sagemaker.core.jumpstart.models#
This module contains the model for JumpStart HubContentDocument.
Classes
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The HubContentDocument class represents the metadata for a JumpStart model. |
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An enumeration. |
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- class sagemaker.core.jumpstart.models.AccelerationConfigModel(*, Type: str, Enabled: bool, Spec: SpecModel | None = None, DiyWorkflowOverrides: Dict[str, DiyWorkflowOverridesModel] | None = None)[source]#
Bases:
BaseConfig- DiyWorkflowOverrides: Dict[str, DiyWorkflowOverridesModel] | None#
- Enabled: bool#
- Type: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.BenchmarkMetricModel(*, Name: str, Value: str, Unit: str, DisplayText: str | None = None, Concurrency: str | None = None)[source]#
Bases:
BaseConfig- Concurrency: str | None#
- DisplayText: str | None#
- Name: str#
- Unit: str#
- Value: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.CapabilityEnum(value)[source]#
Bases:
StrEnum- BEDROCK_CONSOLE = 'BEDROCK_CONSOLE'#
- FINE_TUNING = 'FINE_TUNING'#
- HYPERPOD_DEPLOYMENT = 'HYPERPOD_DEPLOYMENT'#
- INCREMENTAL_TRAINING = 'INCREMENTAL_TRAINING'#
- SAGEMAKER_EVALUATE = 'SAGEMAKER_EVALUATE'#
- SAGEMAKER_MODEL_OPTIMIZE = 'SAGEMAKER_MODEL_OPTIMIZE'#
- TRAINING = 'TRAINING'#
- VALIDATION = 'VALIDATION'#
- class sagemaker.core.jumpstart.models.CompressionTypeEnum(value)[source]#
Bases:
StrEnum- GZIP = 'Gzip'#
- NONE = 'None'#
- class sagemaker.core.jumpstart.models.ConfigSchemaModel(*, ComponentNames: List[str], HubContentDependencies: List[HubContentDependencyModel] | None = None, BenchmarkMetrics: Dict[str, List[BenchmarkMetricModel]] | None = None, AccelerationConfigs: List[AccelerationConfigModel] | None = None)[source]#
Bases:
BaseConfig- AccelerationConfigs: List[AccelerationConfigModel] | None#
- BenchmarkMetrics: Dict[str, List[BenchmarkMetricModel]] | None#
- ComponentNames: List[str]#
- HubContentDependencies: List[HubContentDependencyModel] | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.ContextualHelpModel(*, HubFormatTrainData: List[str] | None = None, HubDefaultTrainData: List[str] | None = None)[source]#
Bases:
BaseConfig- HubDefaultTrainData: List[str] | None#
- HubFormatTrainData: List[str] | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.DefaultPayloadsModel(*, ContentType: str, PromptKey: str | None = None, OutputKeys: OutputKeysModel | None = None, Body: str | Dict[str, Any])[source]#
Bases:
BaseConfig- Body: str | Dict[str, Any]#
- ContentType: str#
- OutputKeys: OutputKeysModel | None#
- PromptKey: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.DemoNotebookModel(*, Title: str, S3Uri: str = None, IsDefault: bool | None = None)[source]#
Bases:
BaseConfig- IsDefault: bool | None#
- S3Uri: str#
- Title: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.DependencyModel(*, DependencyOriginPath: str | None = None, DependencyCopyPath: str | None = None, DependencyType: DependencyTypeEnum | None = None)[source]#
Bases:
BaseConfig- DependencyCopyPath: str | None#
- DependencyOriginPath: str | None#
- DependencyType: DependencyTypeEnum | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.DependencyTypeEnum(value)[source]#
Bases:
StrEnum- ARTIFACT = 'ARTIFACT'#
- DATASET = 'DATASET'#
- NOTEBOOK = 'NOTEBOOK'#
- OTHER = 'OTHER'#
- SCRIPT = 'SCRIPT'#
- class sagemaker.core.jumpstart.models.DiyWorkflowOverridesModel(*, enabled: bool | None = None, reason: str | None = None)[source]#
Bases:
BaseConfig- enabled: bool | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- reason: str | None#
- class sagemaker.core.jumpstart.models.HostingAdditionalDataSourceModel(*, ChannelName: str, ArtifactVersion: str | None = None, S3DataSource: S3DataSourceModel = None, HostingEulaUri: str | None = None, Provider: ProviderModel | None = None)[source]#
