance type for huggingface test to ml.g5.8xlarge

## v2.175.0 (2023-08-05)

### Features

 * Add huggingface-llm 0.9.3 dlc images

### Bug Fixes and Other Changes

 * Upgrade default version for djl to v0.23.0
 * Pass kms_key to _upload_analysis_config when provided

## v2.174.0 (2023-08-02)

### Features

 * meta llama fine tuning
 * support online store ttl for records
 * Deploy uncompressed ML model from S3 to SageMaker Hosting endpoints
 * AutoGluon 0.8.2 image_uris update

### Bug Fixes and Other Changes

 * [Feature] Propagate tags to lineage resources
 * excessive jumpstart logging
 * chore: jumpstart deprecation messages
 * build(deps): bump pygments from 2.11.2 to 2.15.0 in /requirements/tox
 * Remove deleted notebook tests from test confg
 * chore: add jumpstart llama 2 tests

### Documentation Changes

 * add smp class for supporting flash attn

## v2.173.0 (2023-07-15)

### Features

 * jumpstart EULA models

### Bug Fixes and Other Changes

 * Update the apache airflow constraints
 * Update apache airflow version
 * bump up djl inference image uri versions

## v2.172.0 (2023-07-13)

### Features

 * Add check for if TrialComponent is already associated with a Trial in Run
 * Add features_to_explain to shap config

### Bug Fixes and Other Changes

 * Support protobuf4
 * Remove unnecessary get caller identity call
 * Missing JumpStart estimator args
 * Add volume to partition djl_inference

### Documentation Changes

 * Correct runtime param
 * fix wait_for_endpoint docstring

## v2.171.0 (2023-07-06)

### Features

 * Add PipelineDefinitionConfig to pipelines to toggle custom job …

### Bug Fixes and Other Changes

 * Upgrade DJL deepspeed versions
 * Remove unused dependency `protobuf3-to-dict`
 * skip intelligent volume_size allocation based on instance type if it is a pipeline parameter

## v2.170.0 (2023-07-05)

### Features

 * Enable customizing artifact output path

### Bug Fixes and Other Changes

 * Add il-central-1 support for all SM DLCs
 * jumpstart async inference config predictor support
 * Update CreateEdgePackagingJob resourceKey with type string

## v2.169.0 (2023-06-29)

### Features

 * Add support for tags in to_pipeline API for feature processor
 * model registry integration to model cards to support model packages
 * SDK Defaults - DebugHookConfig defaults in TrainingJob API
 * Add segment config for Clarify

### Bug Fixes and Other Changes

 * Neuronx image retrieval missing sdk information

### Documentation Changes

 * Doc updates for SDK defaults - S3 Params, Env Variables, Disable Profiler, and DebugHookConfig

## v2.168.0 (2023-06-22)

### Features

 * Support uncompressed model upload
 * Add optional monitoring_config_override parameter in suggest_baseline API
 * SDK defaults add disable profiler to createTrainingJob

### Bug Fixes and Other Changes

 * Enable spark processing container in KIX
 * Fix key prefix preventing jumpstart model repack

## v2.167.0 (2023-06-21)

### Features

 * add SageMaker FeatureStore feature processing

### Bug Fixes and Other Changes

 * Chore/reset cache if js model not found

## v2.166.0 (2023-06-19)

### Features

 * Add `inf2` support to `HuggingFaceModel`
 * adding resourcekey and tags for api in config for SDK defaults

### Bug Fixes and Other Changes

 * Remove deprecated option.s3url in favor of option.model_id
 * Use sagemaker config keyword
 * SDK Defaults Config - Handle config injection for None Sessions
 * Fix HPO Grid Search comparison and name

## v2.165.0 (2023-06-13)

### Features

 * Add support for Deployment Recommendation ID in model.deploy(). No tagging support

### Bug Fixes and Other Changes

 * maketplace integs
 * Add tagging assert to inference recommender integ tests
 * breaking deviations in _create_sagemaker_model call

### Documentation Changes

 * Add missing quotation mark

## v2.164.0 (2023-06-08)

### Features

 * SDK Defaults - Environment Variables
 * Update Transformers 4.28 - PyTorch 2.0.0 Training and Inference Image URI

### Bug Fixes and Other Changes

 * tag more integs as flaky for auto-retry
 * Remove docker-compose from local requirements
 * enable neo framework version support on ml_inf2 and ml_trn1

## v2.163.0 (2023-06-07)

### Features

 * Add huggingface-llm 0.8.2 dlc images

### Bug Fixes and Other Changes

 * Update to more actionable error message
 * Loosen local reqs for PyYAML

## v2.162.0 (2023-06-06)

### Features

 * Add tagging support for create ir job
 * Selective Step Execution feature in Pipelines
 * Add Neuronx Image uri - Transformers 4.28 - PyTorch 1.13

### Bug Fixes and Other Changes

 * skip pipelines abalone notebook test
 * Update neo multiversion support to include edge devices

### Documentation Changes

 * JumpStart Utility Doc Update

## v2.161.0 (2023-06-01)

### Features

 * Add huggingface-llm 0.6.0 dlc images
 * Add autotune for HyperparameterTuner

### Bug Fixes and Other Changes

 * Remove release tag from non-global test
 * SDK defaults for volume size, JS Estimator image uri region, Predictor str method

## v2.160.0 (2023-05-31)

### Features

 * PyTorch 2.0 release
 * Add TFS 2.12.1 Graviton image

### Bug Fixes and Other Changes

 * Fix failing integ test
 * remove unnecessary log messages for loading existing experiment runs
 * build(deps): bump requests from 2.27.1 to 2.31.0 in /requirements/extras
 * SDK Defaults - switch from config printing to logging

## v2.159.0 (2023-05-23)

### Features

 * Add TF Serving 2.12.1 images to the SM PySDK

### Bug Fixes and Other Changes

 * Update the list of extension packages pylint is allowed to load

## v2.158.0 (2023-05-22)

### Features

 * Enable default role for Spark processors
 * SDK Defaults - S3 Params for Session
 * Bump up images for DJL transformers Neuronx DLCs

### Bug Fixes and Other Changes

 * Relax local-mode PyPI requirements on urllib3

### Documentation Changes

 * Fix Tensorflow and PyTorch supported version in HuggingFaceProcessor
 * Update doc for model_server_workers param in PyTorchModel

## v2.157.0 (2023-05-18)

### Features

 * Handle use case where endpoint is created outside of python …

### Bug Fixes and Other Changes

 * Make type annotation of UploadedCode consistent
 * Add SELinux label to local docker volumes

## v2.156.0 (2023-05-17)

### Features

 * Partition support for DJLModel using SM Training job
 * Update run-notebook-test to consider skips failures

### Bug Fixes and Other Changes

 * Update apache airflow and update test requirements
 * Perform integrity checks for remote function execution
 * Add p2 instances to integ tests
 * Fix typo in logging message within ir mixin
 * double Run create on load_run
 * Update dtype logic for huggingface backend for new containers

### Documentation Changes

 * Update container version for SKLearn
 * Add description for parameters in TransformInput

## v2.155.0 (2023-05-15)

### Features

 * Add support for SageMaker Serverless inference Provisioned Concurrency feature

### Bug Fixes and Other Changes

 * Revert "fix: make RemoteExecutor context manager non-blocking on pend…
 * Add BOM to no No P2 Availability region list

## v2.154.0 (2023-05-11)

### Features

 * Add integ tests for remote_function, auto_capture functionality
 * jumpstart model estimator classes

### Bug Fixes and Other Changes

 * integs - pytorch transformer deps and add test retry
 * adding .lower() so new Pandas dtypes will match the type lookup.
 * Pass KMS value to create processing job

## v2.153.0 (2023-05-09)

### Features

 * Support npz archives in NumpyDeserializer
 * Add FasterTransformer DJL support
 * support for Sample Weights for SageMaker Autopilot

### Bug Fixes and Other Changes

 * retry is_run assertion
 * Avoid 'AttributeError' for endpoint_name, if deploy() is not yet called
 * Fix LambdaStep Creation
 * Fix error when instance_count>1 in remote_function
 * Remove deprecated update_endpoint from deploy() args in TensorFlowModel
 * Update DJL deepspeed and fastertransformer DLC image uris
 * remote_function python version mismatch issue

## v2.152.0 (2023-05-04)

### Features

 * add support for lineage visualization using pyvis
 * Expose Experiment class publicly
 * PyTorch 1.13 release

### Bug Fixes and Other Changes

 * Change data_type argument to dtype to keep consistent with D…
 * Skip edge test
 * make RemoteExecutor context manager non-blocking on pending futures
 * Add inferentia2 DLC images for djl framework
 * Fix typo in using_pytorch.rst
 * Unable to attach estimator to training job when KeepAlivePeriodInSeconds specified
 * update LMI container image
 * Update Clarify SHAPConfig baseline to allow JSON structures

### Documentation Changes

 * Fix broken link in DJL SageMaker docs
 * currency update for the SageMaker data parallelism lib
 * SM model parallel library v1.15.0 release note

## v2.151.0 (2023-04-27)

### Features

 * Update Transformers 4.26 - TensorFlow 2.11.0 Image URI
 * Add Extra Parameters to Lambda Function Wrapper

### Bug Fixes and Other Changes

 * Add kms key support for Model registration
 * Enable inference recommender slow tests
 * Pass sagemaker session to downstream s3 calls
 * Add ap-south-1 to no p3 regions
 * skip test for p2 instance for TF2.12 and above

### Documentation Changes

 * Fix minor misses from the remote function doc release

## v2.150.0 (2023-04-26)

### Features

 * Introduce TensorBoard app class

### Bug Fixes and Other Changes

 * Update data wrangler images

## v2.149.0 (2023-04-25)

### Features

 * Support TF2.12 SageMaker DLC

### Bug Fixes and Other Changes

 * update the doc for Join function
 * change s3UploadMode of sagemaker clarify processing output for computer vision jobs.

### Documentation Changes

 * Add Remote Function updates

## v2.148.0 (2023-04-20)

### Features

 * [huggingface] Add `torch.distributed` support for Trainium and `torchrun`
 * Add PyTorch 2.0 to SDK

### Bug Fixes and Other Changes

 * updating batch transform job in monitoring schedule

## v2.147.0 (2023-04-18)

### Features

 * support different types of deletion mode

## v2.146.1 (2023-04-17)

### Bug Fixes and Other Changes

 * skip failing tests temporarily
 * Added ml.p4d and ml.p4de as supported instances for DeepSpeed

### Documentation Changes

 * Add Model Registry Model Collection

## v2.146.0 (2023-04-13)

### Features

 * Add support for JSON model inputs for Clarify Processor

### Bug Fixes and Other Changes

 * Feature/list collection
 * improve reliability of Run integration test
 * Add a comment that smdataparallel lib excludes tf 2.12 support

### Documentation Changes

 * Update reference to load run method in documentation

## v2.145.0 (2023-04-06)

### Features

 * add support for async inline error notifications
 * Add methods for feature group to list feature metadata parameters and tags
 * Support huggingface hub model_id for DJL Models

### Bug Fixes and Other Changes

 * load_sagemaker_config should lazy initialize a default S3 resource

## v2.144.0 (2023-04-05)

### Features

 * support create Clarify explainer enabled endpoint for Clarify Online Explainability
 * Combined inference and training script artifact
 * jumpstart instance types
 * Deprecation warning for framework profiling for TF 2.12 and on, PT 2.0 and on

### Bug Fixes and Other Changes

 * always delete temporary directory even during exception
 * Fixes the completion_criteria_config dict in the to_input_req method
 * Update CHANGELOG.md

### Documentation Changes

 * Update SageMaker Debugger doc

## v2.143.0 (2023-03-29)

### Features

 * Support for SageMaker SDK Defaults

### Bug Fixes and Other Changes

 * update feature store offline s3 path used in tests

## v2.142.0 (2023-03-27)

### Features

 * combined model + script artifact

## v2.141.0 (2023-03-24)

### Features

 * AutoGluon 0.7.0 image_uris update
 * Add DJL FasterTransformer image uris
 * EMR step runtime role support
 * locations for EMR configuration and Spark dependencies
 * Adding support for 1P Algorithms in ZAZ, ZRH, HYD, MEL

### Documentation Changes

 * Update FeatureGroup kms key id documentation

## v2.140.1 (2023-03-21)

### Bug Fixes and Other Changes

 * Fix cross account register model
 * Handle instance support for Hugging Face tests
 * Upgrade apache-airflow-providers-amazon version
 * build(deps): bump apache-airflow from 2.4.1 to 2.5.1
 * Mark test_create_model_package test for xfail
 * Disable module-not-measured warnings to avoid clutter in build logs

## v2.140.0 (2023-03-17)

### Features

 * SDK changes for TRCOMP support

### Bug Fixes and Other Changes

 * [Feature - Hugging Face] Update Transformers 4.26 - PyTorch 1.13.1 Image uri

## v2.139.0 (2023-03-15)

### Features

 * Add XGBoost framework 1.7-1 version

### Bug Fixes and Other Changes

 * Fix image_uris.retrieve() function to return ValueError when framework is not allowed for an instance_type

## v2.138.0 (2023-03-13)

### Features

 * Jumpstart training metrics

### Bug Fixes and Other Changes

 * Add new region support for MX, PT, TF on SM Training

## v2.137.0 (2023-03-10)

### Features

 * support JSON for input dataset and model output

### Bug Fixes and Other Changes

 * Wait on describe for tag propagation
 * Extracted profile_name directly from sagemaker.Session if None
 * Avoid double encoding to JSON in InferenceRecommenderMixin
 * RepackStep must use the same KMS key as the Model

## v2.136.0 (2023-03-09)

### Features

 * with_feature_group [feature_store]
 * Djl Large Model Support
 * Decouple model.right_size() from model registry

### Bug Fixes and Other Changes

 * Fix integration test error in test_default_right_size_and_deploy_unregistered_base_model
 * Add djl 0.21.0 dlc images

### Documentation Changes

 * Torchrun gpu support documentation change

## v2.135.1.post0 (2023-03-02)

### Documentation Changes

 * update feature store dataset builder docs

## v2.135.1 (2023-03-01)

### Bug Fixes and Other Changes

 * Revert back to stable apache-airflow-providers-amazon from 7.2.1 to 4.0.0.
 * Typo in graviton algos
 * build(deps): bump apache-airflow-providers-amazon from 4.0.0 to 7.2.1 in /requirements/extras
 * Support cloning private repo using ssh key
 * Create a default SageMaker Session inside FeatureGroup class

### Documentation Changes

 * fix typo in README

## v2.135.0 (2023-02-23)

### Features

 * Add DLC accounts for MEL Region
 * allow use of short lived creds for local container

### Bug Fixes and Other Changes

 * update lambda function when function arn is provided

## v2.134.1 (2023-02-22)

### Bug Fixes and Other Changes

 * local mode deletion of temp files on job end
 * Cron expression resetting on update monitor
 * added support to update arguments in create_monitoring_schedule

## v2.134.0 (2023-02-22)

### Features

 * Add python 3.9 and spark 3.2 support for spark processor
 * Adding support for Multi Worker Mirrored Strategy in TF estimator

### Bug Fixes and Other Changes

 * tag permission issue - remove describe before create

## v2.133.0 (2023-02-18)

### Features

 * feature store with_feature_group functionality changes
 * Adding support for SageMaker Training Compiler PyTorch 1.13
 * support of the intelligent stopping in the tuner
 * AutoGluon 0.6.2 image_uris update
 * Support for flexible instance types in the HPO
 * Add business details and hyper parameters fields and update test_model_card.py

### Bug Fixes and Other Changes

 * disable the tuner test
 * Skip test_run_from_transform_job integ test to unblock python-sdk code pipeline
 * Revert "feature: feature store with_feature_group functionality changes"
 * advanced inference recommendation jobs parameters check
 * make model_config optional when predicted labels are provided for bias detection

## v2.132.0 (2023-02-07)

### Features

 * support cluster lifecycle management for Sagemaker EMR step
 * Inference recommendation id deployment support

## v2.131.1 (2023-02-03)

### Bug Fixes and Other Changes

 * test dub gpu integs with p3
 * fix(experiments/run.py): Stop duplication of RUN_TC_TAG on Consecutive Experiment Runs
 * Enable load_run without name args in Transform env
 * Remove confusing log line emitted during feature group ingestion
 * Enable Experiment integ test on beta clients
 * Make test_processor_with_role_as_pipeline_parameter more concrete

### Documentation Changes

 * add security note for the estimator hyperparameter arg
 * SageMaker distributed - model parallism library release note
 * Add a deprecation note for DetailedProfileConfig

## v2.131.0 (2023-01-31)

### Features

 * Display file diff on black-check
 * Support for environment variables in the HPO
 * Support role as PipelineParameter in Processor class
 * Add TrainingImageConfig support for SageMaker training jobs

