Sagemaker

Bug fixes and other changes

* ignore private Automatic Model Tuning hyperparameter when attaching AlgorithmEstimator

Documentation changes

* add Debugger API docs

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"

Bug fixes and other changes

* fix PyTorchModel deployment crash on Windows
* make PyTorch empty framework_version warning include the latest PyTorch version

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

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

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