Bases:
BaseConfig- ArtifactVersion: str | None#
- ChannelName: str#
- HostingEulaUri: str | None#
- Provider: ProviderModel | None#
- S3DataSource: S3DataSourceModel#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HostingArtifactCompressionTypeEnum(value)[source]#
Bases:
StrEnum- GZIP = 'Gzip'#
- NONE = 'None'#
- class sagemaker.core.jumpstart.models.HostingArtifactS3DataTypeEnum(value)[source]#
Bases:
StrEnum- S3OBJECT = 'S3Object'#
- S3PREFIX = 'S3Prefix'#
- class sagemaker.core.jumpstart.models.HostingComponentsModel(*, DynamicContainerDeploymentSupported: bool | None = None, HostingAdditionalDataSources: Dict[str, List[HostingAdditionalDataSourceModel]] | None = None, BedrockIOMappingId: str | None = None, Capabilities: List[CapabilityEnum] | None = None, HostingEcrUri: str | None = None, HostingArtifactS3DataType: HostingArtifactS3DataTypeEnum | None = None, HostingArtifactCompressionType: HostingArtifactCompressionTypeEnum | None = None, HostingArtifactUri: str | None = None, HostingScriptUri: str | None = None, HostingUseScriptUri: bool | None = None, HostingEulaUri: str | None = None, HostingEulaExternalLink: str | None = None, ModelSubscriptionLink: str | None = None, ListingId: str | None = None, ProductId: str | None = None, HostingModelPackageArn: str | None = None, ModelDataDownloadTimeout: int | None = None, ContainerStartupHealthCheckTimeout: int | None = None, InferenceAmiVersion: InferenceAmiVersionEnum | None = None, InferenceEnvironmentVariables: List[InferenceEnvironmentVariablesModel] | None = None, InferenceDependencies: List[str] | None = None, DefaultInferenceInstanceType: str | None = None, SupportedInferenceInstanceTypes: List[str] | None = None, SageMakerSdkPredictorSpecifications: SageMakerSdkPredictorSpecificationsModel | None = None, InferenceVolumeSize: int | None = None, InferenceEnableNetworkIsolation: bool | None = None, DefaultPayloads: Dict[str, DefaultPayloadsModel] | None = None, HostingResourceRequirements: HostingResourceRequirementsModel | None = None, HostingEcrSpecs: HostingEcrSpecsModel | None = None, HostingInstanceTypeVariants: HostingInstanceTypeVariantsModel | None = None, **extra_data: Any)[source]#
Bases:
BaseConfig- BedrockIOMappingId: str | None#
- Capabilities: List[CapabilityEnum] | None#
- ContainerStartupHealthCheckTimeout: int | None#
- DefaultInferenceInstanceType: str | None#
- DefaultPayloads: Dict[str, DefaultPayloadsModel] | None#
- DynamicContainerDeploymentSupported: bool | None#
- HostingAdditionalDataSources: Dict[str, List[HostingAdditionalDataSourceModel]] | None#
- HostingArtifactCompressionType: HostingArtifactCompressionTypeEnum | None#
- HostingArtifactS3DataType: HostingArtifactS3DataTypeEnum | None#
- HostingArtifactUri: str | None#
- HostingEcrSpecs: HostingEcrSpecsModel | None#
- HostingEcrUri: str | None#
- HostingEulaExternalLink: str | None#
- HostingEulaUri: str | None#
- HostingInstanceTypeVariants: HostingInstanceTypeVariantsModel | None#
- HostingModelPackageArn: str | None#
- HostingResourceRequirements: HostingResourceRequirementsModel | None#
- HostingScriptUri: str | None#
- HostingUseScriptUri: bool | None#
- InferenceAmiVersion: InferenceAmiVersionEnum | None#
- InferenceDependencies: List[str] | None#
- InferenceEnableNetworkIsolation: bool | None#
- InferenceEnvironmentVariables: List[InferenceEnvironmentVariablesModel] | None#
- InferenceVolumeSize: int | None#
- ListingId: str | None#
- ModelDataDownloadTimeout: int | None#
- ModelSubscriptionLink: str | None#
- ProductId: str | None#
- SageMakerSdkPredictorSpecifications: SageMakerSdkPredictorSpecificationsModel | None#
- SupportedInferenceInstanceTypes: List[str] | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HostingEcrSpecsModel(*, Framework: str, FrameworkVersion: str, PyVersion: str, HuggingfaceTransformersVersion: str | None = None)[source]#