### Bug Fixes and Other Changes

 * use FeatureGroup's Session in nonconcurrency ingestion
 * Update feature_group.py ingest() description
 * Do not use print function. User logger instead
 * Add batch_get_record and search API for FeatureStore
 * hashing problem for framework processors with identical source dirs

## v2.130.0 (2023-01-26)

### Features

 * Add PyTorch 1.13.1 to SDK
 * Adding image_uri config for DJL containers
 * Support specifying env-vars when creating model from model package
 * local download dir for Model and Estimator classes

### Bug Fixes and Other Changes

 * increase creation time slack minutes
 * Enable load_run auto pass in experiment config
 * Add us-isob-east-1 accounts and configs
 * Clean up Pipeline unit tests

## v2.129.0 (2023-01-19)

### Features

 * add p2 deprecation for PT>=1.13
 * TF2.11 Update to PySDK

### Bug Fixes and Other Changes

 * Improve Pipeline integ tests and fix resource leak
 * Update TF version to 2.8.4

## v2.128.0 (2023-01-10)

### Features

 * right_size() for inference recommender

### Bug Fixes and Other Changes

 * tf 2.9.3 release images
 * Retry ValueError for airflow tests

## v2.127.0 (2023-01-03)

### Features

 * tensorflow inference 2.10.1 release

## v2.126.0 (2022-12-22)

### Features

 * AutoGluon 0.6.1 image_uris

### Bug Fixes and Other Changes

 * Fix broken link in doc
 * Do not specify S3 path for disabled profiler

### Documentation Changes

 * fix the incorrect property reference

## v2.125.0 (2022-12-19)

### Features

 * add RandomSeed to support reproducible HPO

### Bug Fixes and Other Changes

 * Correct SageMaker Clarify API docstrings by changing JSONPath to JMESPath

## v2.124.0 (2022-12-16)

### Features

 * Doc update for TableFormatEnum
 * Add p4de to smddp supported instance types
 * Add disable_profiler field in config and propagate changes
 * Added doc update for dataset builder

### Bug Fixes and Other Changes

 * Use Async Inference Config when available for endpoint update

### Documentation Changes

 * smdistributed libraries release notes

## v2.123.0 (2022-12-15)

### Features

 * Add support for TF2.9.2 training images
 * Add SageMaker Experiment

## v2.122.0 (2022-12-14)

### Features

 * Feature Store dataset builder, delete_record, get_record, list_feature_group
 * Add OSU region to frameworks for DLC

### Bug Fixes and Other Changes

 * the Hyperband support fix for the HPO
 * unpin packaging version
 * Remove content type image/jpg from analysis configuration schema

## v2.121.2 (2022-12-12)

### Bug Fixes and Other Changes

 * Update for Tensorflow Serving 2.11 inference DLCs
 * Revert "fix: type hint of PySparkProcessor __init__"
 * Skip Bad Transform Test

## v2.121.1 (2022-12-09)

### Bug Fixes and Other Changes

 * Pop out ModelPackageName from pipeline definition
 * Fix failing jumpstart cache unit tests

## v2.121.0 (2022-12-08)

### Features

 * Algorithms Region Expansion OSU/DXB

### Bug Fixes and Other Changes

 * FrameworkProcessor S3 uploads
 * Add constraints file for apache-airflow

## v2.120.0 (2022-12-07)

### Features

 * Add Neo image uri config for Pytorch 1.12
 * Adding support for SageMaker Training Compiler in PyTorch estimator starting 1.12
 * Update registries with new region account number mappings.
 * Add DXB region to frameworks by DLC

### Bug Fixes and Other Changes

 * support idempotency for framework and spark processors

## v2.119.0 (2022-12-03)

### Features

 * Add Code Owners file
 * Added transform with monitoring pipeline step in transformer
 * Update TF 2.9 and TF 2.10 inference DLCs
 * make estimator accept json file as modelparallel config
 * SageMaker Training Compiler does not support p4de instances
 * Add support for SparkML v3.3

### Bug Fixes and Other Changes

 * Fix bug forcing uploaded tar to be named sourcedir
 * Update local_requirements.txt PyYAML version
 * refactoring : using with statement
 * Allow Py 3.7 for MMS Test Docker env
 * fix PySparkProcessor __init__ params type
 * type hint of PySparkProcessor __init__
 * Return ARM XGB/SKLearn tags if `image_scope` is `inference_graviton`
 * Update scipy to 1.7.3 to support M1 development envs
 * Fixing type hints for Spark processor that has instance type/count params in reverse order
 * Add DeepAR ap-northeast-3 repository.
 * Fix AsyncInferenceConfig documentation typo
 * fix ml_inf to ml_inf1 in Neo multi-version support
 * Fix type annotations
 * add neo mvp region accounts

## v2.118.0 (2022-12-01)

### Features

 * Update boto3 version to 1.26.20
 * support table format option for create feature group.
 * Support Amazon SageMaker Model Cards
 * support monitoring alerts api
 * Support Amazon SageMaker AutoMLStep

### Bug Fixes and Other Changes

 * integration test in anticipate of ProfilerConfig API changes
 * Add more integ test logic for AutoMLStep
 * update get_execution_role_arn to use role from DefaultSpaceSettings
 * bug on AutoMLInput to allow PipelineVariable
 * FinalMetricDataList is missing from the training job search resu…
 * add integration tests for Model Card
 * update AutoMLStep with cache improvement

### Documentation Changes

 * automlstep doc update

## v2.117.0 (2022-11-15)

### Features

 * add support for PT1.12.1

## v2.116.0 (2022-10-28)

### Features

 * support customized timeout for model data download and inference container startup health check for Hosting Endpoints
 * Trainium Neuron support for PyTorch
 * Pipelines cache keys update
 * Caching Improvements for SM Pipeline Workflows

## v2.115.0 (2022-10-27)

### Features

 * Add support for TF 2.10 training
 * Disable profiler for Trainium instance type
 * support the Hyperband strategy with the StrategyConfig
 * support the GridSearch strategy for hyperparameter optimization

### Bug Fixes and Other Changes

 * Update Graviton supported instance families

## v2.114.0 (2022-10-26)

### Features

 * Graviton support for XGB and SKLearn frameworks
 * Graviton support for PyTorch and Tensorflow frameworks
 * do not expand estimator role when it is pipeline parameter
 * added support for batch transform with model monitoring

### Bug Fixes and Other Changes

 * regex in tuning integs
 * remove debugger environment var set up
 * adjacent slash in s3 key
 * Fix Repack step auto install behavior
 * Add retry for airflow ParsingError

### Documentation Changes

 * doc fix

## v2.113.0 (2022-10-21)

### Features

 * support torch_distributed distribution for Trainium instances

### Bug Fixes and Other Changes

 * bump apache-airflow from 2.4.0 to 2.4.1 in /requirements/extras

### Documentation Changes

 * fix kwargs and descriptions of the smdmp checkpoint function
 * add the doc for the MonitorBatchTransformStep

## v2.112.2 (2022-10-11)

### Bug Fixes and Other Changes

 * Update Neo-TF2.x versions to TF2.9(.2)

### Documentation Changes

 * fix typo in PR template

## v2.112.1 (2022-10-10)

### Bug Fixes and Other Changes

 * fix(local-mode): loosen docker requirement to allow 6.0.0
 * CreateModelPackage API error for Scikit-learn and XGBoost frameworkss

## v2.112.0 (2022-10-09)

### Features

 * added monitor batch transform step (pipeline)

### Bug Fixes and Other Changes

 * Add PipelineVariable annotation to framework estimators

## v2.111.0 (2022-10-05)

### Features

 * Edit test file for supporting TF 2.10 training

### Bug Fixes and Other Changes

 * support kms key in processor pack local code
 * security issue by bumping apache-airflow from 2.3.4 to 2.4.0
 * instance count retrieval logic
 * Add regex for short-form sagemaker-xgboost tags
 * Upgrade attrs>=20.3.0,<23
 * Add PipelineVariable annotation to Amazon estimators

### Documentation Changes

 * add context for pytorch

## v2.110.0 (2022-09-27)

### Features

 * Support KeepAlivePeriodInSeconds for Training APIs
 * added ANALYSIS_CONFIG_SCHEMA_V1_0 in clarify
 * add model monitor image accounts for ap-southeast-3

### Bug Fixes and Other Changes

 * huggingface release test
 * Fixing the logic to return instanceCount for heterogeneousClusters
 * Disable type hints in doc signature and add PipelineVariable annotations in docstring
 * estimator hyperparameters in script mode

### Documentation Changes

 * Added link to example notebook for Pipelines local mode

## v2.109.0 (2022-09-09)

### Features

 * add search filters

### Bug Fixes and Other Changes

 * local pipeline step argument parsing bug
 * support fail_on_violation flag for check steps
 * fix links per app security scan
 * Add PipelineVariable annotation for all processor subclasses

### Documentation Changes

 * the SageMaker model parallel library 1.11.0 release

## v2.108.0 (2022-09-02)

### 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 (2022-08-29)

### 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 (2022-08-24)

### 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 (2022-08-19)

### 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 (2022-08-17)

### 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 (2022-08-05)

### 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 (2022-08-04)

### 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 (2022-07-28)

### Bug Fixes and Other Changes

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

## v2.101.0 (2022-07-27)

### 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 (2022-07-18)

### 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 (2022-07-08)

### 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 (2022-07-05)

### Features

 * Adding deepar image

### Documentation Changes

 * edit to clarify how to use inference.py

## v2.97.0 (2022-06-28)

### 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 (2022-06-20)

### 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 (2022-06-16)

### 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 (2022-06-07)

### Features

 * AutoGluon 0.4.2 image_uris support

## v2.93.1 (2022-06-06)

### Bug Fixes and Other Changes

 * add input parameterization tests for workflow job steps
 * add parameterized tests to transformer

## v2.93.0 (2022-06-03)

### Features

 * MxNet 1.9 support

### Bug Fixes and Other Changes

 * bump importlib-metadata version upperbound to support TF2.9
 * fix pipeline doc code example where process.run only accepts argument
 * Fix Tensorflow default model_dir generation when output_path is pipeline variable
 * Support transformer data parameterization

## v2.92.2 (2022-05-31)

### Bug Fixes and Other Changes

 * turn off Pipeline Parameter inheritance from python primitives
 * Add more validations for pipeline step new interfaces
 * Changed method description per AWS request

## v2.92.1 (2022-05-26)

### Bug Fixes and Other Changes

 * pin protobuf to < 4.0 to fix breaking change

## v2.92.0 (2022-05-26)

### Features

 * add 'Domain' property to RegisterModel step

### Bug Fixes and Other Changes

 * support estimator output path parameterization
 * Add back Prevent passing PipelineVariable object into image_uris.retrieve
 * jumpstart amt tracking
 * fix missing register method params for framework models
 * fix docstring for decorated functions
 * Documents: add sagemaker model building pipeline readthedocs

## v2.91.1 (2022-05-19)

### Bug Fixes and Other Changes

 * Revert Prevent passing PipelineVariable object into image_uris.retrieve

## v2.91.0 (2022-05-19)

### Features

 * Support Properties for StepCollection

### Bug Fixes and Other Changes

 * Prevent passing PipelineVariable object into image_uris.retrieve
 * support image_uri being property ref for model
 * ResourceConflictException from AWS Lambda on pipeline upsert

### Documentation Changes

 * release notes for SMDDP 1.4.1 and SMDMP 1.9.0

## v2.90.0 (2022-05-16)

### Features

 * Add ModelStep for SageMaker Model Building Pipeline

### Bug Fixes and Other Changes

 * update setup.py to add minimum python requirement of 3.6

## v2.89.0 (2022-05-11)

### Features

 * Add PT 1.11 support
 * add validation specification

### Bug Fixes and Other Changes

 * repack model locally when local_code local mode

### Documentation Changes

 * smdmp 1.8.1 release note

## v2.88.3 (2022-05-06)

### Bug Fixes and Other Changes

 * deprecate: Remove deprecated argument s3_data_distribution_type
 * Feat/jumpstart model table update

## v2.88.2 (2022-05-02)

### Bug Fixes and Other Changes

 * Automl integ describe job check
 * Implement subclass compatibility for workflow pipeline job steps

## v2.88.1 (2022-04-27)

### Bug Fixes and Other Changes

 * Add encryption setting to tar_and_upload_dir method

## v2.88.0 (2022-04-26)

### Features

 * jumpstart notebook utils -- list model ids, scripts, tasks, frameworks

### Bug Fixes and Other Changes

 * local mode printing of credentials during docker login closes #2180
 * disable endpoint context test

### Documentation Changes

 * sm model parallel 1.8.0 release notes

## v2.87.0 (2022-04-20)

### Features

 * Add Jumpstart example notebooks
 * add Tensorflow and Pytorch version for SM Training Compiler and expand to regular regions

### Bug Fixes and Other Changes

 * integs for training compiler in non-PDX regions
 * TrainingStep cache misses due to timestamp based job name
 * retry context delete
 * Add more logging when unexpected number of artifacts found

## v2.86.2 (2022-04-14)

### Bug Fixes and Other Changes

 * #using uuid to randomize, otherwise system timestamp is used

## v2.86.1 (2022-04-13)

### Bug Fixes and Other Changes

 * xgboost, sklearn network isolation for jumpstart

### Documentation Changes

 * fix minor typo

## v2.86.0 (2022-04-12)

### Features

 * Adds Spark Processing Notebook to Notebook Tests

## v2.85.0 (2022-04-11)

### Features

 * update lambda code on pipeline create/update/upsert for Lamb…
 * jumpstart model url
 * add serverless inference image_uri retrieve support

### Bug Fixes and Other Changes

 * Add back the Fix for Pipeline variables related customer issues
 * Support file URIs in ProcessingStep's code parameter

## v2.84.0 (2022-04-07)

### Features

 * dependabot integ - move all deps to requirements.txt
 * add xgboost framework version 1.5-1

## v2.83.0 (2022-04-04)

### Features

 * Hugging Face Transformers 4.17 for TF 2.6

### Bug Fixes and Other Changes

 * IOC image version select issue

## v2.82.2 (2022-04-01)

### Bug Fixes and Other Changes

 * Revert "fix: Fix Pipeline variables related customer issues (#2959)"
 * Refactor repack_model script injection, fixes tar.gz error

## v2.82.1 (2022-03-31)

### Bug Fixes and Other Changes

 * Update Inferentia Image URI Config
 * Fix Pipeline variables related customer issues
 * more logging info for static pipeline test data setup

## v2.82.0 (2022-03-30)

### Features

 * pluggable instance fallback mechanism, add CapacityError
 * support passing Env Vars to local mode training

## v2.81.1 (2022-03-29)

### Bug Fixes and Other Changes

 * Update black-check version, add support for Spark 3.1 Processing

## v2.81.0 (2022-03-26)

### Features

 * Retrieve data configuration
 * enable EnableInterContainerTrafficEncryption for model monitoring
 * Hugging Face Transformers 4.17 for PT 1.10

### Bug Fixes and Other Changes

 * remove `new` from serverless
 * temporarily skip tests impacted by data inconsistency
 * Implement override solution for pipeline variables

### Documentation Changes

 * add documentation for image_uri serverless use case
 * minor fixes for smddp 1.4.0 doc

## v2.80.0 (2022-03-18)

### Features

 * Add support for TF2.7
 * Add support for TF 2.8
 * TF242 ioc support
 * Add support for TF 2.6.3
 * Support for remote docker host
 * AutoGluon 0.3.2 and 0.4.0 image_uris

### Bug Fixes and Other Changes

 * Align max_wait definitions in EstimaorBase and Estimator
 * Add JumpStart model table build notification
 * gpu integs CapacityError - fallback to available compute
 * gpu integs CapacityError - fallback to available compute
 * jumpstart docs network isolation

### Documentation Changes

 * sagemaker distributed model parallel 1.7.0 doc

## v2.79.0 (2022-03-16)

### Features

 * Inferentia Neuron support for HuggingFace
 * custom base job name for jumpstart models/estimators
 * Python 3.9 for readthedocs

### Bug Fixes and Other Changes

 * container env generation for S3 URI and add test for the same

### Documentation Changes

 * the SageMaker distributed data parallel v1.4.0 release
 * update sagemaker training compiler docstring
 * smddp doc update

## v2.78.0 (2022-03-07)

### Features

 * TensorFlow 2.4 for Neo
 * Data Serializer

### Bug Fixes and Other Changes

 * Style update in DataSerializer
 * Remove sagemaker_job_name from hyperparameters in TrainingStep
 * reorganize test files for workflow
 * update code to get commit_id in codepipeline

## v2.77.1 (2022-02-25)

### Bug Fixes and Other Changes

 * jumpstart model table

## v2.77.0 (2022-02-22)

### Features

 * override jumpstart content bucket
 * jumpstart model ID suggestions
 * adding customer metadata support to registermodel step

### Bug Fixes and Other Changes

 * Improve Pipeline workflow unit test branch coverage
 * update lineage_trial_compoment get pipeline execution arn
 * Add lineage doc
 * Support primitive types for left value of ConditionSteps

