Amazon SageMaker Model Cards¶
For more information about using model cards with the SageMaker Python SDK, see Amazon SageMaker Model Cards in the Amazon SageMaker Developer Guide.
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class
sagemaker.model_card.
AdditionalInformation
(ethical_considerations=None, caveats_and_recommendations=None, custom_details=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
Additional information for a model card.
Initialize an Additional Information object.
- Parameters
ethical_considerations (str, optional) – Any ethical considerations to document about the model (default: None).
caveats_and_recommendations (str, optional) – Caveats and recommendations for those who might use this model in their applications (default: None).
custom_details (dict, optional) – Any additional custom information to document about the model (default: None).
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class
sagemaker.model_card.
Environment
(container_image)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
Training/inference environment.
Initialize an Environment object.
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class
sagemaker.model_card.
EvaluationJob
(name, evaluation_observation=None, evaluation_job_arn=None, datasets=None, metadata=None, metric_groups=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
Overview of an evaluation job.
Initialize an Evaluation Job object.
- Parameters
name (str) – The evaluation job name.
evaluation_observation (str, optional) – Any observations made during model evaluation (default: None).
evaluation_job_arn (str, optional) – The Amazon Resource Name (ARN) of the evaluation job (default: None).
datasets (List[str], optional) – Evaluation dataset locations. Maximum list length is 10 (default: None).
metadata (Optional[dict], optional) – Additional attributes associated with the evaluation results (default: None).
metric_groups (List[MetricGroup], optional) – An evaluation Metric Group object (default: None).
-
class
sagemaker.model_card.
Function
(function=None, facet=None, condition=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
Function details.
Initialize a Function object.
- Parameters
function (ObjectiveFunctionEnum or str, optional) – The optimization direction of the model’s objective function. It is highly recommended to use sagemaker.model_card.ObjectiveFunctionEnum. Possible values include:
ObjectiveFunctionEnum.MAXIMIZE
(“Maximize”) orObjectiveFunctionEnum.MINIMIZE
(“Minimize”) (default: None).facet (FacetEnum or str, optional) – The metric of the model’s objective function. For example, loss or rmse. It is highly recommended to use sagemaker.model_card.FacetEnum. Possible values include:,
FacetEnum.ACCURACY
(“Accuracy”),FacetEnum.AUC
(“AUC”),FacetEnum.LOSS
(“Loss”),FacetEnum.MAE
(“MAE”), orFacetEnum.RMSE
(“RMSE”) (default: None).condition (str, optional) – An optional description of any conditions of your objective function metric (default: None).
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class
sagemaker.model_card.
IntendedUses
(purpose_of_model=None, intended_uses=None, factors_affecting_model_efficiency=None, risk_rating=<RiskRatingEnum.UNKNOWN: 'Unknown'>, explanations_for_risk_rating=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
The intended uses of a model.
Initialize an Intended Uses object.
- Parameters
purpose_of_model (str, optional) – The general purpose of this model (default: None).
intended_uses (str, optional) – The intended use cases for this model (default: None).
factors_affecting_model_efficiency (str, optional) – Factors affecting model efficacy (default: None).
risk_rating (RiskRatingEnum or str, optional) – Your organization’s risk rating for this model. It is highly recommended to use sagemaker.model_card.RiskRatingEnum. Possible values include:
RiskRatingEnum.HIGH
(“High”),RiskRatingEnum.LOW
(“Low”),RiskRatingEnum.MEDIUM
(“Medium”), orRiskRatingEnum.UNKNOWN
(“Unknown”). Defaults toRiskRatingEnum.UNKNOWN
.explanations_for_risk_rating (str, optional) – An explanation of why your organization categorizes this model with this risk rating (default: None).
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class
sagemaker.model_card.
Metric
(name, type, value, notes=None, x_axis_name=None, y_axis_name=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
Metric data.
Initialize a Metric object.
- Parameters
name (str) – The name of the metric.
type (str or MetricTypeEnum) – It is highly recommended to use sagemaker.model_card.MetricTypeEnum. Possible values include:
MetricTypeEnum.BAR_CHART
(“bar_char”),MetricTypeEnum.BOOLEAN
(“boolean”),MetricTypeEnum.LINEAR_GRAPH
(“linear_graph”),MetricTypeEnum.MATRIX
(“matrix”),MetricTypeEnum.NUMBER
(“number”), orMetricTypeEnum.STRING
(“string”).value (int or float or str or bool or List) – The datatype of the metric. The metric’s value must be compatible with the metric’s type.
notes (str, optional) – Any notes to add to the metric (default: None).
x_axis_name (str, optional) – The name of the x axis (default: None).
y_axis_name (str, optional) – The name of the y axis (default: None).
-
class
sagemaker.model_card.
MetricGroup
(name, metric_data=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
Group of metric data
Initialize a Metric Group object.
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class
sagemaker.model_card.
ModelCard
(name, status=<ModelCardStatusEnum.DRAFT: 'Draft'>, arn=None, version=None, created_time=None, created_by=None, last_modified_time=None, last_modified_by=None, model_overview=None, intended_uses=None, business_details=None, training_details=None, evaluation_details=None, additional_information=None, sagemaker_session=None)¶ Bases:
object
Use an Amazon SageMaker Model Card to document qualitative and quantitative information about a model.
