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‎CHANGELOG.md

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# Changelog
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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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2.225.1.dev0

‎requirements/extras/local_requirements.txt

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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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@@ -38,3 +38,4 @@ accelerate>=0.24.1,<=0.27.0
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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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@@ -49,7 +49,7 @@ def read_requirements(filename):
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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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@@ -82,6 +82,7 @@ def retrieve_default(
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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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@@ -125,4 +127,5 @@ def retrieve_default(
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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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@@ -82,6 +82,7 @@ def retrieve_default(
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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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@@ -125,6 +127,7 @@ def retrieve_default(
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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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@@ -102,6 +102,7 @@ def retrieve_default(
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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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Returns:
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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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@@ -40,3 +40,12 @@ class RoutingStrategy(Enum):
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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"

‎src/sagemaker/environment_variables.py

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@@ -37,6 +37,7 @@ def retrieve_default(
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sagemaker_session: Session = DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
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instance_type: Optional[str] = None,
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script: JumpStartScriptScope = JumpStartScriptScope.INFERENCE,
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config_name: Optional[str] = None,
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) -> Dict[str, str]:
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"""Retrieves the default container environment variables for the model matching the arguments.
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variables specific for the instance type.
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script (JumpStartScriptScope): The JumpStart script for which to retrieve environment
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variables.
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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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dict: The variables to use for the model.
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sagemaker_session=sagemaker_session,
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instance_type=instance_type,
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script=script,
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config_name=config_name,
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)

‎src/sagemaker/huggingface/llm_utils.py

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"""Functions for generating ECR image URIs for pre-built SageMaker Docker images."""
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from __future__ import absolute_import
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import os
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from typing import Optional
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import importlib.util
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import urllib.request
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from urllib.error import HTTPError, URLError
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"Did not find model metadata for the following HuggingFace Model ID %s" % model_id
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)
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return hf_model_metadata_json
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def download_huggingface_model_metadata(
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model_id: str, model_local_path: str, hf_hub_token: Optional[str] = None
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) -> None:
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"""Downloads the HuggingFace Model snapshot via HuggingFace API.
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Args:
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model_id (str): The HuggingFace Model ID
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model_local_path (str): The local path to save the HuggingFace Model snapshot.
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hf_hub_token (str): The HuggingFace Hub Token
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Raises:
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ImportError: If huggingface_hub is not installed.
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"""
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if not importlib.util.find_spec("huggingface_hub"):
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raise ImportError("Unable to import huggingface_hub, check if huggingface_hub is installed")
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from huggingface_hub import snapshot_download
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os.makedirs(model_local_path, exist_ok=True)
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logger.info("Downloading model %s from Hugging Face Hub to %s", model_id, model_local_path)
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snapshot_download(repo_id=model_id, local_dir=model_local_path, token=hf_hub_token)

‎src/sagemaker/hyperparameters.py

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tolerate_vulnerable_model: bool = False,
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tolerate_deprecated_model: bool = False,
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sagemaker_session: Session = DEFAULT_JUMPSTART_SAGEMAKER_SESSION,
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config_name: Optional[str] = None,
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) -> Dict[str, str]:
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"""Retrieves the default training hyperparameters for the model matching the given arguments.
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object, used for SageMaker interactions. If not
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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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dict: The hyperparameters to use for the model.
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tolerate_vulnerable_model=tolerate_vulnerable_model,
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tolerate_deprecated_model=tolerate_deprecated_model,
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sagemaker_session=sagemaker_session,
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config_name=config_name,
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)
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‎src/sagemaker/image_uri_config/autogluon.json