## v2.76.0 (2022-02-17)

### Features

 * Add FailStep Support for Sagemaker Pipeline

### Bug Fixes and Other Changes

 * use recommended inference image uri from Neo API
 * pin test dependencies
 * Add exception in test_action
 * Update Static Endpoint
 * Add CMH to the non-P3 list

### Documentation Changes

 * Support for generation of Jumpstart model table on build

## v2.75.1 (2022-02-08)

### Bug Fixes and Other Changes

 * Add CMH to the non-P3 list

## v2.75.0 (2022-02-05)

### Features

 * JumpStart Integration
 * Adds support for async inference
 * Update instance types for integ test

### Bug Fixes and Other Changes

 * Revert "feature: CompilationStep support for Sagemaker Pipelines
 * gpu use p3/p2 per avail for region
 * jumpstart typo
 * pin pytest-xdist to avoid release failures
 * set sagemaker_connection and image_uri in register method
 * update to incorporate black v22, pin tox versions
 * Add deprecation warning in Clarify DataConfig

### Documentation Changes

 * Jumpstart doc strings and added new sections
 * Add Jumpstart support documentation

## v2.74.0 (2022-01-26)

### Features

 * Add support for SageMaker lineage queries context

### Bug Fixes and Other Changes

 * support specifying a facet by its column index

### Documentation Changes

 * more documentation for serverless inference

## v2.73.0 (2022-01-19)

### Features

 * Add EMRStep support in Sagemaker pipeline
 * Adds Lineage queries in artifact, context and trial components
 * Add support for SageMaker lineage queries in action
 * Adds support for Serverless inference
 * support checkpoint to be passed from estimator
 * support JsonGet/Join parameterization in tuning step Hyperparameters
 * Support model pipelines in CreateModelStep
 * enable python 3.9
 * Add models_v2 under lineage context

### Bug Fixes and Other Changes

 * allow kms_key to be passed for processing step
 * Remove duplicate vertex/edge in query lineage
 * update pricing link
 * Update CHANGELOG.md
 * fixes unnecessary session call while generating pipeline definition for lambda step

### Documentation Changes

 * Enhance smddp 1.2.2 doc
 * Document the available ExecutionVariables

## v2.72.3 (2022-01-10)

### Features

 * default repack encryption
 * support large pipeline
 * add support for pytorch 1.10.0
 
### Documentation Changes

 * SageMaker model parallel library 1.6.0 API doc

### Bug Fixes and Other Changes

 * Model Registration with BYO scripts
 * Add ContentType in test_auto_ml_describe
 * Re-deploy static integ test endpoint if it is not found
 * fix kmeans test deletion sequence, increment lineage statics
 * Increment static lineage pipeline
 * Fix lineage query integ tests
 * Add label_headers option for Clarify ModelExplainabilityMonitor
 * Add action type to lineage object
 * Collapse cross-account artifacts in query lineage response
 * Update CHANGELOG.md to remove defaulting dot characters

## v2.72.2 (2022-01-06)

### Bug Fixes and Other Changes

 * Update CHANGELOG.md
 * Increment static lineage pipeline
 * fix kmeans test deletion sequence, increment lineage statics
 * Re-deploy static integ test endpoint if it is not found
 * Add ContentType in test_auto_ml_describe
 * Model Registration with BYO scripts

### Documentation Changes

 * SageMaker model parallel library 1.6.0 API doc

## v2.72.1 (2021-12-20)

### Bug Fixes and Other Changes

 * typos and broken link
 * S3Input - add support for instance attributes
 * Prevent repack_model script from referencing nonexistent directories
 * Set ProcessingStep upload locations deterministically to avoid cache

## v2.72.0 (2021-12-13)

### Features

 * allow conditional parellel builds

### Bug Fixes and Other Changes

 * local mode - support relative file structure
 * fix endpoint bug

## v2.71.0 (2021-12-06)

### Features

 * Add support for TF 2.6
 * Adding PT 17/18 Repo
 * Add profile_name support for Feature Store ingestion

### Bug Fixes and Other Changes

 * Fix non-existent variable name
 * Add TF 2.6.2 on training
 * Recreate static lineage test data

## v2.70.0 (2021-12-02)

### Features

 * update boto3 minor version >= 1.20.18
 * Add support for SageMaker lineage queries
 * add CV shap explainability for SageMaker Clarify
 * add NLP support for SageMaker Clarify
 * Add support for ModelMonitor/Clarify integration in model building pipelines
 * adding support for transformers 4.11 for SM Training Compiler
 * SM Training Compiler with an UI to enable/disable compilation for HuggingFace DLCs to speedup training

### Bug Fixes and Other Changes

 * pin coveragepy
 * Add support for PyTorch 1.9.1
 * Update s3 path of scheduling analysis config on ClarifyCheckStep
 * documentation/logging to indicate correct place for DEBUG artifacts from SM trcomp
 * validate requested transformers version and use the best available version
 * Install custom pkgs

## v2.69.0 (2021-11-12)

### Features

 * Hugging Face Transformers 4.12 for Pt1.9/TF2.5

## v2.68.0 (2021-11-02)

### Features

 * CompilationStep support for Sagemaker Pipelines

## v2.67.0 (2021-11-01)

### Deprecations and Removals

 * deprecate Serverless Lambda model-predictor

### Features

 * add joinsource to DataConfig
 * Add support for Partial Dependence Plots(PDP) in SageMaker Clarify

### Bug Fixes and Other Changes

 * localmode subprocess parent process not sending SIGTERM to child
 * remove buildspec from repo

## v2.66.2.post0 (2021-10-28)

### Documentation Changes

 * Update estimator docstrings to add Fast File Mode

## v2.66.2 (2021-10-27)

### Bug Fixes and Other Changes

 * expose num_clusters parameter for clarify shap in shapconfig
 * Update cron job to run hourly

## v2.66.1 (2021-10-26)

### Bug Fixes and Other Changes

 * HuggingFace image_uri generation for inference
 * Update '_' and '/' with '-' in filename creation

## v2.66.0 (2021-10-25)

### Features

 * Add image_uris.retrieve() support for AutoGluon

### Documentation Changes

 * fix documentation for input types in estimator.fit
 * Add JsonGet v2 deprecation

## v2.65.0 (2021-10-21)

### Features

 * modify RLEstimator to use newly generated Ray image (1.6.0)
 * network isolation mode for xgboost
 * update clarify imageURI for PDT

### Bug Fixes and Other Changes

 * retry downstream_trials test
 * Add retries to pipeline execution

## v2.64.0 (2021-10-20)

### Deprecations and Removals

 * warn for deprecation - Lambda model-predictor

### Features

 * Add support for TF 2.5
 * Add a pre-push git hook

### Bug Fixes and Other Changes

 * add s3_analysis_config_output_path field in DataConfig constructor
 * make marketplace jobnames random

## v2.63.2 (2021-10-18)

### Bug Fixes and Other Changes

 * Update timeouts for integ tests from 20 to 40

## v2.63.1 (2021-10-14)

### Bug Fixes and Other Changes

 * HF estimator attach modified to work with py38

## v2.63.0 (2021-10-13)

### Features

 * support configurable retry for pipeline steps

## v2.62.0 (2021-10-12)

### Features

 * Hugging Face Transformers 4.10 for Pt1.8/TF2.4 & Transformers 4.11 for PT1.9&TF2.5

### Bug Fixes and Other Changes

 * repack_model script used in pipelines to support source_dir and dependencies

## v2.61.0 (2021-10-11)

### Features

 * add support for PyTorch 1.9.0

### Bug Fixes and Other Changes

 * Update TRAINING_DEFAULT_TIMEOUT_MINUTES to 40 min
 * notebook test for parallel PRs

## v2.60.0 (2021-10-08)

### Features

 * Add support for Hugging Face 4.10.2

## v2.59.8 (2021-10-07)

### Bug Fixes and Other Changes

 * fix feature store ingestion via data wrangler test

## v2.59.7 (2021-10-04)

### Bug Fixes and Other Changes

 * update feature request label
 * update bug template

## v2.59.6 (2021-09-30)

### Bug Fixes and Other Changes

 * ParamValidationError when scheduling a Clarify model monitor

## v2.59.5 (2021-09-29)

### Bug Fixes and Other Changes

 * support maps in step parameters

## v2.59.4 (2021-09-27)

### Bug Fixes and Other Changes

 * add checks for ExecutionRole in UserSettings, adds more unit tests
 * add pytorch 1.8.1 for huggingface

## v2.59.3.post0 (2021-09-22)

### Documentation Changes

 * Info about offline s3 bucket key when creating feature group

## v2.59.3 (2021-09-20)

## v2.59.2 (2021-09-15)

### Bug Fixes and Other Changes

 * unit tests for KIX and remove regional calls to boto

### Documentation Changes

 * Remove Shortbread

## v2.59.1.post0 (2021-09-13)

### Documentation Changes

 * update experiment config doc on fit method

## v2.59.1 (2021-09-02)

### Bug Fixes and Other Changes

 * pin docker to 5.0.0

## v2.59.0 (2021-09-01)

### Features

 * Add KIX account for SM XGBoost 1.2-2 and 1.3-1

### Bug Fixes and Other Changes

 * revert #2572 and address #2611

## v2.58.0 (2021-08-31)

### Features

 * update debugger for KIX
 * support displayName and description for pipeline steps

### Bug Fixes and Other Changes

 * localmode subprocess parent process not sending SIGTERM to child

## v2.57.0 (2021-08-30)

### Deprecations and Removals

 * Remove stale S3DownloadMode from test_session.py

### Features

 * update clarify imageURI for KIX

### Bug Fixes and Other Changes

 * propagate KMS key to model.deploy
 * Propagate tags and VPC configs to repack model steps

## v2.56.0 (2021-08-26)

### Features

 * Add NEO KIX Configuration
 * Algorithms region launch on KIX

### Bug Fixes and Other Changes

 * remove dots from CHANGELOG

## v2.55.0 (2021-08-25)

### Features

 * Add information of Amazon-provided analysis image used by Model Monitor

### Bug Fixes and Other Changes

 * Update Changelog to fix release
 * Fixing the order of populating container list
 * pass network isolation config to pipelineModel
 * Deference symbolic link when create tar file
 * multiprocess issue in feature_group.py
 * deprecate tag logic on Association

### Documentation Changes

 * add dataset_definition to processing page

## v2.54.0 (2021-08-16)

### Features

 * add pytorch 1.5.1 eia configuration

### Bug Fixes and Other Changes

 * issue #2253 where Processing job in Local mode would call Describe API

## v2.53.0 (2021-08-12)

### Features

 * support tuning step parameter range parameterization + support retry strategy in tuner

## v2.52.2.post0 (2021-08-11)

### Documentation Changes

 * clarify that default_bucket creates a bucket
 * Minor updates to Clarify API documentation

## v2.52.2 (2021-08-10)

### Bug Fixes and Other Changes

 * sklearn integ tests, remove swallowing exception on feature group delete attempt
 * sklearn integ test for custom bucket

### Documentation Changes

 * Fix dataset_definition links
 * Document LambdaModel and LambdaPredictor classes

## v2.52.1 (2021-08-06)

### Bug Fixes and Other Changes

 * revert #2251 changes for sklearn processor

## v2.52.0 (2021-08-05)

### Features

 * processors that support multiple Python files, requirements.txt, and dependencies.
 * support step object in step depends on list

### Bug Fixes and Other Changes

 * enable isolation while creating model from job
 * update `sagemaker.serverless` integration test
 * Use correct boto model name for RegisterModelStep properties

## v2.51.0 (2021-08-03)

### Features

 * add LambdaStep support for SageMaker Pipelines
 * support JsonGet for all step types

## v2.50.1 (2021-08-02)

### Bug Fixes and Other Changes

 * null checks for uploaded_code and entry_point

### Documentation Changes

 * update sagemaker.estimator.EstimatorBase
 * Mark baseline as optional in KernelSHAP.

## v2.50.0 (2021-07-28)

### Features

 * add KIX region to image_uris

### Bug Fixes and Other Changes

 * Rename `PredictorBase.delete_endpoint` as `PredictorBase.delete_predictor`
 * incorrect default argument for callback output parameter

### Documentation Changes

 * Remove years from copyright boilerplate
 * Fix documentation formatting for PySpark and SparkJar processors

### Testing and Release Infrastructure

 * enable py38 tox env

## v2.49.2 (2021-07-21)

### Bug Fixes and Other Changes

 * order of populating container list
 * upgrade Adobe Analytics cookie to 3.0

## v2.49.1 (2021-07-19)

### Bug Fixes and Other Changes

 * Set flag when debugger is disabled
 * KMS Key fix for kwargs
 * Update BiasConfig to accept multiple facet params

### Documentation Changes

 * Update huggingface estimator documentation

## v2.49.0 (2021-07-15)

### Features

 * Adding serial inference pipeline support to RegisterModel Step

### Documentation Changes

 * add tuning step get_top_model_s3_uri and callback step to doc
 * links for HF in sdk
 * Add Clarify module to Model Monitoring API docs

## v2.48.2 (2021-07-12)

### Bug Fixes and Other Changes

 * default time for compilation jobs
 * skip hf inference test

## v2.48.1 (2021-07-08)

### Bug Fixes and Other Changes

 * skip HF inference test
 * remove upsert from test_workflow

### Documentation Changes

 * Add Hugging Face docs
 * add tuning step to doc

## v2.48.0 (2021-07-07)

### Features

 * HuggingFace Inference

### Bug Fixes and Other Changes

 * add support for SageMaker workflow tuning step

## v2.47.2.post0 (2021-07-01)

### Documentation Changes

 * smddp 1.2.1 release note / convert md to rst
 * add smd model parallel 1.4.0 release note / restructure doc files

## v2.47.2 (2021-06-30)

### Bug Fixes and Other Changes

 * handle tags when upsert pipeine

## v2.47.1 (2021-06-27)

### Bug Fixes and Other Changes

 * revert "fix: jsonGet interpolation issue 2426 + allow step depends on pass in step instance (#2477)"

## v2.47.0 (2021-06-25)

### Features

 * support job_name_prefix for Clarify

### Bug Fixes and Other Changes

 * Add configuration option with headers for Clarify Explainability
 * jsonGet interpolation issue 2426 + allow step depends on pass in step instance
 * add default retries to feature group ingestion.
 * Update using_pytorch.rst
 * kms key does not propapate in register model step
 * Correctly interpolate Callback output parameters

## v2.46.1 (2021-06-22)

### Bug Fixes and Other Changes

 * Register model step tags

### Documentation Changes

 * update to include new batch_get_record api call
 * Correct type annotation for TrainingStep inputs
 * introduce input mode FastFile
 * update hf transformer version

## v2.46.0 (2021-06-15)

### Features

 * Add HF transformer version 4.6.1

### Bug Fixes and Other Changes

 * encode localmode payload to UTF-8
 * call DescribeDomain as fallback in get_execution_role
 * parameterize PT and TF version for HuggingFace tests

### Documentation Changes

 * Add import statement in Batch Transform Overview doc

## v2.45.0 (2021-06-07)

### Features

 * Add support for Callback steps in model building pipelines

## v2.44.0 (2021-06-01)

### Features

 * support endpoint_name_prefix, seed and version for Clarify

## v2.43.0 (2021-05-31)

### Features

 * add xgboost framework version 1.3-1

### Bug Fixes and Other Changes

 * remove duplicated tags in _append_project_tags

## v2.42.1 (2021-05-27)

### Bug Fixes and Other Changes

 * default value removed if zero for integer param

## v2.42.0 (2021-05-24)

### Features

 * support for custom pipeline execution name
 * Add data ingestion only data-wrangler flow recipe generation helper function

### Bug Fixes and Other Changes

 * add kms key for processing job code upload
 * remove failing notebooks from notebook pr test
 * fix in and not in condition bug
 * Update overview.rst

### Documentation Changes

 * Update "Ask a question" contact link
 * Update smdp docs with sparse_as_dense support

## v2.41.0 (2021-05-17)

### Features

 * add pipeline experiment config
 * add data wrangler processor
 * support RetryStrategy for training jobs

### Bug Fixes and Other Changes

 * fix repack pipeline step by putting inference.py in "code" sub dir
 * add data wrangler image uri
 * fix black-check errors

## v2.40.0 (2021-05-11)

### Features

 * add xgboost framework version 1.2-2

### Bug Fixes and Other Changes

 * fix get_execution_role on Studio
 * [fix] Check py_version existence in RegisterModel step

### Documentation Changes

 * SM Distributed EFA Launch

## v2.39.1 (2021-05-05)

### Bug Fixes and Other Changes

 * RegisterModel step and custom dependency support

### Documentation Changes

 * reverting SageMaker distributed data parallel EFA doc updates
 * adding new version, SM dist. data parallel 1.2.0.
 * add current Hugging Face supported versions
 * SMDDP 1.2.0 release notes