Initialize an Amazon SageMaker Model Card.
- Parameters
name (str) – The unique name of the model card.
status (ModelCardStatusEnum or str, optional) – Your organization’s approval status of the model card. It is highly recommended to use sagemaker.model_card.ModelCardStatusEnum. Possible values include:
ModelCardStatusEnum.APPROVED
(“Approved”),ModelCardStatusEnum.ARCHIVED
(“Archived”),ModelCardStatusEnum.DRAFT
(“Draft”), orModelCardStatusEnum.PENDING_REVIEW
(“PendingReview”). Defaults toModelCardStatusEnum.DRAFT
.arn (str, optional) – The Amazon Resource Name (ARN) of the model card (default: None).
version (int, optional) – The model card version (default: None).
created_time (datetime, optional) – The date/time that you created the model card (default: None).
created_by (dict, optional) – The group or individual that created the model card (default: None).
last_modified_time (datetime, optional) – The last time that the model card was modified (default: None).
last_modified_by (dict, optional) – The group or individual that last modified the model card (default: None).
model_overview (ModelOverview, optional) – An overview of the model (default: None).
intended_uses (IntendedUses, optional) – The intended uses of the model (default: None).
business_details (BusinessDetails, optional) – The business details of the model (default: None).
training_details (TrainingDetails, optional) – The training details of the model (default: None).
evaluation_details (List[EvaluationJob], optional) – The evaluation details of the model (default: None).
additional_information (AdditionalInformation, optional) – Additional information about the model (default: None).
sagemaker_session (Session, optional) – A SageMaker Session object, used for SageMaker interactions (default: None). If not specified, a SageMaker Session is created using the default AWS configuration chain.
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class
sagemaker.model_card.
ModelOverview
(model_id=None, model_name=None, model_description=None, model_version=None, problem_type=None, algorithm_type=None, model_creator=None, model_owner=None, model_artifact=None, inference_environment=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
An overview of the model.
Initialize a Model Overview object.
- Parameters
model_id (str, optional) – A SageMaker Model ARN or non-SageMaker Model ID (default: None).
model_name (str, optional) – A unique name for the model (default: None).
model_description (str, optional) – A description of the model (default: None).
model_version (int or float, optional) – The version of the model (default: None).
problem_type (str, optional) – The type of problem that the model solves. For example, “Binary Classification”, “Multiclass Classification”, “Linear Regression”, “Computer Vision”, or “Natural Language Processing” (default: None).
algorithm_type (str, optional) – The algorithm used to solve the problem type (default: None).
model_creator (str, optional) – The organization, research group, or authors that created the model (default: None).
model_owner (str, optional) – The individual or group that maintains the model in your organization (default: None).
model_artifact (List[str], optional) – A list of model artifact location URIs. The maximum list size is 15. (default: None).
inference_environment (Environment, optional) – An overview of the model’s inference environment (default: None).
-
class
sagemaker.model_card.
ObjectiveFunction
(function, notes=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
The objective function that is optimized during model training.
Initialize an Objective Function object.
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class
sagemaker.model_card.
TrainingDetails
(objective_function=None, training_observations=None, training_job_details=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
The overview of model training.
Initialize a TrainingDetails object.
- Parameters
objective_function (ObjectiveFunction, optional) – The objective function that is optimized during training (default: None).
training_observations (str, optional) – Any observations about training (default: None).
training_job_details (TrainingJobDetails, optional) – Details about any associated training jobs (default: None).
-
class
sagemaker.model_card.
TrainingJobDetails
(training_arn=None, training_datasets=None, training_environment=None, training_metrics=None, user_provided_training_metrics=None, hyper_parameters=None, user_provided_hyper_parameters=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
The overview of a training job.
Initialize a Training Job Details object.
- Parameters
training_arn (str, optional) – The SageMaker training job Amazon Resource Name (ARN) (default: None).
training_datasets (List[str], optional) – The location of the datasets used to train the model. The maximum list size is 15. (default: None).
training_environment (Environment, optional) – The SageMaker training image URI. (default: None).
training_metrics (list[TrainingMetric], optional) – SageMaker training job results. The maximum training_metrics list length is 50 (default: None).
user_provided_training_metrics (list[TrainingMetric], optional) – Custom training job results. The maximum user_provided_training_metrics list length is 50 (default: None).
hyper_parameters (list[HyperParameter], optional) – SageMaker hyper parameter results. The maximum hyper_parameters list length is 100 (default: None).
user_provided_hyper_parameters (list[HyperParameter], optional) – Custom hyper parameter results. The maximum user_provided_hyper_parameters list length is 100 (default: None).
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class
sagemaker.model_card.
BusinessDetails
(business_problem=None, business_stakeholders=None, line_of_business=None)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
The business details of a model.
Initialize an Business Details object.
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class
sagemaker.model_card.
HyperParameter
(name, value)¶ Bases:
sagemaker.model_card.helpers._DefaultToRequestDict
,sagemaker.model_card.helpers._DefaultFromDict
Hyper-Parameters data.
Initialize a HyperParameter object.