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‎CHANGELOG.md

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# Changelog
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## v2.196.0 (2023-10-27)
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### Features
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* inference instance type conditioned on training instance type
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### Bug Fixes and Other Changes
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* improved jumpstart tagging
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## v2.195.1 (2023-10-26)
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### Bug Fixes and Other Changes
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* Allow either instance_type or instance_group to be defined in…
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* enhance image_uris unit tests
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## v2.195.0 (2023-10-25)
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### Features
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* jumpstart gated model artifacts
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* jumpstart extract generated text from response
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* jumpstart contruct payload utility
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### Bug Fixes and Other Changes
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* relax upper bound on urllib in local mode requirements
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* bump urllib3 version
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* allow smdistributed to be enabled with torch_distributed.
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* fix URL links
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### Documentation Changes
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* remove python 2 reference
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* update framework version links
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## v2.194.0 (2023-10-19)
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### Features
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* Added register step in Jumpstart model
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* jumpstart instance specific metric definitions
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### Bug Fixes and Other Changes
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* Updates for DJL 0.24.0 Release
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* use getter for resource-metadata dict
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* add method to Model class to check if repack is needed
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## v2.193.0 (2023-10-18)
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### Features
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* jumpstart model artifact instance type variants
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* jumpstart instance specific hyperparameters
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* Feature Processor event based triggers (#1132)
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* Support job checkpoint in remote function
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* jumpstart model package arn instance type variants
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### Bug Fixes and Other Changes
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* Fix hyperlinks in feature_processor.scheduler parameter descriptions
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* add image_uris_unit_test pytest mark
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* bump apache-airflow to `v2.7.2`
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* clone distribution in validate_distribution
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* fix flaky Inference Recommender integration tests
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### Documentation Changes
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* Update PipelineModel.register documentation
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* specify that input_shape in no longer required for torch 2.0 mod…
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## v2.192.1 (2023-10-13)
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### Bug Fixes and Other Changes
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* update local mode schema
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* import error in unsupported js regions
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* Update Ec2 instance type to g5.4xlarge in test_huggingface_torch_distributed.py
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## v2.192.0 (2023-10-11)
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### Features
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* jumpstart estimator enable infra check flag
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* jumpstart default payloads
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* allow non-python files in job dependencies
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* allow configuring docker container in local mode
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### Bug Fixes and Other Changes
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* js tagging s3 prefix
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* Batch transform: Add support for split_type == "None" in local mode
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* use correct line endings and s3 uris on windows
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* Fixed bug in _create_training_details
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* DJL Neuronx 0.24.0
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### Documentation Changes
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* Include FeatureGroup's load_feature_definitions API documentation
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## v2.191.0 (2023-10-05)
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### Features
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* Selective Step Execution milestone 2 features
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* feature-processor extra data sources support
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## v2.190.0 (2023-10-04)
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### Features
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* Add support for in-memory feature groups and collection type features in Feature Store.
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### Bug Fixes and Other Changes
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* chore: xfail resource in use failure for specific test
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* Add missing API docs for processors
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### Documentation Changes
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* Bring back (de)serializers documentation
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* Add missing AirFlow operators + link to airflow documentation
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## v2.189.0 (2023-10-03)
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### Features
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* add feature processor APIs to public doc
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* s3 prefix model data for JumpStartModel
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* Model Package support for updating approval
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### Bug Fixes and Other Changes
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* Add bucket owner check
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* transform step unit test
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* Release TGI 1.1.0 Image
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## v2.188.0 (2023-09-26)
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### Features

‎VERSION

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2.188.1.dev0
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2.196.1.dev0

‎doc/amazon_sagemaker_featurestore.rst

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    enable_online_store=True
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)
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Creating a feature group takes time as the data is loaded. You will need
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to wait until it is created before you can use it. You can check status
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using the following method.
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Creating a feature group takes time as the data is loaded. You will
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need to wait until it is created before you can use it. You can
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check status using the following method. Note that it can take
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approximately 10-15 minutes to provision an online ``FeatureGroup``
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with the ``InMemory`` ``StorageType``.
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.. code:: python
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.. rubric:: Delete a feature group
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:name: bCe9CA61b78
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You can delete a feature group with the ``delete`` function.
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You can delete a feature group with the ``delete`` function. Note that it
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can take approximately 10-15 minutes to delete an online ``FeatureGroup``
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with the ``InMemory`` ``StorageType``.
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.. code:: python
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‎doc/api/inference/deserializers.rst

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Deserializers
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-------------
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.. automodule:: sagemaker.deserializers
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.. automodule:: sagemaker.base_deserializers
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:members:
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:undoc-members:
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:show-inheritance:
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.. automodule:: sagemaker.deserializers
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/inference/serializers.rst

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Serializers
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-----------
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.. automodule:: sagemaker.base_serializers
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.. automodule:: sagemaker.serializers
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/prep_data/feature_store.rst

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.. autoclass:: sagemaker.feature_store.feature_group.FeatureGroup
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:exclude-members: load_feature_definitions
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.. autoclass:: sagemaker.feature_store.feature_definition.CollectionTypeEnum
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:members:
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.feature_definition.CollectionType
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.feature_definition.ListCollectionType
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.feature_definition.SetCollectionType
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.feature_definition.VectorCollectionType
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.inputs.OnlineStoreStorageTypeEnum
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@feature_processor Decorator
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****************************
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.. autodecorator:: sagemaker.feature_store.feature_processor.feature_processor
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Feature Processor Data Source
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*****************************
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.. autoclass:: sagemaker.feature_store.feature_processor.FeatureGroupDataSource
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:members:
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.feature_processor.CSVDataSource
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:members:
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.feature_processor.ParquetDataSource
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:members:
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:show-inheritance:
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Feature Processor Scheduler
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***************************
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.. automethod:: sagemaker.feature_store.feature_processor.to_pipeline
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.. automethod:: sagemaker.feature_store.feature_processor.schedule
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.. automethod:: sagemaker.feature_store.feature_processor.execute
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.. automethod:: sagemaker.feature_store.feature_processor.delete_schedule
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.. automethod:: sagemaker.feature_store.feature_processor.describe
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.. automethod:: sagemaker.feature_store.feature_processor.list_pipelines

‎doc/conf.py

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autodoc_mock_imports = ["pyspark", "feature_store_pyspark", "py4j"]
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sys.stdout.write("Generating JumpStart model table...")

‎doc/frameworks/huggingface/sagemaker.huggingface.rst

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Hugging Face Processor
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----------------------
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.. autoclass:: sagemaker.huggingface.processing.HuggingFaceProcessor
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‎doc/frameworks/mxnet/sagemaker.mxnet.rst

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MXNet Estimator
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MXNet Processor
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‎doc/frameworks/pytorch/sagemaker.pytorch.rst

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‎doc/frameworks/tensorflow/sagemaker.tensorflow.rst

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