## v2.39.0.post0 (2021-05-04)

### Testing and Release Infrastructure

 * disable smdataparallel tests

## v2.39.0 (2021-04-28)

### Features

 * Add HF transformer version 4.5.0

### Bug Fixes and Other Changes

 * Allow hyperparameters in Tensorflow estimator to be parameterized

### Testing and Release Infrastructure

 * black format unit tests

## v2.38.0 (2021-04-21)

### Features

 * support multiprocess feature group ingest (#2111)

## v2.37.0 (2021-04-20)

### Features

 * add experiment_config for clarify processing job

### Documentation Changes

 * release notes for smdistributed.dataparallel v1.1.2

## v2.36.0 (2021-04-19)

### Features

 * enable smdataparallel custom mpi options support

## v2.35.0 (2021-04-14)

### Features

 * add support for PyTorch 1.8.1

### Bug Fixes and Other Changes

 * boto3 client param updated for feature store
 * Updated release notes and API doc for smd model parallel 1.3.1

## v2.34.0 (2021-04-12)

### Features

 * Add support for accelerator in Clarify

### Bug Fixes and Other Changes

 * add Documentation for how to use
 * enable local mode tests that were skipped
 * add integ test for HuggingFace with TensorFlow

### Documentation Changes

 * release notes for smdistributed.dataparallel v1.1.1
 * fixing the SageMaker distributed version references

### Testing and Release Infrastructure

 * pin version for ducutils

## v2.33.0 (2021-04-05)

### Features

 * Add environment variable support for SageMaker training job

### Bug Fixes and Other Changes

 * add version length mismatch validation for HuggingFace
 * Disable debugger when checkpointing is enabled with distributed training
 * map user context is list associations response

### Testing and Release Infrastructure

 * disable_profiler on mx-horovod test

## v2.32.1 (2021-04-01)

### Bug Fixes and Other Changes

 * disable profiler in some release tests
 * remove outdated notebook from test
 * add compilation option for ml_eia2
 * add short version to smdataparallel supported list

### Documentation Changes

 * creating a "latest" version sm distributed docs
 * add docs for Sagemaker Model Parallel 1.3, released with PT 1.8
 * update PyTorch version in doc

## v2.32.0 (2021-03-26)

### Features

 * upgrade neo mxnet to 1.8
 * Enable Profiler in China Regions

### Bug Fixes and Other Changes

 * use workflow parameters in training hyperparameters (#2114) (#2115)
 * skip HuggingFace tests in regions without p2 instances

### Documentation Changes

 * add Feature Store methods docs

## v2.31.1 (2021-03-23)

### Bug Fixes and Other Changes

 * added documentation for Hugging Face Estimator
 * mark HuggingFace tests as release tests

### Documentation Changes

 * adding version 1.1.0 docs for smdistributed.dataparallel

## v2.31.0 (2021-03-23)

### Features

 * add HuggingFace framework estimator
 * update TF framework version support
 * Support all processor types in ProcessingStep

### Bug Fixes and Other Changes

 * Add pipelines functions.

## v2.30.0 (2021-03-17)

### Features

 * add support for PyTorch 1.8.0
 * Allow users to send custom attributes to the model endpoint

### Bug Fixes and Other Changes

 * use ResolvedOutputS3Uir for Hive DDL LOCATION
 * Do lazy initialization in predictor

## v2.29.2 (2021-03-11)

### Bug Fixes and Other Changes

 * move pandas to required dependency from specific use cases

## v2.29.1 (2021-03-09)

### Bug Fixes and Other Changes

 * return all failed row indices in feature_group.ingest
 * move service-role path parsing for AmazonSageMaker-ExecutionRole for get_execution_role() into except block of IAM get_role() call and add warning message
 * add description parameter for RegisterModelStep
 * add type annotations for Lineage

### Documentation Changes

 * remove ellipsis from CHANGELOG.md

## v2.29.0 (2021-03-04)

### Features

 * add support for TensorFlow 2.4.1 for training, inference and data parallel
 * Support profiler config in the pipeline training job step
 * support PyTorch 1.7.1 training, inference and data parallel

## v2.28.0 (2021-03-03)

### Features

 * support creating endpoints with model images from private registries

## v2.27.1 (2021-03-03)

### Bug Fixes and Other Changes

 * Change Estimator.logs() to use latest_training_job.name
 * mask creds from docker commands in local mode. Closes #2118

### Documentation Changes

 * fix pipelines processing step typo
 * remove double 'enable-network-isolation' description

## v2.27.0 (2021-03-01)

### Features

 * add inference_id to predict

### Bug Fixes and Other Changes

 * disable profiler by default for regions not support it

### Documentation Changes

 * add TF 2.4.1 support to sm distributed data parallel docs and other updates

## v2.26.0 (2021-02-26)

### Features

 * Add Framework Version support for PyTorch compilation (Neo)

### Bug Fixes and Other Changes

 * add mxnet 1.7.0 eia configuration
 * update source constructor for lineage action and artifact

### Documentation Changes

 * fix typo in create_monitoring_schedule method

## v2.25.2 (2021-02-25)

### Bug Fixes and Other Changes

 * Use the output path to store the Clarify config file
 * feature group should ignore nan values
 * ignore failing smdataparallel test
 * Add tests for Training job & Transform job in visualizer
 * visualizer for pipeline processing job steps

### Documentation Changes

 * update doc for Elastic Inference MXNet 1.7.0

## v2.25.1 (2021-02-20)

### Bug Fixes and Other Changes

 * Add tests for visualizer to improve test coverage

### Documentation Changes

 * specify correct return type

### Testing and Release Infrastructure

 * rename canary_quick pytest mark to release

## v2.25.0 (2021-02-19)

### Features

 * Enable step caching
 * Add other Neo supported regions for Inferentia inference images

### Bug Fixes and Other Changes

 * remove FailStep from pipelines
 * use sagemaker_session in workflow tests
 * use ECR public for multidatamodel tests
 * add the mapping from py3 to cuda11 images
 * Add 30s cap time for tag tests
 * add build spec for slow tests
 * mark top 10 slow tests
 * remove slow test_run_xxx_monitor_baseline tests
 * pin astroid to 2.4.2

### Testing and Release Infrastructure

 * unmark more flaky integ tests
 * remove canary_quick pytest mark from flaky/unnecessary tests
 * remove python3.8 from buildspec
 * remove py38 tox env
 * fix release buildspec typo
 * unblock regional release builds
 * lower test TPS for experiment analytics
 * move package preparation and publishing to the deploy step

## v2.24.5 (2021-02-12)

### Bug Fixes and Other Changes

 * test_tag/test_tags method assert fix in association tests

### Documentation Changes

 * removing mention of TF 2.4 from SM distributed model parallel docs
 * adding details about mpi options, other small updates

## v2.24.4 (2021-02-09)

### Bug Fixes and Other Changes

 * add integration test for listing artifacts by type
 * List Associations integ tests

## v2.24.3 (2021-02-04)

### Bug Fixes and Other Changes

 * Remove pytest fixture and fix test_tag/s method

## v2.24.2 (2021-02-03)

### Bug Fixes and Other Changes

 * use 3.5 version of get-pip.py
 * SM DDP release notes/changelog files

### Documentation Changes

 * adding versioning to sm distributed data parallel docs

## v2.24.1 (2021-01-28)

### Bug Fixes and Other Changes

 * fix collect-tests tox env
 * create profiler specific unsupported regions
 * Update smd_model_parallel_pytorch.rst

## v2.24.0 (2021-01-22)

### Features

 * add support for Std:Join for pipelines
 * Map image name to image uri
 * friendly names for short URIs

### Bug Fixes and Other Changes

 * increase allowed time for search to get updated
 * refactor distribution config construction

### Documentation Changes

 * Add SMP 1.2.0 API docs

## v2.23.6 (2021-01-20)

### Bug Fixes and Other Changes

 * add artifact, action, context to virsualizer

## v2.23.5 (2021-01-18)

### Bug Fixes and Other Changes

 * increase time allowed for trial components to index

## v2.23.4.post0 (2021-01-14)

### Documentation Changes

 * update predict_fn implementation for PyTorch EIA 1.5.1

## v2.23.4 (2021-01-13)

### Bug Fixes and Other Changes

 * remove captureWarninig setting

## v2.23.3 (2021-01-12)

### Bug Fixes and Other Changes

 * improve optional dependency error message
 * add debugger rule container account in PDT
 * assert step execution first in pipeline test
 * add service inserted fields to generated Hive DDL

### Documentation Changes

 * fix description for max_wait
 * use correct classpath in V2 alias documentation.
 * Bad arg name in feat-store ingestion manager

## v2.23.2 (2021-01-06)

### Bug Fixes and Other Changes

 * remove shell=True in subprocess.check_output
 * use SecurityConfig dict key

### Documentation Changes

 * remove D212 from ignore to comply with PEP257 standards

## v2.23.1 (2020-12-29)

### Bug Fixes and Other Changes

 * update git utils temp file
 * Allow online store only FeatureGroups

### Documentation Changes

 * inform contributors when not to mark integration tests as canaries
 * adding change log for smd model parallel

## v2.23.0 (2020-12-23)

### Features

 * Add support for actions in debugger rules.

### Bug Fixes and Other Changes

 * include sparkml 2.4 in image uri config properly
 * Mount metadata dir only if it exists
 * allow urllib3 1.26

## v2.22.0 (2020-12-22)

### Features

 * Support local mode for Amazon SageMaker Processing jobs

### Bug Fixes and Other Changes

 * Add API enhancements for SMP
 * adjust naming convention; fix links
 * lower value used in featurestore test

### Documentation Changes

 * Update GTDD instructions

## v2.21.0 (2020-12-21)

### Features

 * remove D205 to enable PEP257 Docstring Conventions

### Bug Fixes and Other Changes

 * Pin smdebug-rulesconfig to 1.0.0
 * use itertuples to ingest pandas dataframe to FeatureStore

## v2.20.0 (2020-12-16)

### Features

 * add dataset definition support for processing jobs

### Bug Fixes and Other Changes

 * include workflow integ tests with clarify and debugger enabled
 * only run DataParallel and EdgePackaging tests in supported regions

### Documentation Changes

 * fix smp code example, add note for CUDA 11 to sdp
 * adding note about CUDA 11 to SMP. Small title update PyTorch

## v2.19.0 (2020-12-08)

### Features

 * add tensorflow 1.15.4 and 2.3.1 as valid versions
 * add py36 as valid python version for pytorch 1.6.0
 * auto-select container version for p4d and smdistributed
 * add edge packaging job support
 * Add Clarify Processor, Model Bias, Explainability, and Quality Monitors support. (#494)
 * add model parallelism support
 * add data parallelism support (#454) (#511)
 * support creating and updating profiler in training job (#444) (#526)

### Bug Fixes and Other Changes

 * bump boto3 and smdebug_rulesconfig versions for reinvent and enable data parallel integ tests
 * run UpdateTrainingJob tests only during allowed secondary status
 * Remove workarounds and apply fixes to Clarify and MM integ tests
 * add p4d to smdataparallel supported instances
 * Mount metadata directory when starting local mode docker container
 * add integ test for profiler
 * Re-enable model monitor integration tests.

### Documentation Changes

 * add SageMaker distributed libraries documentation
 * update documentation for the new SageMaker Debugger APIs
 * minor updates to doc strings

## v2.18.0 (2020-12-03)

### Features

 * all de/serializers support content type
 * warn on 'Stopped' (non-Completed) jobs
 * all predictors support serializer/deserializer overrides

### Bug Fixes and Other Changes

 * v2 upgrade tool should ignore cell starting with '%'
 * use iterrows to iterate pandas dataframe
 * check for distributions in TF estimator

### Documentation Changes

 * Update link to Sagemaker PyTorch Docker Containers
 * create artifact restricted to SM context note

### Testing and Release Infrastructure

 * remove flaky assertion in test_integ_history_server
 * adjust assertion of TensorFlow MNIST test

## v2.17.0 (2020-12-02)

### Features

 * bump minor version for re:Invent 2020 features

## v2.16.4 (2020-12-01)

### Features

 * Add re:Invent 2020 features

### Bug Fixes and Other Changes

 * use eia python version fixture in integration tests
 * bump version to 2.17.0 for re:Invent-2020

### Documentation Changes

 * add feature store documentation

## v2.16.3.post0 (2020-11-17)

### Testing and Release Infrastructure

 * use ECR-hosted image for ubuntu:16.04

## v2.16.3 (2020-11-11)

### Bug Fixes and Other Changes

 * fix failures for multiple spark run() invocations

## v2.16.2 (2020-11-09)

### Bug Fixes and Other Changes

 * create default bucket only if needed

## v2.16.1 (2020-10-28)

### Bug Fixes and Other Changes

 * ensure 1p algos are compatible with forward-port

## v2.16.0.post0 (2020-10-28)

### Documentation Changes

 * clarify non-breaking changes after v1 forward port

## v2.16.0 (2020-10-27)

### Features

 * update image uri for neo tensorflow

## v2.15.4 (2020-10-26)

### Bug Fixes and Other Changes

 * add kms_key optional arg to Pipeline.deploy()

### Documentation Changes

 * Debugger API - improve docstrings and add examples

## v2.15.3 (2020-10-20)

### Bug Fixes and Other Changes

 * refactor _create_model_request

## v2.15.2 (2020-10-19)

### Bug Fixes and Other Changes

 * preserve model_dir bool value
 * refactor out batch transform job input generation

## v2.15.1 (2020-10-15)

### Bug Fixes and Other Changes

 * include more notebook tests, logger to warn
 * include managed spot training notebook test
 * add missing account IDs for af-south-1 and eu-south-1

## v2.15.0 (2020-10-07)

### Features

 * add network isolation support for PipelineModel
 * forward-port v1 names as deprecated aliases

### Bug Fixes and Other Changes

 * include additional docstyle improvements
 * check optional keyword before accessing
 * use local updated args; use train_max_wait
 * cross-platform file URI for Processing
 * update kwargs target attribute

### Documentation Changes

 * fix Spark class links
 * kwargs descriptions include clickable links
 * fix broken link to moved notebook

## v2.14.0 (2020-10-05)

### Features

 * upgrade Neo MxNet to 1.7

### Bug Fixes and Other Changes

 * add a condition to retrieve correct image URI for xgboost

## v2.13.0 (2020-09-30)

### Features

 * add xgboost framework version 1.2-1

### Bug Fixes and Other Changes

 * revert "feature: upgrade Neo MxNet to 1.7 (#1928)"

## v2.12.0 (2020-09-29)

### Features

 * upgrade Neo MxNet to 1.7

## v2.11.0 (2020-09-28)

### Features

 * Add SDK support for SparkML Serving Container version 2.4

### Bug Fixes and Other Changes

 * pin pytest version <6.1.0 to avoid pytest-rerunfailures breaking changes
 * temporarily skip the MxNet Neo test until we fix them

### Documentation Changes

 * fix conda setup for docs

## v2.10.0 (2020-09-23)

### Features

 * add inferentia pytorch inference container config

## v2.9.2 (2020-09-21)

### Bug Fixes and Other Changes

 * allow kms encryption upload for processing

## v2.9.1 (2020-09-17)

### Bug Fixes and Other Changes

 * update spark image_uri config with eu-north-1 account

## v2.9.0 (2020-09-17)

### Features

 * add MXNet 1.7.0 images

### Documentation Changes

 * removed Kubernetes workflow content

## v2.8.0 (2020-09-16)

### Features

 * add spark processing support to processing jobs

### Bug Fixes and Other Changes

 * remove DataFrame assert from unrelated test

## v2.7.0 (2020-09-15)

### Features

 * reshape Parents into experiment analytics dataframe

## v2.6.0 (2020-09-14)

### Features

 * add model monitor image accounts for af-south-1 and eu-south-1

### Bug Fixes and Other Changes

 * enforce some docstyle conventions

### Documentation Changes

 * fix CSVSerializer typo in v2.rst

## v2.5.5 (2020-09-10)

### Bug Fixes and Other Changes

 * update PyTorch 1.6.0 inference image uri config
 * set use_spot_instances and max_wait as init params from job description
 * run integ tests when image_uri_config jsons are changed
 * Revert "fix: update pytorch inference 1.6 image uri config (#1873)"
 * update pytorch inference 1.6 image uri config

### Documentation Changes

 * fix typo in v2.rst

### Testing and Release Infrastructure

 * fix PyTorch inference packed model integ test

## v2.5.4 (2020-09-08)

### Bug Fixes and Other Changes

 * update max_run_wait to max_wait in v2.rst for estimator parameters
 * Updating regional account ids for af-south-1 and eu-south-1
 * add account ids for af-south-1 and eu-south-1 for debugger rules

## v2.5.3 (2020-09-02)

### Bug Fixes and Other Changes

 * Revert "change: update image uri config for pytorch 1.6.0 inference (#1864)"
 * update image uri config for pytorch 1.6.0 inference
 * add missing framework version image uri config

