sagemaker.core

sagemaker.core#

SageMaker Core package for low-level resource management and SDK foundations.

Modules

`accept_types`	This module is for SageMaker accept types.
`analytics`	Placeholder docstring
`apiutils`	Utilities for providing a more pythonic style wrapper of boto.
`base_deserializers`	Backward compatibility module for base deserializers.
`base_serializers`	Backward compatibility module for base serializers.
`clarify`	This module configures the SageMaker Clarify bias and model explainability processor jobs.
`collection`	This module contains code related to Amazon SageMaker Collections in the Model Registry.
`common_utils`	Placeholder docstring
`compute_resource_requirements`	Compute Resource Requirements needed to deploy a model
`config`	This module configures the default values for SageMaker Python SDK.
`config_schema`
`constants`	Constants used across the SageMaker Core package.
`content_types`	This module is for SageMaker content types.
`debugger`	Classes for using debugger and profiler with Amazon SageMaker.
`deprecations`	Module for deprecation abstractions.
`deserializers`	Deserializers for SageMaker inference.
`drift_check_baselines`	This file contains code related to drift check baselines
`enums`	Defines enum values.
`environment_variables`	Accessors to retrieve environment variables for hosting containers.
`exceptions`	Custom exception classes for Sagemaker SDK
`experiments`	SageMaker Experiments module for tracking experiments, trials, and runs.
`explainer`	Imports the classes in this module to simplify customer imports
`fw_utils`	Utility methods used by framework classes.
`git_utils`	Placeholder docstring
`helper`
`hyperparameters`	Accessors to retrieve hyperparameters for training jobs.
`image_retriever`
`image_uris`	Functions for generating ECR image URIs for pre-built SageMaker Docker images.
`inference_config`	Configuration classes for SageMaker inference endpoints.
`inference_recommender`	Classes for using Inference Recommender with Amazon SageMaker.
`inputs`	Amazon SageMaker channel configurations for S3 data sources and file system data sources
`instance_group`	Defines the InstanceGroup class that configures a heterogeneous cluster.
`instance_types`	Accessors to retrieve instance types.
`instance_types_gpu_info`	Accessors to retrieve instance types GPU info.
`interactive_apps`	Classes for starting/accessing apps hosted on Amazon SageMaker Studio.
`iterators`	Implements iterators for deserializing data returned from an inference streaming endpoint.
`job`	Placeholder docstring
`jumpstart`	This module contains JumpStart utilities for the SageMaker Python SDK.
`lambda_helper`	This module contains helper methods related to Lambda.
`lineage`	SageMaker Lineage tracking and artifact management.
`local`	Local mode utilities for SageMaker.
`logs`	Placeholder docstring
`metadata_properties`	This file contains code related to metadata properties.
`metric_definitions`	Accessors to retrieve metric definition for training jobs.
`mlflow`	MLflow integration module - stub.
`model_card`	Model Card utilities for SageMaker Python SDK.
`model_life_cycle`	This file contains code related to model life cycle.
`model_metrics`	This file contains code related to model metrics, including metric source and file source.
`model_monitor`	Amazon SageMaker Model Monitoring module.
`model_registry`
`model_uris`	Accessors to retrieve the model artifact S3 URI of pretrained machine learning models.
`modules`	SageMaker modules directory.
`network`	This file contains code related to network configuration.
`parameter`	Placeholder docstring
`partner_app`	__init__ file for sagemaker.core.partner_app
`payloads`	Utilities related to payloads of pretrained machine learning models.
`processing`	This module contains code related to the `Processor` class.
`remote_function`	Defines classes and helper methods used in remote function executions.
`resource_requirements`	Accessors to retrieve resource requirements.
`resources`
`s3`	S3 utilities for SageMaker.
`script_uris`	Accessors to retrieve the script Amazon S3 URI to run pretrained machine learning models.
`serializers`	Serializers for SageMaker inference.
`serverless_inference_config`	This module contains code related to the ServerlessInferenceConfig class.
`session_settings`	Defines classes to parametrize a SageMaker `Session`.
`shapes`
`spark`	Placeholder docstring
`telemetry`	This module contains telemetry utilities for the SageMaker Python SDK.
`tools`
`training`	Training configuration and utilities.
`training_compiler`	Training Compiler configuration for SageMaker Python SDK.
`training_compiler_config`	Configuration for the SageMaker Training Compiler.
`transformer`	Placeholder docstring
`user_agent`	Placeholder docstring
`utilities`	Utilities for SageMaker Python SDK.
`utils`	Utilities package for SageMaker Core.
`workflow`	Workflow primitives for SageMaker pipelines.