# Changelog ## 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