Bases:
BaseConfig- Framework: str#
- FrameworkVersion: str#
- HuggingfaceTransformersVersion: str | None#
- PyVersion: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HostingInstanceTypeVariantsModel(*, Aliases: Dict[str, str] | None = None, Variants: Dict[str, HostingVariantModel] | None = None)[source]#
Bases:
BaseConfig- Aliases: Dict[str, str] | None#
- Variants: Dict[str, HostingVariantModel] | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HostingResourceRequirementsModel(*, NumAccelerators: int | None = None, NumCpus: int | None = None, MinMemoryMb: int)[source]#
Bases:
BaseConfig- MinMemoryMb: int#
- NumAccelerators: int | None#
- NumCpus: int | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HostingVariantModel(*, Properties: HostingVariantPropertiesModel | None = None)[source]#
Bases:
BaseConfig- Properties: HostingVariantPropertiesModel | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HostingVariantPropertiesModel(*, ImageUri: str | None = None, EnvironmentVariables: Dict[str, str] | None = None, ModelPackageArn: str | None = None, ListingId: str | None = None, ProductId: str | None = None, ResourceRequirements: HostingResourceRequirementsModel | None = None)[source]#
Bases:
BaseConfig- EnvironmentVariables: Dict[str, str] | None#
- ImageUri: str | None#
- ListingId: str | None#
- ModelPackageArn: str | None#
- ProductId: str | None#
- ResourceRequirements: HostingResourceRequirementsModel | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HubAccessConfigModel(*, HubContentArn: str | None = None)[source]#
Bases:
BaseConfig- HubContentArn: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HubContentDependencyModel(*, HubContentArn: str)[source]#
Bases:
BaseConfig- HubContentArn: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HubContentDocument(*, TrainingArtifactS3DataType: TrainingArtifactS3DataTypeEnum | None = None, TrainingArtifactCompressionType: TrainingArtifactCompressionTypeEnum | None = None, TrainingModelPackageArtifactUri: str | None = None, Hyperparameters: List[HyperparameterUpperModel] | None = None, TrainingScriptUri: str | None = None, TrainingEcrUri: str | None = None, TrainingMetrics: List[TrainingMetricModel] | None = None, TrainingArtifactUri: str | None = None, TrainingDependencies: List[str] | None = None, DefaultTrainingInstanceType: str | None = None, SupportedTrainingInstanceTypes: List[str] | None = None, TrainingVolumeSize: int | None = None, TrainingEnableNetworkIsolation: bool | None = None, FineTuningSupported: bool | None = None, ValidationSupported: bool | None = None, DefaultTrainingDatasetUri: str | None = None, EncryptInterContainerTraffic: bool | None = None, MaxRuntimeInSeconds: int | None = None, DisableOutputCompression: bool | None = None, ModelDir: str | None = None, TrainingInstanceTypeVariants: TrainingInstanceTypeVariantsModel | None = None, DynamicContainerDeploymentSupported: bool | None = None, HostingAdditionalDataSources: Dict[str, List[HostingAdditionalDataSourceModel]] | None = None, BedrockIOMappingId: str | None = None, Capabilities: List[CapabilityEnum] = None, HostingEcrUri: str | None = None, HostingArtifactS3DataType: HostingArtifactS3DataTypeEnum | None = None, HostingArtifactCompressionType: HostingArtifactCompressionTypeEnum | None = None, HostingArtifactUri: str | None = None, HostingScriptUri: str | None = None, HostingUseScriptUri: bool | None = None, HostingEulaUri: str | None = None, HostingEulaExternalLink: str | None = None, ModelSubscriptionLink: str | None = None, ListingId: str | None = None, ProductId: str | None = None, HostingModelPackageArn: str | None = None, ModelDataDownloadTimeout: int | None = None, ContainerStartupHealthCheckTimeout: int | None = None, InferenceAmiVersion: