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.github/workflows/codeql.yml

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name: "CodeQL"
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on:
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push:
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branches: [ "master" ]
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pull_request:
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branches: [ "master" ]
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schedule:
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- cron: '30 8 * * *'
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jobs:
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analyze:
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name: Analyze (${{ matrix.language }})
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runs-on: ${{ 'ubuntu-latest' }}
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permissions:
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security-events: write
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packages: read
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strategy:
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matrix:
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include:
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- language: python
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build-mode: none
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- language: java-kotlin
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build-mode: none
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steps:
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- name: Checkout repository
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uses: actions/checkout@6ccd57f4c5d15bdc2fef309bd9fb6cc9db2ef1c6
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- name: Initialize CodeQL
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uses: github/codeql-action/init@4b1d7da102ff94aca014c0245062b1a463356d72
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with:
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languages: ${{ matrix.language }}
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build-mode: ${{ matrix.build-mode }}
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- name: Perform CodeQL Analysis
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uses: github/codeql-action/analyze@4b1d7da102ff94aca014c0245062b1a463356d72
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with:
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category: "/language:${{matrix.language}}"

CHANGELOG.md

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# Changelog
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## v2.226.1 (2024-07-17)
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## v2.226.0 (2024-07-12)
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### Features
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* Curated hub improvements
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* InferenceSpec support for MMS and testing
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### Bug Fixes and Other Changes
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* ModelBuilder not passing HF_TOKEN to model.
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* update image_uri_configs 07-10-2024 07:18:04 PST
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## v2.225.0 (2024-07-10)
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### Features
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* model optimization
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### Bug Fixes and Other Changes
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* fix integ test
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* update uris for v1.1.1
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* update image_uri_configs 07-04-2024 07:17:24 PST
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## v2.224.4 (2024-07-04)
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### Bug Fixes and Other Changes
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* allow for inf spec and server override to be passed
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## v2.224.3 (2024-07-03)
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### Bug Fixes and Other Changes
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* Upgrade local dependencies
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* Improve docstrings for estimator tags
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## v2.224.2 (2024-06-27)
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### Bug Fixes and Other Changes

VERSION

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2.224.3.dev0
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2.226.2.dev0
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urllib3>=1.26.8,<3.0.0
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docker>=5.0.2,<7.0.0
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docker>=5.0.2,<8.0.0
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PyYAML>=5.4.1,<7

requirements/extras/test_requirements.txt

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schema==0.7.5
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tensorflow>=2.1,<=2.16
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mlflow>=2.12.2,<2.13
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huggingface_hub>=0.23.4

setup.py

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# Declare minimal set for installation
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required_packages = [
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"attrs>=23.1.0,<24",
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"boto3>=1.33.3,<2.0",
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"boto3>=1.34.142,<2.0",
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"cloudpickle==2.2.1",
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"google-pasta",
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"numpy>=1.9.0,<2.0",

src/sagemaker/accept_types.py

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tolerate_deprecated_model: bool = False,
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sagemaker_session: Session = DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
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model_type: JumpStartModelType = JumpStartModelType.OPEN_WEIGHTS,
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config_name: Optional[str] = None,
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) -> str:
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"""Retrieves the default accept type for the model matching the given arguments.
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object, used for SageMaker interactions. If not
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specified, one is created using the default AWS configuration
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chain. (Default: sagemaker.jumpstart.constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION).
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config_name (Optional[str]): Name of the JumpStart Model config to apply. (Default: None).
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Returns:
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str: The default accept type to use for the model.
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tolerate_deprecated_model=tolerate_deprecated_model,
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sagemaker_session=sagemaker_session,
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model_type=model_type,
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config_name=config_name,
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)

src/sagemaker/content_types.py

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tolerate_deprecated_model: bool = False,
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sagemaker_session: Session = DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
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model_type: JumpStartModelType = JumpStartModelType.OPEN_WEIGHTS,
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config_name: Optional[str] = None,
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) -> str:
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"""Retrieves the default content type for the model matching the given arguments.
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object, used for SageMaker interactions. If not
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specified, one is created using the default AWS configuration
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chain. (Default: sagemaker.jumpstart.constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION).
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config_name (Optional[str]): Name of the JumpStart Model config to apply. (Default: None).
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Returns:
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str: The default content type to use for the model.
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tolerate_deprecated_model=tolerate_deprecated_model,
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sagemaker_session=sagemaker_session,
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model_type=model_type,
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config_name=config_name,
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)
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src/sagemaker/deserializers.py

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tolerate_deprecated_model: bool = False,
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sagemaker_session: Session = DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
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model_type: JumpStartModelType = JumpStartModelType.OPEN_WEIGHTS,
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config_name: Optional[str] = None,
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) -> BaseDeserializer:
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"""Retrieves the default deserializer for the model matching the given arguments.
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object, used for SageMaker interactions. If not
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specified, one is created using the default AWS configuration
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chain. (Default: sagemaker.jumpstart.constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION).
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config_name (Optional[str]): Name of the JumpStart Model config to apply. (Default: None).
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BaseDeserializer: The default deserializer to use for the model.
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tolerate_deprecated_model=tolerate_deprecated_model,
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sagemaker_session=sagemaker_session,
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model_type=model_type,
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config_name=config_name,
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)

src/sagemaker/enums.py

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"""The endpoint routes requests to the specific instances that have
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more capacity to process them.
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"""
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class Tag(str, Enum):
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"""Enum class for tag keys to apply to models."""
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OPTIMIZATION_JOB_NAME = "sagemaker-sdk:optimization-job-name"
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SPECULATIVE_DRAFT_MODEL_PROVIDER = "sagemaker-sdk:speculative-draft-model-provider"
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FINE_TUNING_MODEL_PATH = "sagemaker-sdk:fine-tuning-model-path"
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FINE_TUNING_JOB_NAME = "sagemaker-sdk:fine-tuning-job-name"

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