## v2.5.2 (2020-08-31)

### Bug Fixes and Other Changes

 * refactor normalization of args for processing
 * set TF 2.1.1 as highest py2 version for TF
 * decrease integ test concurrency and increase delay between retries

## v2.5.1 (2020-08-27)

### Bug Fixes and Other Changes

 * formatting changes from updates to black

## v2.5.0 (2020-08-25)

### Features

 * add mypy tox target

### Bug Fixes and Other Changes

 * break out methods to get processing arguments
 * break out methods to get train arguments

## v2.4.2 (2020-08-24)

### Bug Fixes and Other Changes

 * check ast node on later renamers for cli v2 updater

### Documentation Changes

 * Clarify removals in v2

## v2.4.1 (2020-08-19)

### Bug Fixes and Other Changes

 * update rulesconfig to 0.1.5

## v2.4.0 (2020-08-17)

### Features

 * Neo algorithm accounts for af-south-1 and eu-south-1

### Bug Fixes and Other Changes

 * upgrade pytest and other deps, tox clean-up
 * upgrade airflow to 1.10.11
 * update exception assertion with new api change
 * docs: Add SerDe documentation

## v2.3.0 (2020-08-11)

### Features

 * support TF training 2.3

### Documentation Changes

 * update 1p estimators class description

## v2.2.0 (2020-08-10)

### Features

 * new 1P algorithm accounts for af-south-1 and eu-south-1

### Bug Fixes and Other Changes

 * update debugger us-east-1 account
 * docs: Add information on Amazon SageMaker Operators usage in China

## v2.1.0 (2020-08-06)

### Features

 * add DLC account numbers for af-south-1 and eu-south-1

## v2.0.1 (2020-08-05)

### Bug Fixes and Other Changes

 * use pathlib.PurePosixPath for S3 URLs and Unix paths
 * fix regions for updated RL images

### Documentation Changes

 * update CHANGELOG to reflect v2.0.0 changes

### Testing and Release Infrastructure

 * remove v2-incompatible notebooks from notebook build

## v2.0.0 (2020-08-04)

### Breaking Changes

 * rename s3_input to TrainingInput
 * Move _NumpyDeserializer to sagemaker.deserializers.NumpyDeserializer
 * rename numpy_to_record_serializer to RecordSerializer
 * Move _CsvDeserializer to sagemaker.deserializers and rename to CSVDeserializer
 * Move _JsonSerializer to sagemaker.serializers.JSONSerializer
 * Move _NPYSerializer to sagemaker.serializers and rename to NumpySerializer
 * Move _JsonDeserializer to sagemaker.deserializers.JSONDeserializer
 * Move _CsvSerializer to sagemaker.serializers.CSVSerializer
 * preserve script path when S3 source_dir is provided
 * use image_uris.retrieve() for XGBoost URIs
 * deprecate sagemaker.amazon.amazon_estimator.get_image_uri()
 * deprecate fw_registry module and use image_uris.retrieve() for SparkML
 * deprecate Python SDK CLI
 * Remove the content_types module
 * deprecate unused parameters
 * deprecate fw_utils.create_image_uri()
 * use images_uris.retrieve() for Debugger
 * deprecate fw_utils.parse_s3_url in favor of s3.parse_s3_url
 * deprecate unused functions from utils and fw_utils
 * Remove content_type and accept parameters from Predictor
 * Add parameters to deploy and remove parameters from create_model
 * Add LibSVM serializer for XGBoost predictor
 * move ShuffleConfig from sagemaker.session to sagemaker.inputs
 * deprecate get_ecr_image_uri_prefix
 * rename estimator.train_image() to estimator.training_image_uri()
 * deprecate is_version_equal_or_higher and is_version_equal_or_lower
 * default wait=True for HyperparameterTuner.fit() and Transformer.transform()
 * remove unused bin/sagemaker-submit file

### Features

 * start new module for retrieving prebuilt SageMaker image URIs
 * handle separate training/inference images and EI in image_uris.retrieve
 * add support for Amazon algorithms in image_uris.retrieve()
 * Add pandas deserializer
 * Remove LegacySerializer and LegacyDeserializer
 * Add sparse matrix serializer
 * Add v2 SerDe compatability
 * Add JSON Lines serializer
 * add framework upgrade tool
 * add 1p algorithm image_uris migration tool
 * Update migration tool to support breaking changes to create_model
 * support PyTorch 1.6 training

### Bug Fixes and Other Changes

 * handle named variables in v2 migration tool
 * add modifier for s3_input class
 * add XGBoost support to image_uris.retrieve()
 * add MXNet configuration to image_uris.retrieve()
 * add remaining Amazon algorithms for image_uris.retrieve()
 * add PyTorch configuration for image_uris.retrieve()
 * make image_scope optional for some images in image_uris.retrieve()
 * separate logs() from attach()
 * use image_uris.retrieve instead of fw_utils.create_image_uri for DLC frameworks
 * use images_uris.retrieve() for scikit-learn classes
 * use image_uris.retrieve() for RL images
 * Rename BaseDeserializer.deserialize data parameter
 * Add allow_pickle parameter to NumpyDeserializer
 * Fix scipy.sparse imports
 * Improve code style of SerDe compatibility
 * use image_uris.retrieve for Neo and Inferentia images
 * use generated RL version fixtures and update Ray version
 * use image_uris.retrieve() for ModelMonitor default image
 * use _framework_name for 'protected' attribute
 * Fix JSONLinesDeserializer
 * upgrade TFS version and fix py_versions KeyError
 * Fix PandasDeserializer tests to more accurately mock response
 * don't require instance_type for image_uris.retrieve() if only one option
 * ignore code cells with shell commands in v2 migration tool
 * Support multiple Accept types

### Documentation Changes

 * fix pip install command
 * document name changes for TFS classes
 * document v2.0.0 changes
 * update KFP full pipeline

### Testing and Release Infrastructure

 * generate Chainer latest version fixtures from config
 * use generated TensorFlow version fixtures
 * use generated MXNet version fixtures

## v1.72.0 (2020-07-29)

### Features

 * Neo: Add Granular Target Description support for compilation

### Documentation Changes

 * Add xgboost doc on bring your own model
 * fix typos on processing docs

## v1.71.1 (2020-07-27)

### Bug Fixes and Other Changes

 * remove redundant information from the user_agent string.

### Testing and Release Infrastructure

 * use unique model name in TFS integ tests
 * use pytest-cov instead of coverage

## v1.71.0 (2020-07-23)

### Features

 * Add mpi support for mxnet estimator api

### Bug Fixes and Other Changes

 * use 'sagemaker' logger instead of root logger
 * account for "py36" and "py37" in image tag parsing

## v1.70.2 (2020-07-22)

### Bug Fixes and Other Changes

 * convert network_config in processing_config to dict

### Documentation Changes

 * Add ECR URI Estimator example

## v1.70.1 (2020-07-21)

### Bug Fixes and Other Changes

 * Nullable fields in processing_config

## v1.70.0 (2020-07-20)

### Features

 * Add model monitor support for us-gov-west-1
 * support TFS 2.2

### Bug Fixes and Other Changes

 * reshape Artifacts into data frame in ExperimentsAnalytics

### Documentation Changes

 * fix MXNet version info for requirements.txt support

## v1.69.0 (2020-07-09)

### Features

 * Add ModelClientConfig Fields for Batch Transform

### Documentation Changes

 * add KFP Processing component

## v2.0.0.rc1 (2020-07-08)

### Breaking Changes

 * Move StreamDeserializer to sagemaker.deserializers
 * Move StringDeserializer to sagemaker.deserializers
 * rename record_deserializer to RecordDeserializer
 * remove "train_" where redundant in parameter/variable names
 * Add BytesDeserializer
 * rename image to image_uri
 * rename image_name to image_uri
 * create new inference resources during model.deploy() and model.transformer()
 * rename session parameter to sagemaker_session in S3 utility classes
 * rename distributions to distribution in TF/MXNet estimators
 * deprecate update_endpoint arg in deploy()
 * create new inference resources during estimator.deploy() or estimator.transformer()
 * deprecate delete_endpoint() for estimators and HyperparameterTuner
 * refactor Predictor attribute endpoint to endpoint_name
 * make instance_type optional for Airflow model configs
 * refactor name of RealTimePredictor to Predictor
 * remove check for Python 2 string in sagemaker.predictor._is_sequence_like()
 * deprecate sagemaker.utils.to_str()
 * drop Python 2 support

### Features

 * add BaseSerializer and BaseDeserializer
 * add Predictor.update_endpoint()

### Bug Fixes and Other Changes

 * handle "train_*" renames in v2 migration tool
 * handle image_uri rename for Session methods in v2 migration tool
 * Update BytesDeserializer accept header
 * handle image_uri rename for estimators and models in v2 migration tool
 * handle image_uri rename in Airflow model config functions in v2 migration tool
 * update migration tool for S3 utility functions
 * set _current_job_name and base_tuning_job_name in HyperparameterTuner.attach()
 * infer base name from job name in estimator.attach()
 * ensure generated names are < 63 characters when deploying compiled models
 * add TF migration documentation to error message

### Documentation Changes

 * update documentation with v2.0.0.rc1 changes
 * remove 'train_*' prefix from estimator parameters
 * update documentation for image_name/image --> image_uri

### Testing and Release Infrastructure

 * refactor matching logic in v2 migration tool
 * add cli modifier for RealTimePredictor and derived classes
 * change coverage settings to reduce intermittent errors
 * clean up pickle.load logic in integ tests
 * use fixture for Python version in framework integ tests
 * remove assumption of Python 2 unit test runs

## v1.68.0 (2020-07-07)

### Features

 * add spot instance support for AlgorithmEstimator

### Documentation Changes

 * add xgboost documentation for inference

## v1.67.1.post0 (2020-07-01)

### Documentation Changes

 * add Step Functions SDK info

## v1.67.1 (2020-06-30)

### Bug Fixes and Other Changes

 * add deprecation warnings for estimator.delete_endpoint() and tuner.delete_endpoint()

## v1.67.0 (2020-06-29)

### Features

 * Apache Airflow integration for SageMaker Processing Jobs

### Bug Fixes and Other Changes

 * fix punctuation in warning message

### Testing and Release Infrastructure

 * address warnings about pytest custom marks, error message checking, and yaml loading
 * mark long-running cron tests
 * fix tox test dependencies and bump coverage threshold to 86%

## v1.66.0 (2020-06-25)

### Features

 * add 3.8 as supported python version

### Testing and Release Infrastructure

 * upgrade airflow to latest stable version
 * update feature request issue template

## v1.65.1.post1 (2020-06-24)

### Testing and Release Infrastructure

 * add py38 to buildspecs

## v1.65.1.post0 (2020-06-22)

### Documentation Changes

 * document that Local Mode + local code doesn't support dependencies arg

### Testing and Release Infrastructure

 * upgrade Sphinx to 3.1.1

## v1.65.1 (2020-06-18)

### Bug Fixes and Other Changes

 * remove include_package_data=True from setup.py

### Documentation Changes

 * add some clarification to Processing docs

### Testing and Release Infrastructure

 * specify what kinds of clients in PR template

## v1.65.0 (2020-06-17)

### Features

 * support for describing hyperparameter tuning job

### Bug Fixes and Other Changes

 * update distributed GPU utilization warning message
 * set logs to False if wait is False in AutoML
 * workflow passing spot training param to training job

## v2.0.0.rc0 (2020-06-17)

### Breaking Changes

 * remove estimator parameters for TF legacy mode
 * remove legacy `TensorFlowModel` and `TensorFlowPredictor` classes
 * force image URI to be passed for legacy TF images
 * rename `sagemaker.tensorflow.serving` to `sagemaker.tensorflow.model`
 * require `framework_version` and `py_version` for framework estimator and model classes
 * change `Model` parameter order to make `model_data` optional

### Bug Fixes and Other Changes

 * add v2 migration tool

### Documentation Changes

 * update TF documentation to reflect breaking changes and how to upgrade
 * start v2 usage and migration documentation

### Testing and Release Infrastructure

 * remove scipy from dependencies
 * remove TF from optional dependencies

## v1.64.1 (2020-06-16)

### Bug Fixes and Other Changes

 * include py38 tox env and some dependency upgrades

## v1.64.0 (2020-06-15)

### Features

 * add support for SKLearn 0.23

## v1.63.0 (2020-06-12)

### Features

 * Allow selecting inference response content for automl generated models
 * Support for multi variant endpoint invocation with target variant param

### Documentation Changes

 * improve docstring and remove unavailable links

## v1.62.0 (2020-06-11)

### Features

 * Support for multi variant endpoint invocation with target variant param

### Bug Fixes and Other Changes

 * Revert "feature: Support for multi variant endpoint invocation with target variant param (#1571)"
 * make instance_type optional for prepare_container_def
 * docs: workflows navigation

### Documentation Changes

 * fix typo in MXNet documentation

## v1.61.0 (2020-06-09)

### Features

 * Use boto3 DEFAULT_SESSION when no boto3 session specified.

### Bug Fixes and Other Changes

 * remove v2 Session warnings
 * upgrade smdebug-rulesconfig to 0.1.4
 * explicitly handle arguments in create_model for sklearn and xgboost

## v1.60.2 (2020-05-29)

### Bug Fixes and Other Changes

 * [doc] Added Amazon Components for Kubeflow Pipelines

## v1.60.1.post0 (2020-05-28)

### Documentation Changes

 * clarify that entry_point must be in the root of source_dir (if applicable)

## v1.60.1 (2020-05-27)

### Bug Fixes and Other Changes

 * refactor the navigation

### Documentation Changes

 * fix undoc directive; removes extra tabs

## v1.60.0.post0 (2020-05-26)

### Documentation Changes

 * remove some duplicated documentation from main README
 * fix TF requirements.txt documentation

## v1.60.0 (2020-05-25)

### Features

 * support TensorFlow training 2.2

### Bug Fixes and Other Changes

 * blacklist unknown xgboost image versions
 * use format strings instead of os.path.join for S3 URI in S3Downloader

### Documentation Changes

 * consolidate framework version and image information

## v1.59.0 (2020-05-21)

### Features

 * MXNet elastic inference support

### Bug Fixes and Other Changes

 * add Batch Transform data processing options to Airflow config
 * add v2 warning messages
 * don't try to use local output path for KMS key in Local Mode

### Documentation Changes

 * add instructions for how to enable 'local code' for Local Mode

## v1.58.4 (2020-05-20)

### Bug Fixes and Other Changes

 * update AutoML default max_candidate value to use the service default
 * add describe_transform_job in session class

### Documentation Changes

 * clarify support for requirements.txt in Tensorflow docs

### Testing and Release Infrastructure

 * wait for DisassociateTrialComponent to take effect in experiment integ test cleanup

## v1.58.3 (2020-05-19)

### Bug Fixes and Other Changes

 * update DatasetFormat key name for sagemakerCaptureJson

### Documentation Changes

 * update Processing job max_runtime_in_seconds docstring

## v1.58.2.post0 (2020-05-18)

### Documentation Changes

 * specify S3 source_dir needs to point to a tar file
 * update PyTorch BYOM topic

## v1.58.2 (2020-05-13)

### Bug Fixes and Other Changes

 * address flake8 error

## v1.58.1 (2020-05-11)

### Bug Fixes and Other Changes

 * upgrade boto3 to 1.13.6

## v1.58.0 (2020-05-08)

### Features

 * support inter container traffic encryption for processing jobs

### Documentation Changes

 * add note that v2.0.0 plans have been posted

## v1.57.0 (2020-05-07)

### Features

 * add tensorflow training 1.15.2 py37 support
 * PyTorch 1.5.0 support

## v1.56.3 (2020-05-06)

### Bug Fixes and Other Changes

 * update xgboost latest image version

## v1.56.2 (2020-05-05)

### Bug Fixes and Other Changes

 * training_config returns MetricDefinitions
 * preserve inference script in model repack.