InferenceAmiVersionEnum | None = None, InferenceEnvironmentVariables: List[InferenceEnvironmentVariablesModel] | None = None, InferenceDependencies: List[str] | None = None, DefaultInferenceInstanceType: str | None = None, SupportedInferenceInstanceTypes: List[str] | None = None, SageMakerSdkPredictorSpecifications: SageMakerSdkPredictorSpecificationsModel | None = None, InferenceVolumeSize: int | None = None, InferenceEnableNetworkIsolation: bool | None = None, DefaultPayloads: Dict[str, DefaultPayloadsModel] | None = None, HostingResourceRequirements: HostingResourceRequirementsModel | None = None, HostingEcrSpecs: HostingEcrSpecsModel | None = None, HostingInstanceTypeVariants: HostingInstanceTypeVariantsModel | None = None, ModelTypes: List[ModelTypeEnum], Url: str, MinSdkVersion: str | None = None, TrainingSupported: bool, IncrementalTrainingSupported: bool, ResourceNameBase: str | None = None, GatedBucket: bool | None = None, MarketplaceVersion: str | None = None, NotebookLocations: NotebookLocationsModel | None = None, ModelProviderIconUri: str | None = None, Task: str | None = None, Framework: str | None = None, Provider: str | None = None, DataType: str | None = None, License: str | None = None, ContextualHelp: ContextualHelpModel | None = None, Dependencies: List[DependencyModel] | None = None, InferenceConfigs: Dict[str, ConfigSchemaModel] | None = None, InferenceConfigComponents: Dict[str, HostingComponentsModel] | None = None, InferenceConfigRankings: Dict[str, RankingSchemaModel] | None = None, TrainingConfigs: Dict[str, ConfigSchemaModel] | None = None, TrainingConfigComponents: Dict[str, TrainingComponentsModel] | None = None, TrainingConfigRankings: Dict[str, RankingSchemaModel] | None = None, Resources: List[ResourceModel] | None = None, Highlights: List[str] | None = None)[source]#
Bases:
HostingComponentsModel,TrainingComponentsModelThe HubContentDocument class represents the metadata for a JumpStart model.
- Capabilities: List[CapabilityEnum]#
- ContextualHelp: ContextualHelpModel | None#
- DataType: str | None#
- Dependencies: List[DependencyModel] | None#
- Framework: str | None#
- GatedBucket: bool | None#
- Highlights: List[str] | None#
- IncrementalTrainingSupported: bool#
- InferenceConfigComponents: Dict[str, HostingComponentsModel] | None#
- InferenceConfigRankings: Dict[str, RankingSchemaModel] | None#
- InferenceConfigs: Dict[str, ConfigSchemaModel] | None#
- License: str | None#
- MarketplaceVersion: str | None#
- MinSdkVersion: str | None#
- ModelProviderIconUri: str | None#
- ModelTypes: List[ModelTypeEnum]#
- NotebookLocations: NotebookLocationsModel | None#
- Provider: str | None#
- ResourceNameBase: str | None#
- Resources: List[ResourceModel] | None#
- Task: str | None#
- TrainingConfigComponents: Dict[str, TrainingComponentsModel] | None#
- TrainingConfigRankings: Dict[str, RankingSchemaModel] | None#
- TrainingConfigs: Dict[str, ConfigSchemaModel] | None#
- TrainingSupported: bool#
- Url: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.HyperparameterLowerModel(*, name: str = None, label: str | None = None, description: str | None = None, scope: ScopeEnum = None, validators: List[str | ValidatorEnum] | None = None, default: int | float | str = None, min: int | float | str | None = None, max: int | float | str | None = None, type: TypeEnum = None, options: List[str] | None = None)[source]#
Bases:
BaseConfig- default: int | float | str#
- description: str | None#
- label: str | None#
- max: int | float | str | None#
- min: int | float | str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- name: str#
- options: List[str] | None#
- validators: List[str | ValidatorEnum] | None#
