v1.46.0

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

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

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

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

Bug fixes and other changes

• Documentation for Amazon Sagemaker Operators

v1.44.3

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

Bug fixes and other changes

• add pyyaml dependencies to the required list.

Documentation changes

• Correct info on code_location parameter

v1.44.1

Bug fixes and other changes

• Remove local mode dependencies from required.

v1.44.0

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

Bug fixes and other changes

• remove red from possible colors when streaming logs