hc99's picture
Add files using upload-large-folder tool
476455e verified
# Changelog
## 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