### Testing and Release Infrastructure

 * support Python 3.7

## v1.56.1.post1 (2020-04-29)

### Documentation Changes

 * document model.tar.gz structure for MXNet and PyTorch
 * add documentation for EstimatorBase parameters missing from docstring

## v1.56.1.post0 (2020-04-28)

### Testing and Release Infrastructure

 * add doc8 check for documentation files

## v1.56.1 (2020-04-27)

### Bug Fixes and Other Changes

 * add super() call in Local Mode DataSource subclasses
 * fix xgboost image incorrect latest version warning
 * allow output_path without trailing slash in Local Mode training jobs
 * allow S3 folder input to contain a trailing slash in Local Mode

### Documentation Changes

 * Add namespace-based setup for SageMaker Operators for Kubernetes
 * Add note about file URLs for Estimator methods in Local Mode

## v1.56.0 (2020-04-24)

### Features

 * add EIA support for TFS 1.15.0 and 2.0.0

### Bug Fixes and Other Changes

 * use format strings intead of os.path.join for Unix paths for Processing Jobs

## v1.55.4 (2020-04-17)

### Bug Fixes and Other Changes

 * use valid encryption key arg for S3 downloads
 * update sagemaker pytorch containers to external link
 * allow specifying model name when creating a Transformer from an Estimator
 * allow specifying model name in create_model() for TensorFlow, SKLearn, and XGBoost
 * allow specifying model name in create_model() for Chainer, MXNet, PyTorch, and RL

### Documentation Changes

 * fix wget endpoints
 * add Adobe Analytics; upgrade Sphinx and docs environment
 * Explain why default model_fn loads PyTorch-EI models to CPU by default
 * Set theme in conf.py
 * correct transform()'s wait default value to "False"

### Testing and Release Infrastructure

 * move unit tests for updating an endpoint to test_deploy.py
 * move Neo unit tests to a new file and directly use the Model class
 * move Model.deploy unit tests to separate file
 * add Model unit tests for delete_model and enable_network_isolation
 * skip integ tests in PR build if only unit tests are modified
 * add Model unit tests for prepare_container_def and _create_sagemaker_model
 * use Model class for model deployment unit tests
 * split model unit tests by Model, FrameworkModel, and ModelPackage
 * add Model unit tests for all transformer() params
 * add TF batch transform integ test with KMS and network isolation
 * use pytest fixtures in batch transform integ tests to train and upload to S3 only once
 * improve unit tests for creating Transformers and transform jobs
 * add PyTorch + custom model bucket batch transform integ test

## v1.55.3 (2020-04-08)

### Bug Fixes and Other Changes

 * remove .strip() from batch transform
 * allow model with network isolation when creating a Transformer from an Estimator
 * add enable_network_isolation to EstimatorBase

## v1.55.2 (2020-04-07)

### Bug Fixes and Other Changes

 * use .format instead of os.path.join for Processing S3 paths.

### Testing and Release Infrastructure

 * use m5.xlarge instances for "ap-northeast-1" region integ tests.

## v1.55.1 (2020-04-06)

### Bug Fixes and Other Changes

 * correct local mode behavior for CN regions

## v1.55.0.post0 (2020-04-06)

### Documentation Changes

 * fix documentation to provide working example.
 * add documentation for XGBoost
 * Correct comment in SKLearn Estimator about default Python version
 * document inferentia supported version
 * Merge Amazon Sagemaker Operators for Kubernetes and Kubernetes Jobs pages

### Testing and Release Infrastructure

 * turn on warnings as errors for docs builds

## v1.55.0 (2020-03-31)

### Features

 * support cn-north-1 and cn-northwest-1

## v1.54.0 (2020-03-31)

### Features

 * inferentia support

## v1.53.0 (2020-03-30)

### Features

 * Allow setting S3 endpoint URL for Local Session

### Bug Fixes and Other Changes

 * Pass kwargs from create_model to Model constructors
 * Warn if parameter server is used with multi-GPU instance

## v1.52.1 (2020-03-26)

### Bug Fixes and Other Changes

 * Fix local _SageMakerContainer detached mode (aws#1374)

## v1.52.0.post0 (2020-03-25)

### Documentation Changes

 * Add docs for debugger job support in operator

## v1.52.0 (2020-03-24)

### Features

 * add us-gov-west-1 to neo supported regions

## v1.51.4 (2020-03-23)

### Bug Fixes and Other Changes

 * Check that session is a LocalSession when using local mode
 * add tflite to Neo-supported frameworks
 * ignore tags with 'aws:' prefix when creating an EndpointConfig based on an existing one
 * allow custom image when calling deploy or create_model with various frameworks

### Documentation Changes

 * fix description of default model_dir for TF
 * add more details about PyTorch eia

## v1.51.3 (2020-03-12)

### Bug Fixes and Other Changes

 * make repack_model only removes py file when new entry_point provided

## v1.51.2 (2020-03-11)

### Bug Fixes and Other Changes

 * handle empty inputs/outputs in ProcessingJob.from_processing_name()
 * use DLC images for GovCloud

### Testing and Release Infrastructure

 * generate test job name at test start instead of module start

## v1.51.1 (2020-03-10)

### Bug Fixes and Other Changes

 * skip pytorch ei test in unsupported regions

### Documentation Changes

 * correct MultiString/MULTI_STRING docstring

## v1.51.0 (2020-03-09)

### Features

 * pytorch 1.3.1 eia support

### Documentation Changes

 * Update Kubernetes Operator default tag
 * improve docstring for tuner.best_estimator()

## v1.50.18.post0 (2020-03-05)

### Documentation Changes

 * correct Estimator code_location default S3 path

## v1.50.18 (2020-03-04)

### Bug Fixes and Other Changes

 * change default compile model max run to 15 mins

## v1.50.17.post0 (2020-03-03)

### Testing and Release Infrastructure

 * fix PR builds to run on changes to their own buildspecs
 * programmatically determine partition based on region

## v1.50.17 (2020-02-27)

### Bug Fixes and Other Changes

 * upgrade framework versions

## v1.50.16 (2020-02-26)

### Bug Fixes and Other Changes

 * use sagemaker_session when initializing Constraints and Statistics
 * add sagemaker_session parameter to DataCaptureConfig
 * make AutoML.deploy use self.sagemaker_session by default

### Testing and Release Infrastructure

 * unset region during integ tests
 * use sagemaker_session fixture in all Airflow tests
 * remove remaining TF legacy mode integ tests

## v1.50.15 (2020-02-25)

### Bug Fixes and Other Changes

 * enable Neo integ tests

## v1.50.14.post0 (2020-02-24)

### Testing and Release Infrastructure

 * remove TF framework mode notebooks from PR build
 * don't create docker network for all integ tests

## v1.50.14 (2020-02-20)

### Bug Fixes and Other Changes

 * don't use os.path.join for S3 path when repacking TFS model
 * dynamically determine AWS domain based on region

## v1.50.13 (2020-02-19)

### Bug Fixes and Other Changes

 * allow download_folder to download file even if bucket is more restricted

### Testing and Release Infrastructure

 * configure pylint to recognize boto3 and botocore as third-party imports
 * add multiple notebooks to notebook PR build

## v1.50.12 (2020-02-17)

### Bug Fixes and Other Changes

 * enable network isolation for amazon estimators

### Documentation Changes

 * clarify channel environment variables in PyTorch documentation

## v1.50.11 (2020-02-13)

### Bug Fixes and Other Changes

 * fix HyperparameterTuner.attach for Marketplace algorithms
 * move requests library from required packages to test dependencies
 * create Session or LocalSession if not specified in Model

### Documentation Changes

 * remove hardcoded list of target devices in compile()
 * Fix typo with SM_MODEL_DIR, missing quotes

## v1.50.10.post0 (2020-02-12)

### Documentation Changes

 * add documentation guidelines to CONTRIBUTING.md
 * Removed section numbering

## v1.50.10 (2020-02-11)

### Bug Fixes and Other Changes

 * remove NEO_ALLOWED_TARGET_INSTANCE_FAMILY

## v1.50.9.post0 (2020-02-06)

### Documentation Changes

 * remove labels from issue templates

## v1.50.9 (2020-02-04)

### Bug Fixes and Other Changes

 * account for EI and version-based ECR repo naming in serving_image_uri()

### Documentation Changes

 * correct broken AutoML API documentation link
 * fix MXNet version lists

## v1.50.8 (2020-01-30)

### Bug Fixes and Other Changes

 * disable Debugger defaults in unsupported regions
 * modify session and kms_utils to check for S3 bucket before creation
 * update docker-compose and PyYAML dependencies
 * enable smdebug for Horovod (MPI) training setup
 * create lib dir for dependencies safely (only if it doesn't exist yet).
 * create the correct session for MultiDataModel

### Documentation Changes

 * update links to the local mode notebooks examples.
 * Remove outdated badges from README
 * update links to TF notebook examples to link to script mode examples.
 * clean up headings, verb tenses, names, etc. in MXNet overview
 * Update SageMaker operator Helm chart installation guide

### Testing and Release Infrastructure

 * choose faster notebook for notebook PR build
 * properly fail PR build if has-matching-changes fails
 * properly fail PR build if has-matching-changes fails

## v1.50.7 (2020-01-20)

### Bug fixes and other changes

 * do not use script for TFS when entry_point is not provided
 * remove usage of pkg_resources
 * update py2 warning message since python 2 is deprecated
 * cleanup experiments, trials, and trial components in integ tests

## v1.50.6.post0 (2020-01-20)

### Documentation changes

 * add additional information to Transformer class transform function doc string

## v1.50.6 (2020-01-18)

### Bug fixes and other changes

 * Append serving to model framework name for PyTorch, MXNet, and TensorFlow

## v1.50.5 (2020-01-17)

### Bug fixes and other changes

 * Use serving_image_uri for Airflow

### Documentation changes

 * revise Processing docstrings for formatting and class links
 * Add processing readthedocs

## v1.50.4 (2020-01-16)

### Bug fixes and other changes

 * Remove version number from default version comment
 * remove remaining instances of python-dateutil pin
 * upgrade boto3 and remove python-dateutil pin

### Documentation changes

 * Add issue templates and configure issue template chooser
 * Update error type in delete_endpoint docstring
 * add version requirement for using "requirements.txt" when serving an MXNet model
 * update container dependency versions for MXNet and PyTorch
 * Update supported versions of PyTorch

## v1.50.3 (2020-01-15)

### Bug fixes and other changes

 * ignore private Automatic Model Tuning hyperparameter when attaching AlgorithmEstimator

### Documentation changes

 * add Debugger API docs

## v1.50.2 (2020-01-14)

### Bug fixes and other changes

 * add tests to quick canary
 * honor 'wait' flag when updating endpoint
 * add default framework version warning message in Model classes
 * Adding role arn explanation for sagemaker role
 * allow predictor to be returned from AutoML.deploy()
 * add PR checklist item about unique_name_from_base()
 * use unique_name_from_base for multi-algo tuning test
 * update copyright year in license header

### Documentation changes

 * add version requirement for using "requirement.txt" when serving a PyTorch model
 * add SageMaker Debugger overview
 * clarify requirements.txt usage for Chainer, MXNet, and Scikit-learn
 * change "associate" to "create" for OpenID connector
 * fix typo and improve clarity on installing packages via "requirements.txt"

## v1.50.1 (2020-01-07)

### Bug fixes and other changes

 * fix PyTorchModel deployment crash on Windows
 * make PyTorch empty framework_version warning include the latest PyTorch version

## v1.50.0 (2020-01-06)

### Features

 * allow disabling debugger_hook_config

### Bug fixes and other changes

 * relax urllib3 and requests restrictions.
 * Add uri as return statement for upload_string_as_file_body
 * refactor logic in fw_utils and fill in docstrings
 * increase poll from 5 to 30 for DescribeEndpoint lambda.
 * fix test_auto_ml tests for regions without ml.c4.xlarge hosts.
 * fix test_processing for regions without m4.xlarge instances.
 * reduce test's describe frequency to eliminate throttling error.
 * Increase number of retries when describing an endpoint since tf-2.0 has larger images and takes longer to start.

### Documentation changes

 * generalize Model Monitor documentation from SageMaker Studio tutorial

## v1.49.0 (2019-12-23)

### Features

 * Add support for TF-2.0.0.
 * create ProcessingJob from ARN and from name

### Bug fixes and other changes

 * Make tf tests tf-1.15 and tf-2.0 compatible.

### Documentation changes

 * add Model Monitor documentation
 * add link to Amazon algorithm estimator parent class to clarify **kwargs

## v1.48.1 (2019-12-18)

### Bug fixes and other changes

 * use name_from_base in auto_ml.py but unique_name_from_base in tests.
 * make test's custom bucket include region and account name.
 * add Keras to the list of Neo-supported frameworks

### Documentation changes

 * add link to parent classes to clarify **kwargs
 * add link to framework-related parent classes to clarify **kwargs

## v1.48.0 (2019-12-17)

### Features

 * allow setting the default bucket in Session

### Bug fixes and other changes

 * set integration test parallelization to 512
 * shorten base job name to avoid collision
 * multi model integration test to create ECR repo with unique names to allow independent parallel executions

## v1.47.1 (2019-12-16)

### Bug fixes and other changes

 * Revert "feature: allow setting the default bucket in Session (#1168)"

### Documentation changes

 * add AutoML README
 * add missing classes to API docs

## v1.47.0 (2019-12-13)

### Features

 * allow setting the default bucket in Session

### Bug fixes and other changes

 * allow processing users to run code in s3

## v1.46.0 (2019-12-12)

### Features

 * support Multi-Model endpoints

### Bug fixes and other changes

 * update PR template with items about tests, regional endpoints, and API docs

## v1.45.2 (2019-12-10)

### Bug fixes and other changes

 * modify schedule cleanup to abide by latest validations
 * lower log level when getting execution role from a SageMaker Notebook
 * Fix "ValueError: too many values to unpack (expected 2)" is occurred in windows local mode
 * allow ModelMonitor and Processor to take IAM role names (in addition to ARNs)

### Documentation changes

 * mention that the entry_point needs to be named inference.py for tfs

## v1.45.1 (2019-12-06)

### Bug fixes and other changes

 * create auto ml job for tests that based on existing job
 * fixing py2 support for latest TF version
 * fix tags in deploy call for generic estimators
 * make multi algo integration test assertion less specific

## v1.45.0 (2019-12-04)

### Features

 * add support for TF 1.15.0, PyTorch 1.3.1 and MXNet 1.6rc0.
 * add S3Downloader.list(s3_uri) functionality
 * introduce SageMaker AutoML
 * wrap up Processing feature
 * add a few minor features to Model Monitoring
 * add enable_sagemaker_metrics flag
 * Amazon SageMaker Model Monitoring
 * add utils.generate_tensorboard_url function
 * Add jobs list to Estimator

### Bug fixes and other changes

 * remove unnecessary boto model files
 * update boto version to >=1.10.32
 * correct Debugger tests
 * fix bug in monitor.attach() for empty network_config
 * Import smdebug_rulesconfig from PyPI
 * bump the version to 1.45.0 (publishes 1.46.0) for re:Invent-2019
 * correct AutoML imports and expose current_job_name
 * correct Model Monitor eu-west-3 image name.
 * use DLC prod images
 * remove unused env variable for Model Monitoring
 * aws model update
 * rename get_debugger_artifacts to latest_job_debugger_artifacts
 * remove retain flag from update_endpoint
 * correct S3Downloader behavior
 * consume smdebug_ruleconfig .whl for ITs
 * disable DebuggerHook and Rules for TF distributions
 * incorporate smdebug_ruleconfigs pkg until availability in PyPI
 * remove pre/post scripts per latest validations
 * update rules_config .whl
 * remove py_version from SKLearnProcessor
 * AutoML improvements
 * stop overwriting custom rules volume and type
 * fix tests due to latest server-side validations
 * Minor processing changes
 * minor processing changes (instance_count + docs)
 * update api to latest
 * Eureka master
 * Add support for xgboost version 0.90-2
 * SageMaker Debugger revision
 * Add support for SageMaker Debugger [WIP]
 * Fix linear learner crash when num_class is string and predict type is `multiclass_classifier`
 * Additional Processing Jobs integration tests
 * Migrate to updated Processing Jobs API
 * Processing Jobs revision round 2
 * Processing Jobs revision
 * remove instance_pools parameter from tuner
 * Multi-Algorithm Hyperparameter Tuning Support
 * Import Processors in init files
 * Remove SparkML Processors and corresponding unit tests
 * Processing Jobs Python SDK support

## v1.44.4 (2019-12-02)

### Bug fixes and other changes

 * Documentation for Amazon Sagemaker Operators

## v1.44.3 (2019-11-26)

### Bug fixes and other changes

 * move sagemaker config loading to LocalSession since it is only used for local code support.

### Documentation changes

 * fix docstring wording.

## v1.44.2 (2019-11-25)

### Bug fixes and other changes

 * add pyyaml dependencies to the required list.

### Documentation changes

 * Correct info on code_location parameter

## v1.44.1 (2019-11-21)

### Bug fixes and other changes

 * Remove local mode dependencies from required.

## v1.44.0 (2019-11-21)

### Features

 * separating sagemaker dependencies into more use case specific installable components.

### Bug fixes and other changes

 * remove docker-compose as a required dependency.

