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Xiong Zeng
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‎CHANGELOG.md

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# Changelog
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## v2.212.0 (2024-03-06)
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### Features
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* Update SM Python SDK for PT 2.2.0 SM DLC
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### Bug Fixes and Other Changes
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* Create custom tarfile extractall util to fix backward compatibility issue
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* Upgrade smp to version 2.2
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* Enhance model builder selection logic to include model size
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## v2.211.0 (2024-03-05)
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### Features
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* pin dll version to support python3.11 to the sdk
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* instance specific jumpstart host requirements
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* Add TensorFlow 2.14 image configs
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* Add AutoMLV2 support
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* Support selective pipeline execution between function step and regular step
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* Add new Triton DLC URIs
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### Bug Fixes and Other Changes
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* Skip No Canvas regions for test_deploy_best_candidate
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* make sure gpus are found in local_gpu run
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* Bump Apache Airflow version to 2.8.2
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* properly close sagemaker config file after loading config
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* remove enable_network_isolation from the python doc
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### Documentation Changes
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* Add doc for new feature processor APIs and classes
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## v2.210.0 (2024-02-28)
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### Features
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* Prepend SageMaker Studio App Type to boto3 User Agent string
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* TGI optimum 0.0.18 (general+llm)
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* TGI 1.4.2
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### Bug Fixes and Other Changes
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* tolerate vulnerable old model for integ test and temporarily skip test_list_jumpstart_models_script_filter
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* add missing regions to pytorch config
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* Add validation for sagemaker version on remote job
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* fixed implementation of fail_on_violation for transform with monitoring
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## v2.209.0 (2024-02-24)
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### Features

‎VERSION

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2.209.1.dev0
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2.212.1.dev0

‎doc/api/prep_data/feature_store.rst

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:members:
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:show-inheritance:
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Inputs
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******
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:members:
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:show-inheritance:
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.. autoclass:: sagemaker.feature_store.feature_processor.PySparkDataSource
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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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Feature Processor Scheduler and Triggers
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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.describe
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.. automethod:: sagemaker.feature_store.feature_processor.list_pipelines
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.. automethod:: sagemaker.feature_store.feature_processor.put_trigger
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.. automethod:: sagemaker.feature_store.feature_processor.enable_trigger
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.. automethod:: sagemaker.feature_store.feature_processor.disable_trigger
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.. automethod:: sagemaker.feature_store.feature_processor.delete_trigger
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‎doc/api/training/automlv2.rst

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AutoMLV2
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--------
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.. automodule:: sagemaker.automl.automlv2
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/training/index.rst

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algorithm
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analytics
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automl
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automlv2
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debugger
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estimators
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tuner

‎doc/requirements.txt

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packaging==20.9
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jinja2==3.1.3
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schema==0.7.5
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accelerate>=0.24.1,<=0.27.0

‎requirements/extras/huggingface_requirements.txt

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accelerate>=0.24.1,<=0.27.0

‎requirements/extras/test_requirements.txt

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black==22.3.0
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stopit==1.1.2
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# Update tox.ini to have correct version of airflow constraints file
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apache-airflow==2.8.1
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apache-airflow==2.8.2
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apache-airflow-providers-amazon==7.2.1
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attrs>=23.1.0,<24
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fabric==2.6.0
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onnx==1.14.1
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# tf2onnx==1.15.1
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nbformat>=5.9,<6
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accelerate>=0.24.1,<=0.27.0

‎setup.py

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"feature-processor": read_requirements(
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"requirements/extras/feature-processor_requirements.txt"
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),
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"huggingface": read_requirements("requirements/extras/huggingface_requirements.txt"),
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}
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# Meta dependency groups
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extras["all"] = [item for group in extras.values() for item in group]

‎src/sagemaker/__init__.py

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from sagemaker.automl.automl import AutoML, AutoMLJob, AutoMLInput # noqa: F401
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from sagemaker.automl.candidate_estimator import CandidateEstimator, CandidateStep # noqa: F401
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from sagemaker.automl.automlv2 import ( # noqa: F401
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AutoMLV2,
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AutoMLJobV2,
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LocalAutoMLDataChannel,
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AutoMLDataChannel,
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AutoMLTimeSeriesForecastingConfig,
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AutoMLImageClassificationConfig,
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AutoMLTabularConfig,
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AutoMLTextClassificationConfig,
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AutoMLTextGenerationConfig,
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)
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from sagemaker.debugger import ProfilerConfig, Profiler # noqa: F401
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