- class sagemaker.core.jumpstart.models.HyperparameterUpperModel(*, Name: str = None, Label: str | None = None, Description: str | None = None, Scope: ScopeEnum = None, Validators: List[str | ValidatorEnum] | None = None, Default: int | float | str = None, Min: int | float | str | None = None, Max: int | float | str | None = None, Type: TypeEnum = None, Options: List[str] | None = None)[source]#
Bases:
BaseConfig- Default: int | float | str#
- Description: str | None#
- Label: str | None#
- Max: int | float | str | None#
- Min: int | float | str | None#
- Name: str#
- Options: List[str] | None#
- Validators: List[str | ValidatorEnum] | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.InferenceAmiVersionEnum(value)[source]#
Bases:
StrEnum- AL2_AMI_SAGEMAKER_INFERENCE_GPU_2 = 'al2-ami-sagemaker-inference-gpu-2'#
- AL2_AMI_SAGEMAKER_INFERENCE_GPU_3_1 = 'al2-ami-sagemaker-inference-gpu-3-1'#
- class sagemaker.core.jumpstart.models.InferenceEnvironmentVariablesModel(*, Name: str | None = None, Scope: ScopeEnum | None = None, Default: int | float | str | None = None, Min: int | float | str | None = None, Max: int | float | str | None = None, Type: TypeEnum | None = None, RequiredForModelClass: bool | None = None)[source]#
Bases:
BaseConfig- Default: int | float | str | None#
- Max: int | float | str | None#
- Min: int | float | str | None#
- Name: str | None#
- RequiredForModelClass: bool | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.ModelTypeEnum(value)[source]#
Bases:
StrEnum- OPEN_WEIGHTS = 'OPEN_WEIGHTS'#
- PROPRIETARY = 'PROPRIETARY'#
- class sagemaker.core.jumpstart.models.NotebookLocationsModel(*, DemoNotebook: str | None = None, DemoNotebooks: List[DemoNotebookModel] | None = None, ModelFit: str | None = None, ModelDeploy: str | None = None)[source]#
Bases:
BaseConfig- DemoNotebook: str | None#
- DemoNotebooks: List[DemoNotebookModel] | None#
- ModelDeploy: str | None#
- ModelFit: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.OutputKeysModel(*, generated_text: str | None = None, input_logprobs: str | None = None, label: str | None = None, **extra_data: Any)[source]#
Bases:
BaseConfig- generated_text: str | None#
- input_logprobs: str | None#
- label: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.ProviderModel(*, Name: str, Classification: str)[source]#
Bases:
BaseConfig- Classification: str#
- Name: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.RankingSchemaModel(*, Description: str | None = None, Rankings: List[str] | None = None)[source]#
Bases:
BaseConfig- Description: str | None#
- Rankings: List[str] | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.ResourceModel(*, DisplayName: str | None = None, Url: str | None = None)[source]#
Bases:
BaseConfig- DisplayName: str | None#
- Url: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.S3DataSourceModel(*, CompressionType: CompressionTypeEnum | None = None, S3DataType: S3DataTypeEnum | None = None, S3Uri: str | None = None, HubAccessConfig: HubAccessConfigModel | None = None)[source]#
Bases:
BaseConfig- CompressionType: CompressionTypeEnum | None#
- HubAccessConfig: HubAccessConfigModel | None#
- S3DataType: S3DataTypeEnum | None#
- S3Uri: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.S3DataTypeEnum(value)[source]#
Bases:
StrEnum- S3OBJECT = 'S3Object'#
- S3PREFIX = 'S3Prefix'#
- class sagemaker.core.jumpstart.models.SageMakerSdkPredictorSpecificationsModel(*, DefaultContentType: str, SupportedContentTypes: List[str], DefaultAcceptType: str, SupportedAcceptTypes: List[str])[source]#
Bases:
BaseConfig- DefaultAcceptType: str#
- DefaultContentType: str#
- SupportedAcceptTypes: List[str]#
- SupportedContentTypes: List[str]#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.ScopeEnum(value)[source]#
Bases:
StrEnum- ALGORITHM = 'algorithm'#
- CONTAINER = 'container'#
- HYPER = 'hyper'#
- class sagemaker.core.jumpstart.models.SpecModel(*, Compiler: str | None = None, Version: str | None = None)[source]#