## v1.43.5 (2019-11-18)

### Bug fixes and other changes

 * remove red from possible colors when streaming logs

## v1.43.4.post1 (2019-10-29)

### Documentation changes

 * clarify that source_dir can be an S3 URI

## v1.43.4.post0 (2019-10-28)

### Documentation changes

 * clarify how to use parameter servers with distributed MXNet training

## v1.43.4 (2019-10-24)

### Bug fixes and other changes

 * use regional endpoint for STS in builds and tests

### Documentation changes

 * update link to point to ReadTheDocs

## v1.43.3 (2019-10-23)

### Bug fixes and other changes

 * exclude regions for P2 tests

## v1.43.2 (2019-10-21)

### Bug fixes and other changes

 * add support for me-south-1 region

## v1.43.1 (2019-10-17)

### Bug fixes and other changes

 * validation args now use default framework_version for TensorFlow

## v1.43.0 (2019-10-16)

### Features

 * Add support for PyTorch 1.2.0

## v1.42.9 (2019-10-14)

### Bug fixes and other changes

 * use default bucket for checkpoint_s3_uri integ test
 * use sts regional endpoint when creating default bucket
 * use us-west-2 endpoint for sts in buildspec
 * take checkpoint_s3_uri and checkpoint_local_path in Framework class

## v1.42.8 (2019-10-10)

### Bug fixes and other changes

 * add kwargs to create_model for 1p to work with kms

## v1.42.7 (2019-10-09)

### Bug fixes and other changes

 * paginating describe log streams

## v1.42.6.post0 (2019-10-07)

### Documentation changes

 * model local mode

## v1.42.6 (2019-10-03)

### Bug fixes and other changes

 * update tfs documentation for requirements.txt
 * support content_type in FileSystemInput
 * allowing account overrides in special regions

## v1.42.5 (2019-10-02)

### Bug fixes and other changes

 * update using_mxnet.rst

## v1.42.4 (2019-10-01)

### Bug fixes and other changes

 * Revert "fix issue-987 error by adding instance_type in endpoint_name (#1058)"
 * fix issue-987 error by adding instance_type in endpoint_name

## v1.42.3 (2019-09-26)

### Bug fixes and other changes

 * preserve EnableNetworkIsolation setting in attach
 * enable kms support for repack_model
 * support binary by NoneSplitter.
 * stop CI unit test code checks from running in parallel

## v1.42.2 (2019-09-25)

### Bug fixes and other changes

 * re-enable airflow_config tests

## v1.42.1 (2019-09-24)

### Bug fixes and other changes

 * lazy import of tensorflow module
 * skip airflow_config tests as they're blocking the release build
 * skip lda tests in regions that does not support it.
 * add airflow_config tests to canaries
 * use correct STS endpoint for us-iso-east-1

## v1.42.0 (2019-09-20)

### Features

 * add estimator preparation to airflow configuration

### Bug fixes and other changes

 * correct airflow workflow for BYO estimators.

## v1.41.0 (2019-09-20)

### Features

 * enable sklearn for network isolation mode

## v1.40.2 (2019-09-19)

### Bug fixes and other changes

 * use new ECR images in us-iso-east-1 for TF and MXNet

## v1.40.1 (2019-09-18)

### Bug fixes and other changes

 * expose kms_key parameter for deploying from training and hyperparameter tuning jobs

### Documentation changes

 * Update sklearn default predict_fn

## v1.40.0 (2019-09-17)

### Features

 * add support to TF 1.14 serving with elastic accelerator.

## v1.39.4 (2019-09-17)

### Bug fixes and other changes

 * pass enable_network_isolation when creating TF and SKLearn models

## v1.39.3 (2019-09-16)

### Bug fixes and other changes

 * expose vpc_config_override in transformer() methods
 * use Estimator.create_model in Estimator.transformer

## v1.39.2 (2019-09-11)

### Bug fixes and other changes

 * pass enable_network_isolation in Estimator.create_model
 * use p2 instead of p3 for the Horovod test

## v1.39.1 (2019-09-10)

### Bug fixes and other changes

 * copy dependencies into new folder when repacking model
 * make get_caller_identity_arn get role from DescribeNotebookInstance
 * add https to regional STS endpoint
 * clean up git support integ tests

## v1.39.0 (2019-09-09)

### Features

 * Estimator.fit like logs for transformer
 * handler for stopping transform job

### Bug fixes and other changes

 * remove hardcoded creds from integ test
 * remove hardcoded creds from integ test
 * Fix get_image_uri warning log for default xgboost version.
 * add enable_network_isolation to generic Estimator class
 * use regional endpoint when creating AWS STS client
 * update Sagemaker Neo regions
 * use cpu_instance_type fixture for stop_transform_job test
 * hyperparameter tuning with spot instances and checkpoints
 * skip efs and fsx integ tests in all regions

### Documentation changes

 * clarify some Local Mode limitations

## v1.38.6 (2019-09-04)

### Bug fixes and other changes

 * update: disable efs fsx integ tests in non-pdx regions
 * fix canary test failure issues
 * use us-east-1 for PR test runs

### Documentation changes

 * updated description for "accept" parameter in batch transform

## v1.38.5 (2019-09-02)

### Bug fixes and other changes

 * clean up resources created by file system set up when setup fails

## v1.38.4 (2019-08-29)

### Bug fixes and other changes

 * skip EFS tests until they are confirmed fixed.

### Documentation changes

 * add note to CONTRIBUTING to clarify automated formatting
 * add checkpoint section to using_mxnet topic

## v1.38.3 (2019-08-28)

### Bug fixes and other changes

 * change AMI ids in tests to be dynamic based on regions

## v1.38.2 (2019-08-27)

### Bug fixes and other changes

 * skip efs tests in non us-west-2 regions
 * refactor tests to use common retry method

## v1.38.1 (2019-08-26)

### Bug fixes and other changes

 * update py2 warning message
 * add logic to use asimov image for TF 1.14 py2

### Documentation changes

 * changed EFS directory path instructions in documentation and Docstrings

## v1.38.0 (2019-08-23)

### Features

 * support training inputs from EFS and FSx

## v1.37.2 (2019-08-20)

### Bug fixes and other changes

 * Add support for Managed Spot Training and Checkpoint support
 * Integration Tests now dynamically checks AZs

## v1.37.1 (2019-08-19)

### Bug fixes and other changes

 * eliminate dependency on mnist dataset website

### Documentation changes

 * refactor using_sklearn and fix minor errors in using_pytorch and using_chainer

## v1.37.0 (2019-08-15)

### Features

 * add XGBoost Estimator as new framework

### Bug fixes and other changes

 * fix tests for new regions
 * add update_endpoint for PipelineModel

### Documentation changes

 * refactor the using Chainer topic

## v1.36.4 (2019-08-13)

### Bug fixes and other changes

 * region build from staging pr

### Documentation changes

 * Refactor Using PyTorch topic for consistency

## v1.36.3 (2019-08-13)

### Bug fixes and other changes

 * fix integration test failures masked by timeout bug
 * prevent multiple values error in sklearn.transformer()
 * model.transformer() passes tags to create_model()

## v1.36.2 (2019-08-12)

### Bug fixes and other changes

 * rework CONTRIBUTING.md to include a development workflow

## v1.36.1 (2019-08-08)

### Bug fixes and other changes

 * prevent integration test's timeout functions from hiding failures

### Documentation changes

 * correct typo in using_sklearn.rst

## v1.36.0 (2019-08-07)

### Features

 * support for TensorFlow 1.14

### Bug fixes and other changes

 * ignore FI18 flake8 rule
 * allow Airflow enabled estimators to use absolute path entry_point

## v1.35.1 (2019-08-01)

### Bug fixes and other changes

 * update sklearn document to include 3p dependency installation

### Documentation changes

 * refactor and edit using_mxnet topic

## v1.35.0 (2019-07-31)

### Features

 * allow serving image to be specified when calling MXNet.deploy

## v1.34.3 (2019-07-30)

### Bug fixes and other changes

 * waiting for training tags to propagate in the test

## v1.34.2 (2019-07-29)

### Bug fixes and other changes

 * removing unnecessary tests cases
 * Replaced generic ValueError with custom subclass when reporting unexpected resource status

### Documentation changes

 * correct wording for Cloud9 environment setup instructions

## v1.34.1 (2019-07-23)

### Bug fixes and other changes

 * enable line-too-long Pylint check
 * improving Chainer integ tests
 * update TensorFlow script mode dependency list
 * improve documentation of some functions
 * update PyTorch version
 * allow serving script to be defined for deploy() and transformer() with frameworks
 * format and add missing docstring placeholders
 * add MXNet 1.4.1 support

### Documentation changes

 * add instructions for setting up Cloud9 environment.
 * update using_tensorflow topic

## v1.34.0 (2019-07-18)

### Features

 * Git integration for CodeCommit
 * deal with credentials for Git support for GitHub

### Bug fixes and other changes

 * modify TODO on disabled Pylint check
 * enable consider-using-ternary Pylint check
 * enable chained-comparison Pylint check
 * enable too-many-public-methods Pylint check
 * enable consider-using-in Pylint check
 * set num_processes_per_host only if provided by user
 * fix attach for 1P algorithm estimators
 * enable ungrouped-imports Pylint check
 * enable wrong-import-order Pylint check
 * enable attribute-defined-outside-init Pylint check
 * enable consider-merging-isinstance Pylint check
 * enable inconsistent-return-statements Pylint check
 * enable simplifiable-if-expression pylint checks
 * fix list serialization for 1P algos
 * enable no-else-return and no-else-raise pylint checks
 * enable unidiomatic-typecheck pylint check

## v1.33.0 (2019-07-10)

### Features

 * git support for hosting models
 * allow custom model name during deploy

### Bug fixes and other changes

 * remove TODO comment on import-error Pylint check
 * enable wrong-import-position pylint check
 * Revert "change: enable wrong-import-position pylint check (#907)"
 * enable signature-differs pylint check
 * enable wrong-import-position pylint check
 * enable logging-not-lazy pylint check
 * reset default output path in Transformer.transform
 * Add ap-northeast-1 to Neo algorithms region map

## v1.32.2 (2019-07-08)

### Bug fixes and other changes

 * enable logging-format-interpolation pylint check
 * remove superfluous parens per Pylint rule

### Documentation changes

 * add pypi, rtd, black badges to readme

## v1.32.1 (2019-07-04)

### Bug fixes and other changes

 * correct code per len-as-condition Pylint check
 * tighten pylint config and expand C and R exceptions
 * Update displaytime.sh
 * fix notebook tests
 * separate unit, local mode, and notebook tests in different buildspecs

### Documentation changes

 * refactor the overview topic in the sphinx project

## v1.32.0 (2019-07-02)

### Features

 * support Endpoint_type for TF transform

### Bug fixes and other changes

 * fix git test in test_estimator.py
 * Add ap-northeast-1 to Neo algorithms region map

## v1.31.1 (2019-07-01)

### Bug fixes and other changes

 * print build execution time
 * remove unnecessary failure case tests
 * build spec improvements.

## v1.31.0 (2019-06-27)

### Features

 * use deep learning images

### Bug fixes and other changes

 * Update buildspec.yml
 * allow only one integration test run per time
 * remove unnecessary P3 tests from TFS integration tests
 * add pytest.mark.local_mode annotation to broken tests

## v1.30.0 (2019-06-25)

### Features

 * add TensorFlow 1.13 support
 * add git_config and git_clone, validate method

### Bug fixes and other changes

 * add pytest.mark.local_mode annotation to broken tests

## v1.29.0 (2019-06-24)

### Features

 * network isolation mode in training

### Bug fixes and other changes

 * Integrate black into development process
 * moving not canary TFS tests to local mode

## v1.28.3 (2019-06-20)

### Bug fixes and other changes

 * update Sagemaker Neo regions and instance families

### Documentation changes

 * fix punctuation in MXNet version list
 * clean up MXNet and TF documentation

## v1.28.2 (2019-06-19)

### Bug fixes and other changes

 * prevent race condition in vpc tests

## v1.28.1 (2019-06-17)

### Bug fixes and other changes

 * Update setup.py

## v1.28.0 (2019-06-17)

### Features

 * Add DataProcessing Fields for Batch Transform

## v1.27.0 (2019-06-11)

### Features

 * add wait argument to estimator deploy

### Bug fixes and other changes

 * fix logger creation in Chainer integ test script

## v1.26.0 (2019-06-10)

### Features

 * emit estimator transformer tags to model
 * Add extra_args to enable encrypted objects upload

### Bug fixes and other changes

 * downgrade c5 in integ tests and test all TF Script Mode images

### Documentation changes

 * include FrameworkModel and ModelPackage in API docs

## v1.25.1 (2019-06-06)

### Bug fixes and other changes

 * use unique job name in hyperparameter tuning test

## v1.25.0 (2019-06-03)

### Features

 * repack_model support dependencies and code location

### Bug fixes and other changes

 * skip p2 tests in ap-south-east
 * add better default transform job name handling within Transformer

### Documentation changes

 * TFS support for pre/processing functions

## v1.24.0 (2019-05-29)

### Features

 * add region check for Neo service

## v1.23.0 (2019-05-27)

### Features

 * support MXNet 1.4 with MMS

### Documentation changes

 * update using_sklearn.rst parameter name

## v1.22.0 (2019-05-23)

### Features

 * add encryption option to "record_set"

### Bug fixes and other changes

 * honor source_dir from S3

## v1.21.2 (2019-05-22)

### Bug fixes and other changes

 * set _current_job_name in attach()
 * emit training jobs tags to estimator

## v1.21.1 (2019-05-21)

### Bug fixes and other changes

 * repack model function works without source directory

## v1.21.0 (2019-05-20)

### Features

 * Support for TFS preprocessing

## v1.20.3 (2019-05-15)

### Bug fixes and other changes

 * run tests if buildspec.yml has been modified
 * skip local file check for TF requirements file when source_dir is an S3 URI

### Documentation changes

 * fix docs in regards to transform_fn for mxnet

## v1.20.2 (2019-05-13)

### Bug fixes and other changes

 * pin pytest version to 4.4.1 to avoid pluggy version conflict

## v1.20.1 (2019-05-09)

### Bug fixes and other changes

 * update TrainingInputMode with s3_input InputMode

## v1.20.0 (2019-05-08)

### Features

 * add RL Ray 0.6.5 support

### Bug fixes and other changes

 * prevent false positive PR test results
 * adjust Ray test script for Ray 0.6.5

## v1.19.1 (2019-05-06)

### Bug fixes and other changes

 * add py2 deprecation message for the deep learning framework images

## v1.19.0 (2019-04-30)

### Features

 * add document embedding support to Object2Vec algorithm

## v1.18.19 (2019-04-30)

### Bug fixes and other changes

 * skip p2/p3 tests in eu-central-1

## v1.18.18 (2019-04-29)

### Bug fixes and other changes

 * add automatic model tuning integ test for TF script mode

## v1.18.17 (2019-04-25)

### Bug fixes and other changes

 * use unique names for test training jobs

## v1.18.16 (2019-04-24)

### Bug fixes and other changes

 * add KMS key option for Endpoint Configs
 * skip p2 test in regions without p2s, freeze urllib3, and specify allow_pickle=True for numpy
 * use correct TF version in empty framework_version warning
 * remove logging level overrides

### Documentation changes

 * add environment setup instructions to CONTRIBUTING.md
 * add clarification around framework version constants
 * remove duplicate content from workflow readme
 * remove duplicate content from RL readme

## v1.18.15 (2019-04-18)

### Bug fixes and other changes

 * fix propagation of tags to SageMaker endpoint

## v1.18.14.post1 (2019-04-17)

### Documentation changes

 * remove duplicate content from Chainer readme

## v1.18.14.post0 (2019-04-15)

### Documentation changes

 * remove duplicate content from PyTorch readme and fix internal links

## v1.18.14 (2019-04-11)

### Bug fixes and other changes

 * make Local Mode export artifacts even after failure

## v1.18.13 (2019-04-10)

### Bug fixes and other changes

 * skip horovod p3 test in region with no p3
 * use unique training job names in TensorFlow script mode integ tests

## v1.18.12 (2019-04-08)

### Bug fixes and other changes

 * add integ test for tagging
 * use unique names for test training jobs
 * Wrap horovod code inside main function
 * add csv deserializer
 * restore notebook test

## v1.18.11 (2019-04-04)

### Bug fixes and other changes

 * local data source relative path includes the first directory
 * upgrade pylint and fix tagging with SageMaker models

### Documentation changes

 * add info about unique job names

## v1.18.10 (2019-04-03)

### Bug fixes and other changes

 * make start time, end time and period configurable in sagemaker.analytics.TrainingJobAnalytics

### Documentation changes

 * fix typo of argument spelling in linear learner docstrings

## v1.18.9.post1 (2019-04-02)

### Documentation changes

 * spelling error correction

## v1.18.9.post0 (2019-04-01)

### Documentation changes

 * move RL readme content into sphinx project

## v1.18.9 (2019-03-28)

### Bug fixes

 * hyperparameter query failure on script mode estimator attached to complete job

### Other changes

 * add EI support for TFS framework

### Documentation changes

 * add third-party libraries sections to using_chainer and using_pytorch topics

## v1.18.8 (2019-03-26)

### Bug fixes

 * fix ECR URI validation
 * remove unrestrictive principal * from KMS policy tests.

### Documentation changes

 * edit description of local mode in overview.rst
 * add table of contents to using_chainer topic
 * fix formatting for HyperparameterTuner.attach()

## v1.18.7 (2019-03-21)

### Other changes

 * add pytest marks for integ tests using local mode
 * add account number and unit tests for govcloud

### Documentation changes

 * move chainer readme content into sphinx and fix broken link in using_mxnet

## v1.18.6.post0 (2019-03-20)

### Documentation changes

 * add mandatory sagemaker_role argument to Local mode example.

