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Releases: aws/sagemaker-python-sdk

v1.49.0

23 Dec 17:38

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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

18 Dec 17:39

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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

17 Dec 17:39

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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

16 Dec 20:08

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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

v1.46.0

12 Dec 17:39

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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

10 Dec 17:38

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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

06 Dec 03:37

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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

04 Dec 04:37

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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

02 Dec 06:02

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Bug fixes and other changes

  • Documentation for Amazon Sagemaker Operators

v1.44.3

26 Nov 07:03

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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.