Bases:
BaseConfig- Compiler: str | None#
- Version: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.TrainingArtifactCompressionTypeEnum(value)[source]#
Bases:
StrEnum- GZIP = 'Gzip'#
- NONE = 'None'#
- class sagemaker.core.jumpstart.models.TrainingArtifactS3DataTypeEnum(value)[source]#
Bases:
StrEnum- S3OBJECT = 'S3Object'#
- S3PREFIX = 'S3Prefix'#
- class sagemaker.core.jumpstart.models.TrainingComponentsModel(*, TrainingArtifactS3DataType: TrainingArtifactS3DataTypeEnum | None = None, TrainingArtifactCompressionType: TrainingArtifactCompressionTypeEnum | None = None, TrainingModelPackageArtifactUri: str | None = None, Hyperparameters: List[HyperparameterUpperModel] | None = None, TrainingScriptUri: str | None = None, TrainingEcrUri: str | None = None, TrainingMetrics: List[TrainingMetricModel] | None = None, TrainingArtifactUri: str | None = None, TrainingDependencies: List[str] | None = None, DefaultTrainingInstanceType: str | None = None, SupportedTrainingInstanceTypes: List[str] | None = None, TrainingVolumeSize: int | None = None, TrainingEnableNetworkIsolation: bool | None = None, FineTuningSupported: bool | None = None, ValidationSupported: bool | None = None, DefaultTrainingDatasetUri: str | None = None, EncryptInterContainerTraffic: bool | None = None, MaxRuntimeInSeconds: int | None = None, DisableOutputCompression: bool | None = None, ModelDir: str | None = None, TrainingInstanceTypeVariants: TrainingInstanceTypeVariantsModel | None = None)[source]#
Bases:
BaseConfig- DefaultTrainingDatasetUri: str | None#
- DefaultTrainingInstanceType: str | None#
- DisableOutputCompression: bool | None#
- EncryptInterContainerTraffic: bool | None#
- FineTuningSupported: bool | None#
- Hyperparameters: List[HyperparameterUpperModel] | None#
- MaxRuntimeInSeconds: int | None#
- ModelDir: str | None#
- SupportedTrainingInstanceTypes: List[str] | None#
- TrainingArtifactCompressionType: TrainingArtifactCompressionTypeEnum | None#
- TrainingArtifactS3DataType: TrainingArtifactS3DataTypeEnum | None#
- TrainingArtifactUri: str | None#
- TrainingDependencies: List[str] | None#
- TrainingEcrUri: str | None#
- TrainingEnableNetworkIsolation: bool | None#
- TrainingInstanceTypeVariants: TrainingInstanceTypeVariantsModel | None#
- TrainingMetrics: List[TrainingMetricModel] | None#
- TrainingModelPackageArtifactUri: str | None#
- TrainingScriptUri: str | None#
- TrainingVolumeSize: int | None#
- ValidationSupported: bool | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.TrainingInstanceTypeVariantsModel(*, Aliases: Dict[str, str] | None = None, Variants: Dict[str, TrainingVariantModel] | None = None)[source]#
Bases:
BaseConfig- Aliases: Dict[str, str] | None#
- Variants: Dict[str, TrainingVariantModel] | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.TrainingMetricModel(*, Name: str, Regex: str)[source]#
Bases:
BaseConfig- Name: str#
- Regex: str#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.TrainingVariantModel(*, Properties: TrainingVarientPropertiesModel | None = None)[source]#
Bases:
BaseConfig- Properties: TrainingVarientPropertiesModel | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- class sagemaker.core.jumpstart.models.TrainingVarientPropertiesModel(*, ImageUri: str | None = None, GatedModelEnvVarUri: str | None = None, TrainingArtifactUri: str | None = None, EnvironmentVariables: Dict[str, str] | None = None, Hyperparameters: List[HyperparameterLowerModel] | None = None)[source]#
Bases:
BaseConfig- EnvironmentVariables: Dict[str, str] | None#
- GatedModelEnvVarUri: str | None#
- Hyperparameters: List[HyperparameterLowerModel] | None#
- ImageUri: str | None#
- TrainingArtifactUri: str | None#
- model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'frozen': True, 'validate_assignment': True}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].