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Releases: aws/sagemaker-python-sdk

SageMaker Python SDK 1.15.2

22 Nov 03:45
d8c055b
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  • bug-fix: Fix FileNotFoundError for entry_point without source_dir
  • doc-fix: Add missing feature 1.5.0 in change log
  • doc-fix: Add README for airflow

SageMaker Python SDK 1.15.1

20 Nov 03:15
9c27fd9
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  • enhancement: Local Mode: add explicit pull for serving
  • feature: Estimators: dependencies attribute allows export of additional libraries into the container
  • feature: Add APIs to export Airflow transform and deploy config
  • bug-fix: Allow code_location argument to be S3 URI in training_config API
  • enhancement: Local Mode: add explicit pull for serving

SageMaker Python SDK 1.15.0

16 Nov 21:44
e37ac12
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  • bug-fix: Changes to use correct S3 bucket and time range for dataframes in TrainingJobAnalytics.
  • bug-fix: Local Mode: correctly handle the case where the model output folder doesn't exist yet
  • feature: Add APIs to export Airflow training, tuning and model config
  • doc-fix: Fix typos in tensorflow serving documentation
  • doc-fix: Add estimator base classes to API docs
  • feature: HyperparameterTuner: add support for Automatic Model Tuning's Warm Start Jobs
  • feature: HyperparameterTuner: Make input channels optional
  • feature: Add support for Chainer 5.0
  • feature: Estimator: add support for MetricDefinitions
  • feature: Estimators: add support for Amazon IP Insights algorithm

SageMaker Python SDK 1.14.2

14 Nov 00:07
49912ff
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  • bug-fix: support CustomAttributes argument in local mode invoke_endpoint requests
  • enhancement: add content_type parameter to sagemaker.tensorflow.serving.Predictor
  • doc-fix: add TensorFlow Serving Container docs
  • doc-fix: fix rendering error in README.rst
  • enhancement: Local Mode: support optional input channels
  • build: added pylint
  • build: upgrade docker-compose to 1.23
  • enhancement: Frameworks: update warning for not setting framework_version as we aren't planning a breaking change anymore
  • enhancement: Session: remove hardcoded 'training' from job status error message
  • bug-fix: Updated Cloudwatch namespace for metrics in TrainingJobsAnalytics

SageMaker Python SDK 1.14.1

08 Nov 19:11
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  • feature: Estimators: add support for Amazon Object2Vec algorithm

SageMaker Python SDK 1.14.0

07 Nov 20:34
8d76437
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  • feature: add support for sagemaker-tensorflow-serving container
  • feature: Estimator: make input channels optional

SageMaker Python SDK 1.13.0

05 Nov 22:02
868f81b
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  • feature: Estimator: add input mode to training channels
  • feature: Estimator: add model_uri and model_channel_name parameters
  • enhancement: Local Mode: support output_path. Can be either file:// or s3://
  • enhancement: Added image uris for SageMaker built-in algorithms for SIN/LHR/BOM/SFO/YUL
  • feature: Estimators: add support for MXNet 1.3.0, which introduces a new training script format
  • feature: Documentation: add explanation for the new training script format used with MXNet
  • feature: Estimators: add distributions for customizing distributed training with the new training script format

SageMaker Python SDK 1.12.0

26 Oct 01:10
a5595af
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  • feature: add support for TensorFlow 1.11.0

SageMaker Python SDK 1.11.3

16 Oct 21:47
08bacf6
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  • feature: Local Mode: Add support for Batch Inference
  • feature: Add timestamp to secondary status in training job output
  • bug-fix: Local Mode: Set correct default values for additional_volumes and additional_env_vars
  • enhancement: Local Mode: support nvidia-docker2 natively
  • warning: Frameworks: add warning for upcoming breaking change that makes framework_version required

SageMaker Python SDK 1.11.2

10 Oct 19:38
80ba921
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  • enhancement: Enable setting VPC config when creating/deploying models
  • enhancement: Local Mode: accept short lived credentials with a warning message
  • bug-fix: Local Mode: pass in job name as parameter for training environment variable