## v1.18.6 (2019-03-20)

### Changes

 * enable new release process
 * Update inference pipelines documentation
 * Migrate content from workflow and pytorch readmes into sphinx project
 * Propagate Tags from estimator to model, endpoint, and endpoint config

## 1.18.5

* bug-fix: pass kms id as parameter for uploading code with Server side encryption
* feature: ``PipelineModel``: Create a Transformer from a PipelineModel
* bug-fix: ``AlgorithmEstimator``: Make SupportedHyperParameters optional
* feature: ``Hyperparameter``: Support scaling hyperparameters
* doc-fix: Remove duplicate content from main README.rst, /tensorflow/README.rst, and /sklearn/README.rst and add links to readthedocs content

## 1.18.4

* doc-fix: Remove incorrect parameter for EI TFS Python README
* feature: ``Predictor``: delete SageMaker model
* feature: ``PipelineModel``: delete SageMaker model
* bug-fix: Estimator.attach works with training jobs without hyperparameters
* doc-fix: remove duplicate content from mxnet/README.rst
* doc-fix: move overview content in main README into sphynx project
* bug-fix: pass accelerator_type in ``deploy`` for REST API TFS ``Model``
* doc-fix: move content from tf/README.rst into sphynx project
* doc-fix: move content from sklearn/README.rst into sphynx project
* doc-fix: Improve new developer experience in README
* feature: Add support for Coach 0.11.1 for Tensorflow

## 1.18.3.post1

* doc-fix: fix README for PyPI

## 1.18.3

* doc-fix: update information about saving models in the MXNet README
* doc-fix: change ReadTheDocs links from latest to stable
* doc-fix: add ``transform_fn`` information and fix ``input_fn`` signature in the MXNet README
* feature: add support for ``Predictor`` to delete endpoint configuration by default when calling ``delete_endpoint()``
* feature: add support for ``Model`` to delete SageMaker model
* feature: add support for ``Transformer`` to delete SageMaker model
* bug-fix: fix default account for SKLearnModel

## 1.18.2

* enhancement: Include SageMaker Notebook Instance version number in boto3 user agent, if available.
* feature: Support for updating existing endpoint

## 1.18.1

* enhancement: Add ``tuner`` to imports in ``sagemaker/__init__.py``

## 1.18.0

* bug-fix: Handle StopIteration in CloudWatch Logs retrieval
* feature: Update EI TensorFlow latest version to 1.12
* feature: Support for Horovod

## 1.17.2

* feature: HyperparameterTuner: support VPC config

## 1.17.1

* enhancement: Workflow: Specify tasks from which training/tuning operator to transform/deploy in related operators
* feature: Supporting inter-container traffic encryption flag

## 1.17.0

* bug-fix: Workflow: Revert appending Airflow retry id to default job name
* feature: support for Tensorflow 1.12
* feature: support for Tensorflow Serving 1.12
* bug-fix: Revert appending Airflow retry id to default job name
* bug-fix: Session: don't allow get_execution_role() to return an ARN that's not a role but has "role" in the name
* bug-fix: Remove ``__all__`` from ``__init__.py`` files
* doc-fix: Add TFRecord split type to docs
* doc-fix: Mention ``SM_HPS`` environment variable in MXNet README
* doc-fix: Specify that Local Mode supports only framework and BYO cases
* doc-fix: Add missing classes to API docs
* doc-fix: Add information on necessary AWS permissions
* bug-fix: Remove PyYAML to let docker-compose install the right version
* feature: Update TensorFlow latest version to 1.12
* enhancement: Add Model.transformer()
* bug-fix: HyperparameterTuner: make ``include_cls_metadata`` default to ``False`` for everything except Frameworks

## 1.16.3

* bug-fix: Local Mode: Allow support for SSH in local mode
* bug-fix: Workflow: Append retry id to default Airflow job name to avoid name collisions in retry
* bug-fix: Local Mode: No longer requires s3 permissions to run local entry point file
* feature: Estimators: add support for PyTorch 1.0.0
* bug-fix: Local Mode: Move dependency on sagemaker_s3_output from rl.estimator to model
* doc-fix: Fix quotes in estimator.py and model.py

## 1.16.2

* enhancement: Check for S3 paths being passed as entry point
* feature: Add support for AugmentedManifestFile and ShuffleConfig
* bug-fix: Add version bound for requests module to avoid conflicts with docker-compose and docker-py
* bug-fix: Remove unnecessary dependency tensorflow
* doc-fix: Change ``distribution`` to ``distributions``
* bug-fix: Increase docker-compose http timeout and health check timeout to 120.
* feature: Local Mode: Add support for intermediate output to a local directory.
* bug-fix: Update PyYAML version to avoid conflicts with docker-compose
* doc-fix: Correct the numbered list in the table of contents
* doc-fix: Add Airflow API documentation
* feature: HyperparameterTuner: add Early Stopping support

## 1.16.1.post1

* Documentation: add documentation for Reinforcement Learning Estimator.
* Documentation: update TensorFlow README for Script Mode

## 1.16.1

* feature: update boto3 to version 1.9.55

## 1.16.0

* feature: Add 0.10.1 coach version
* feature: Add support for SageMaker Neo
* feature: Estimators: Add RLEstimator to provide support for Reinforcement Learning
* feature: Add support for Amazon Elastic Inference
* feature: Add support for Algorithm Estimators and ModelPackages: includes support for AWS Marketplace
* feature: Add SKLearn Estimator to provide support for SciKit Learn
* feature: Add Amazon SageMaker Semantic Segmentation algorithm to the registry
* feature: Add support for SageMaker Inference Pipelines
* feature: Add support for SparkML serving container

## 1.15.2

* bug-fix: Fix FileNotFoundError for entry_point without source_dir
* doc-fix: Add missing feature 1.5.0 in change log
* doc-fix: Add README for airflow

## 1.15.1

* enhancement: Local Mode: add explicit pull for serving
* feature: Estimators: dependencies attribute allows export of additional libraries into the container
* feature: Add APIs to export Airflow transform and deploy config
* bug-fix: Allow code_location argument to be S3 URI in training_config API
* enhancement: Local Mode: add explicit pull for serving

## 1.15.0

* feature: Estimator: add script mode and Python 3 support for TensorFlow
* bug-fix: Changes to use correct S3 bucket and time range for dataframes in TrainingJobAnalytics.
* bug-fix: Local Mode: correctly handle the case where the model output folder doesn't exist yet
* feature: Add APIs to export Airflow training, tuning and model config
* doc-fix: Fix typos in tensorflow serving documentation
* doc-fix: Add estimator base classes to API docs
* feature: HyperparameterTuner: add support for Automatic Model Tuning's Warm Start Jobs
* feature: HyperparameterTuner: Make input channels optional
* feature: Add support for Chainer 5.0
* feature: Estimator: add support for MetricDefinitions
* feature: Estimators: add support for Amazon IP Insights algorithm

## 1.14.2

* bug-fix: support ``CustomAttributes`` argument in local mode ``invoke_endpoint`` requests
* enhancement: add ``content_type`` parameter to ``sagemaker.tensorflow.serving.Predictor``
* doc-fix: add TensorFlow Serving Container docs
* doc-fix: fix rendering error in README.rst
* enhancement: Local Mode: support optional input channels
* build: added pylint
* build: upgrade docker-compose to 1.23
* enhancement: Frameworks: update warning for not setting framework_version as we aren't planning a breaking change anymore
* feature: Estimator: add script mode and Python 3 support for TensorFlow
* enhancement: Session: remove hardcoded 'training' from job status error message
* bug-fix: Updated Cloudwatch namespace for metrics in TrainingJobsAnalytics
* bug-fix: Changes to use correct s3 bucket and time range for dataframes in TrainingJobAnalytics.
* enhancement: Remove MetricDefinition lookup via tuning job in TrainingJobAnalytics

## 1.14.1

* feature: Estimators: add support for Amazon Object2Vec algorithm

## 1.14.0

* feature: add support for sagemaker-tensorflow-serving container
* feature: Estimator: make input channels optional

## 1.13.0

* feature: Estimator: add input mode to training channels
* feature: Estimator: add model_uri and model_channel_name parameters
* enhancement: Local Mode: support output_path. Can be either file:// or s3://
* enhancement: Added image uris for SageMaker built-in algorithms for SIN/LHR/BOM/SFO/YUL
* feature: Estimators: add support for MXNet 1.3.0, which introduces a new training script format
* feature: Documentation: add explanation for the new training script format used with MXNet
* feature: Estimators: add ``distributions`` for customizing distributed training with the new training script format

## 1.12.0

* feature: add support for TensorFlow 1.11.0

## 1.11.3

* feature: Local Mode: Add support for Batch Inference
* feature: Add timestamp to secondary status in training job output
* bug-fix: Local Mode: Set correct default values for additional_volumes and additional_env_vars
* enhancement: Local Mode: support nvidia-docker2 natively
* warning: Frameworks: add warning for upcoming breaking change that makes framework_version required

## 1.11.2

* enhancement: Enable setting VPC config when creating/deploying models
* enhancement: Local Mode: accept short lived credentials with a warning message
* bug-fix: Local Mode: pass in job name as parameter for training environment variable

## 1.11.1

* enhancement: Local Mode: add training environment variables for AWS region and job name
* doc-fix: Instruction on how to use preview version of PyTorch - 1.0.0.dev.
* doc-fix: add role to MXNet estimator example in readme
* bug-fix: default TensorFlow json serializer accepts dict of numpy arrays

## 1.11.0

* bug-fix: setting health check timeout limit on local mode to 30s
* bug-fix: make Hyperparameters in local mode optional.
* enhancement: add support for volume KMS key to Transformer
* feature: add support for GovCloud

## 1.10.1

* feature: add train_volume_kms_key parameter to Estimator classes
* doc-fix: add deprecation warning for current MXNet training script format
* doc-fix: add docs on deploying TensorFlow model directly from existing model
* doc-fix: fix code example for using Gzip compression for TensorFlow training data

## 1.10.0

* feature: add support for TensorFlow 1.10.0

## 1.9.3.1

* doc-fix: fix rst warnings in README.rst

## 1.9.3

* bug-fix: Local Mode: Create output/data directory expected by SageMaker Container.
* bug-fix: Estimator accepts the vpc configs made capable by 1.9.1

## 1.9.2

* feature: add support for TensorFlow 1.9

## 1.9.1

* bug-fix: Estimators: Fix serialization of single records
* bug-fix: deprecate enable_cloudwatch_metrics from Framework Estimators.
* enhancement: Enable VPC config in training job creation

## 1.9.0

* feature: Estimators: add support for MXNet 1.2.1

## 1.8.0

* bug-fix: removing PCA from tuner
* feature: Estimators: add support for Amazon k-nearest neighbors(KNN) algorithm

## 1.7.2

* bug-fix: Prediction output for the TF_JSON_SERIALIZER
* enhancement: Add better training job status report

## 1.7.1

* bug-fix: get_execution_role no longer fails if user can't call get_role
* bug-fix: Session: use existing model instead of failing during ``create_model()``
* enhancement: Estimator: allow for different role from the Estimator's when creating a Model or Transformer

## 1.7.0

* feature: Transformer: add support for batch transform jobs
* feature: Documentation: add instructions for using Pipe Mode with TensorFlow

## 1.6.1

* feature: Added multiclass classification support for linear learner algorithm.

## 1.6.0

* feature: Add Chainer 4.1.0 support

## 1.5.4

* feature: Added Docker Registry for all 1p algorithms in amazon_estimator.py
* feature: Added get_image_uri method for 1p algorithms in amazon_estimator.py
* Support SageMaker algorithms in FRA and SYD regions

## 1.5.3

* bug-fix: Can create TrainingJobAnalytics object without specifying metric_names.
* bug-fix: Session: include role path in ``get_execution_role()`` result
* bug-fix: Local Mode: fix RuntimeError handling

## 1.5.2

* Support SageMaker algorithms in ICN region

## 1.5.1

* enhancement: Let Framework models reuse code uploaded by Framework estimators
* enhancement: Unify generation of model uploaded code location
* feature: Change minimum required scipy from 1.0.0 to 0.19.0
* feature: Allow all Framework Estimators to use a custom docker image.
* feature: Option to add Tags on SageMaker Endpoints

## 1.5.0

* feature: Add Support for PyTorch Framework
* feature: Estimators: add support for TensorFlow 1.7.0
* feature: Estimators: add support for TensorFlow 1.8.0
* feature: Allow Local Serving of Models in S3
* enhancement: Allow option for ``HyperparameterTuner`` to not include estimator metadata in job
* bug-fix: Estimators: Join tensorboard thread after fitting

## 1.4.2

* bug-fix: Estimators: Fix attach for LDA
* bug-fix: Estimators: allow code_location to have no key prefix
* bug-fix: Local Mode: Fix s3 training data download when there is a trailing slash

## 1.4.1

* bug-fix: Local Mode: Fix for non Framework containers

## 1.4.0

* bug-fix: Remove __all__ and add noqa in __init__
* bug-fix: Estimators: Change max_iterations hyperparameter key for KMeans
* bug-fix: Estimators: Remove unused argument job_details for ``EstimatorBase.attach()``
* bug-fix: Local Mode: Show logs in Jupyter notebooks
* feature: HyperparameterTuner: Add support for hyperparameter tuning jobs
* feature: Analytics: Add functions for metrics in Training and Hyperparameter Tuning jobs
* feature: Estimators: add support for tagging training jobs

## 1.3.0

* feature: Add chainer

## 1.2.5

* bug-fix: Change module names to string type in __all__
* feature: Save training output files in local mode
* bug-fix: tensorflow-serving-api: SageMaker does not conflict with tensorflow-serving-api module version
* feature: Local Mode: add support for local training data using file://
* feature: Updated TensorFlow Serving api protobuf files
* bug-fix: No longer poll for logs from stopped training jobs

## 1.2.4

* feature: Estimators: add support for Amazon Random Cut Forest algorithm

## 1.2.3

* bug-fix: Fix local mode not using the right s3 bucket

## 1.2.2

* bug-fix: Estimators: fix valid range of hyper-parameter 'loss' in linear learner

## 1.2.1

* bug-fix: Change Local Mode to use a sagemaker-local docker network

## 1.2.0

* feature: Add Support for Local Mode
* feature: Estimators: add support for TensorFlow 1.6.0
* feature: Estimators: add support for MXNet 1.1.0
* feature: Frameworks: Use more idiomatic ECR repository naming scheme

## 1.1.3

* bug-fix: TensorFlow: Display updated data correctly for TensorBoard launched from ``run_tensorboard_locally=True``
* feature: Tests: create configurable ``sagemaker_session`` pytest fixture for all integration tests
* bug-fix: Estimators: fix inaccurate hyper-parameters in kmeans, pca and linear learner
* feature: Estimators: Add new hyperparameters for linear learner.

## 1.1.2

* bug-fix: Estimators: do not call create bucket if data location is provided

## 1.1.1

* feature: Estimators: add ``requirements.txt`` support for TensorFlow

## 1.1.0

* feature: Estimators: add support for TensorFlow-1.5.0
* feature: Estimators: add support for MXNet-1.0.0
* feature: Tests: use ``sagemaker_timestamp`` when creating endpoint names in integration tests
* feature: Session: print out billable seconds after training completes
* bug-fix: Estimators: fix LinearLearner and add unit tests
* bug-fix: Tests: fix timeouts for PCA async integration test
* feature: Predictors: allow ``predictor.predict()`` in the JSON serializer to accept dictionaries

## 1.0.4

* feature: Estimators: add support for Amazon Neural Topic Model(NTM) algorithm
* feature: Documentation: fix description of an argument of sagemaker.session.train
* feature: Documentation: add FM and LDA to the documentation
* feature: Estimators: add support for async fit
* bug-fix: Estimators: fix estimator role expansion

## 1.0.3

* feature: Estimators: add support for Amazon LDA algorithm
* feature: Hyperparameters: add data_type to hyperparameters
* feature: Documentation: update TensorFlow examples following API change
* feature: Session: support multi-part uploads
* feature: add new SageMaker CLI

## 1.0.2

* feature: Estimators: add support for Amazon FactorizationMachines algorithm
* feature: Session: correctly handle TooManyBuckets error_code in default_bucket method
* feature: Tests: add training failure tests for TF and MXNet
* feature: Documentation: show how to make predictions against existing endpoint
* feature: Estimators: implement write_spmatrix_to_sparse_tensor to support any scipy.sparse matrix

## 1.0.1

* api-change: Model: Remove support for 'supplemental_containers' when creating Model
* feature: Documentation: multiple updates
* feature: Tests: ignore tests data in tox.ini, increase timeout for endpoint creation, capture exceptions during endpoint deletion, tests for input-output functions
* feature: Logging: change to describe job every 30s when showing logs
* feature: Session: use custom user agent at all times
* feature: Setup: add travis file

## 1.0.0

* Initial commit