SageMaker Python SDK 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

SageMaker Python SDK 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

SageMaker Python SDK 1.4.2

• bug-fix: Unit Tests: Improve unit test runtime
• 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

SageMaker Python SDK 1.4.1

• bug-fix: Local Mode: Fix for non Framework containers

SageMaker Python SDK 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

SageMaker Python SDK 1.3.0

• feature: add chainer

SageMaker Python SDK 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

SageMaker Python SDK 1.2.4

• feature: Estimators: add support for Amazon Random Cut Forest algorithm

SageMaker Python SDK 1.2.3

1.2.3

• bug-fix: Fix local mode not using the right s3 bucket

SageMaker Python SDK v1.2.2

1.2.2

• bug-fix: Estimators: fix valid range of hyper-parameter 'loss' in linear learner