merge from base repo #1
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* image -> image_uri * train_instance_count -> instance_count * train_instance_type -> instance_type * train_max_run -> max_run * train_max_run_wait -> max_run_wait * train_volume_size -> volume_size * sagemaker.session.s3_input -> sagemaker.inputs.TrainingInput
get_image_uri -> sagemaker.image_uris.retrieve()
* Removed sagemaker_session for SKLearn * Moved checkpoint_path into hyper parameters (https://sagemaker.readthedocs.io/en/v2.0.0.rc0/frameworks/tensorflow/upgrade_from_legacy.html) * Added framework_version and py_version * Update entry_point and renamed image_name to image_uri for TensorFlow
The TuningStep Class is not exposed, making it not possible to import like other steps. e.g. `from stepfunctions.steps import TuningStep`
Fixing failing integ test due to new DescribeExecution response params
Expose TuningStep from SageMaker steps
…teps, fix Rule evaluator image, and instance count/type
Bumping version to 1.1.2
fix: Upgrade to SageMaker v2 SDK
Sunset Python 2 support for SDK v2
…science-sdk-python
[Feature]: Support new ASL choice comparators
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