ModelByIdGetResponseBody¶
- pydantic model openapi_client.models.model_by_id_get_response_body.ModelByIdGetResponseBody¶
Registered ML model record. InputSchema and OutputSchema are N/A when OutputType is metadata.
- Fields:
- field supported_file_formats: Optional[List[StrictStr]] = None (alias 'SupportedFileFormats')¶
File formats accepted when running the model (for example csv, parquet, txt).
- field input_schema: Optional[ModelByIdGetResponseBodyInputSchema] = None (alias 'InputSchema')¶
- field last_modified_by: Optional[StrictStr] = None (alias 'LastModifiedBy')¶
User who last updated the model metadata.
- field artifacts_location: Optional[StrictStr] = None (alias 'ArtifactsLocation')¶
S3 URI of the model artifact for custom models, or N/A for subscribed/existing SageMaker resources.
- field keywords: Optional[List[StrictStr]] = None (alias 'Keywords')¶
Free-form tags stored on the model. Defaults to [] when absent.
- field description: Optional[StrictStr] = None (alias 'Description')¶
Human-readable description of the model.
- field post_processed_glue_jobs: Optional[StrictStr] = None (alias 'PostProcessedGlueJobs')¶
Glue job name used after inference.
- field is_subscribed_model: Optional[StrictStr] = None (alias 'IsSubscribedModel')¶
no for custom artifact-created models (SageMaker model is deleted with Amorphic). yes for models registered from an existing SageMaker resource (SageMaker model is not deleted).
- field model_name: Optional[StrictStr] = None (alias 'ModelName')¶
Display name. Must be unique (case-insensitive) and match ^[a-zA-Z][a-zA-Z0-9-]{2,49}$.
- field algorithm_used: Optional[StrictStr] = None (alias 'AlgorithmUsed')¶
Training algorithm key used to select the SageMaker container image (for example BlazingText, XGBoost). N/A for subscribed models.
- field last_modified_time: Optional[StrictStr] = None (alias 'LastModifiedTime')¶
Last metadata update time as YYYY-MM-DD HH:MM:SS.
- field output_type: Optional[StrictStr] = None (alias 'OutputType')¶
metadata writes inference output as files; datasetdata writes to a dataset and requires InputSchema and OutputSchema.
- field output_schema: Optional[ModelByIdGetResponseBodyOutputSchema] = None (alias 'OutputSchema')¶
- field model_id: Optional[StrictStr] = None (alias 'ModelId')¶
Unique identifier. For custom creates this is also the SageMaker ModelName.
- field creation_time: Optional[StrictStr] = None (alias 'CreationTime')¶
Creation time as YYYY-MM-DD HH:MM:SS.
- field created_by: Optional[StrictStr] = None (alias 'CreatedBy')¶
User who registered the model.
- field pre_processed_glue_jobs: Optional[StrictStr] = None (alias 'PreProcessedGlueJobs')¶
Glue job name used before inference.
- field access_type: Optional[StrictStr] = None (alias 'AccessType')¶
Caller’s ACL on the model (owner, editor, or read-only). Defaults to read-only when the stored value is missing.
- to_str()¶
Returns the string representation of the model using alias
- Return type:
str
- to_json()¶
Returns the JSON representation of the model using alias
- Return type:
str
- classmethod from_json(json_str)¶
Create an instance of ModelByIdGetResponseBody from a JSON string
- Return type:
Optional[Self]
- to_dict()¶
Return the dictionary representation of the model using alias.
This has the following differences from calling pydantic’s self.model_dump(by_alias=True):
None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.
- Return type:
Dict[str,Any]
- classmethod from_dict(obj)¶
Create an instance of ModelByIdGetResponseBody from a dict
- Return type:
Optional[Self]