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"0.7": "0.7.0",
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"0.8": "0.8.2",
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"1.0": "1.0.0",
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"1.1": "1.1.0"
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"1.1": "1.1.1"
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},
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"versions": {
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"0.3.1": {
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"py_versions": [
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"py310"
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]
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},
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"1.1.1": {
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"registries": {
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"af-south-1": "626614931356",
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"il-central-1": "780543022126",
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"ap-east-1": "871362719292",
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"ap-northeast-1": "763104351884",
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"ap-northeast-2": "763104351884",
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"ap-northeast-3": "364406365360",
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"ap-south-1": "763104351884",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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"ap-southeast-3": "907027046896",
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"ap-southeast-4": "457447274322",
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"ca-central-1": "763104351884",
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"eu-central-1": "763104351884",
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"eu-north-1": "763104351884",
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"eu-west-1": "763104351884",
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"eu-west-2": "763104351884",
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"eu-west-3": "763104351884",
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"eu-south-1": "692866216735",
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"me-south-1": "217643126080",
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"sa-east-1": "763104351884",
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"us-east-1": "763104351884",
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"us-east-2": "763104351884",
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"us-gov-east-1": "446045086412",
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"us-gov-west-1": "442386744353",
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"us-iso-east-1": "886529160074",
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"us-isob-east-1": "094389454867",
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"us-west-1": "763104351884",
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"us-west-2": "763104351884",
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"ca-west-1": "204538143572"
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},
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"repository": "autogluon-training",
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"processors": [
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"cpu",
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"gpu"
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],
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"py_versions": [
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"py311"
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]
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}
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}
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},
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"0.7": "0.7.0",
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"0.8": "0.8.2",
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"1.0": "1.0.0",
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"1.1": "1.1.0"
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"1.1": "1.1.1"
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},
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"versions": {
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"0.3.1": {
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"py_versions": [
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"py310"
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]
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},
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"1.1.1": {
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"registries": {
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"af-south-1": "626614931356",
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"il-central-1": "780543022126",
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"ap-east-1": "871362719292",
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"ap-northeast-1": "763104351884",
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"ap-northeast-2": "763104351884",
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"ap-northeast-3": "364406365360",
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"ap-south-1": "763104351884",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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"ap-southeast-3": "907027046896",
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"ap-southeast-4": "457447274322",
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"ca-central-1": "763104351884",
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"cn-north-1": "727897471807",
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"cn-northwest-1": "727897471807",
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"eu-central-1": "763104351884",
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"eu-north-1": "763104351884",
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"eu-west-1": "763104351884",
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"eu-west-2": "763104351884",
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"eu-west-3": "763104351884",
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"eu-south-1": "692866216735",
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"me-south-1": "217643126080",
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"sa-east-1": "763104351884",
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"us-east-1": "763104351884",
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"us-east-2": "763104351884",
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"us-gov-east-1": "446045086412",
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"us-gov-west-1": "442386744353",
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"us-iso-east-1": "886529160074",
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"us-isob-east-1": "094389454867",
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"us-west-1": "763104351884",
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"us-west-2": "763104351884",
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"ca-west-1": "204538143572"
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},
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"repository": "autogluon-inference",
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"processors": [
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"cpu",
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"gpu"
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],
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"py_versions": [
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"py311"
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]
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}
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}
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}

‎src/sagemaker/image_uri_config/pytorch.json

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"1.12": "1.12.1",
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"2.0": "2.0.1",
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"2.1": "2.1.0",
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"2.2": "2.2.1"
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"2.2": "2.2.1",
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"2.3": "2.3.0"
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},
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"versions": {
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"1.12.1": {
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"us-west-2": "763104351884"
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},
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"repository": "pytorch-inference-graviton"
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},
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"2.3.0": {
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"container_version": {
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"cpu": "ubuntu20.04"
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},
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"py_versions": [
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"py311"
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],
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"registries": {
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"af-south-1": "626614931356",
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"ap-east-1": "871362719292",
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"ap-northeast-1": "763104351884",
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"ap-northeast-2": "763104351884",
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"ap-northeast-3": "364406365360",
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"ap-south-1": "763104351884",
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"ap-south-2": "772153158452",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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"ap-southeast-3": "907027046896",
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"ap-southeast-4": "457447274322",
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"ca-central-1": "763104351884",
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"ca-west-1": "204538143572",
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"cn-north-1": "727897471807",
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"cn-northwest-1": "727897471807",
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"eu-central-1": "763104351884",
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"eu-central-2": "380420809688",
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"eu-north-1": "763104351884",
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"eu-south-1": "692866216735",
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"eu-south-2": "503227376785",
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"eu-west-1": "763104351884",
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"eu-west-2": "763104351884",
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"eu-west-3": "763104351884",
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"il-central-1": "780543022126",
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"me-central-1": "914824155844",
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"me-south-1": "217643126080",
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"sa-east-1": "763104351884",
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"us-east-1": "763104351884",
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"us-east-2": "763104351884",
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"us-gov-east-1": "446045086412",
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"us-gov-west-1": "442386744353",
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"us-west-1": "763104351884",
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"us-west-2": "763104351884"
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},
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"repository": "pytorch-inference-graviton"
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}
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}
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},

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