sagemaker.core.shapes.model_card_shapes

Classes

AdditionalInformation(*[, ...])
BarChartMetric(*, name[, notes, type, ...])
BusinessDetails(*[, business_problem, ...])
ContainersItem(*[, model_data_url, image, ...])
EvaluationDetailsItem(*, name, ...)
Function(value)	An enumeration.
InferenceSpecification(*, containers)
IntendedUses(*[, purpose_of_model, ...])
LinearGraphMetric(*, name[, notes, type, ...])
MatrixMetric(*, name[, notes, type, ...])
MetricGroupsItem(*, name, metric_data)
ModelCardContent(*, model_overview, ...)
ModelOverview(*[, model_description, ...])
ObjectiveFunction(*[, function, facet, ...])
RiskRating(value)	An enumeration.
SimpleMetric(*, name[, notes, type, ...])
TrainingDetails(*[, objective_function, ...])
TrainingEnvironment(*[, container_image])
TrainingHyperParameter(*, name[, value])
TrainingJobDetails(*[, training_arn, ...])
TrainingMetric(*, name[, notes])

class sagemaker.core.shapes.model_card_shapes.AdditionalInformation(*, ethical_considerations: Annotated[str | None, MaxLen(max_length=2048)] = None, caveats_and_recommendations: Annotated[str | None, MaxLen(max_length=2048)] = None, custom_details: Dict[str, str] | None = None)

Bases: BaseModel

caveats_and_recommendations: str | None

custom_details: Dict[str, str] | None

ethical_considerations: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class sagemaker.core.shapes.model_card_shapes.BarChartMetric(*, name: Annotated[str, _PydanticGeneralMetadata(pattern='.{1,255}')], notes: Annotated[str | None, MaxLen(max_length=1024)] = None, type: Literal['bar_chart'] = None, value: List, x_axis_name: List[str] | None = None, y_axis_name: str | None = None)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

notes: str | None

type: Literal['bar_chart']

value: List

x_axis_name: List[str] | None

y_axis_name: str | None

class sagemaker.core.shapes.model_card_shapes.BusinessDetails(*, business_problem: Annotated[str | None, MaxLen(max_length=2048)] = None, business_stakeholders: Annotated[str | None, MaxLen(max_length=2048)] = None, line_of_business: Annotated[str | None, MaxLen(max_length=2048)] = None)

Bases: BaseModel

business_problem: str | None

business_stakeholders: str | None

line_of_business: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class sagemaker.core.shapes.model_card_shapes.ContainersItem(*, model_data_url: Annotated[str | None, MaxLen(max_length=1024)] = None, image: Annotated[str | None, MaxLen(max_length=255)] = None, nearest_model_name: str | None = None, model_data_source: ModelDataSource | None = None, is_checkpoint: bool | None = None, base_model: BaseModel | None = None)

Bases: BaseModel

base_model: BaseModel | None

image: str | None

is_checkpoint: bool | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_data_source: ModelDataSource | None

model_data_url: str | None

nearest_model_name: str | None

class sagemaker.core.shapes.model_card_shapes.EvaluationDetailsItem(*, name: ~typing.Annotated[str, _PydanticGeneralMetadata(pattern='.{1,63}')], evaluation_observation: ~typing.Annotated[str | None, ~annotated_types.MaxLen(max_length=2096)] = None, evaluation_job_arn: ~typing.Annotated[str | None, ~annotated_types.MaxLen(max_length=256)] = None, datasets: ~typing.Annotated[~typing.List[str] | None, ~annotated_types.MaxLen(max_length=10)] = None, metadata: ~typing.Dict[str, str] | None = None, metric_groups: ~typing.List[~sagemaker.core.shapes.model_card_shapes.MetricGroupsItem] | None = <factory>)

Bases: BaseModel

datasets: List[str] | None

evaluation_job_arn: str | None

evaluation_observation: str | None

metadata: Dict[str, str] | None

metric_groups: List[MetricGroupsItem] | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

class sagemaker.core.shapes.model_card_shapes.Function(value)

Bases: str, Enum

An enumeration.

MAXIMIZE = 'Maximize'

MINIMIZE = 'Minimize'

class sagemaker.core.shapes.model_card_shapes.InferenceSpecification(*, containers: List[ContainersItem])

Bases: BaseModel

containers: List[ContainersItem]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class sagemaker.core.shapes.model_card_shapes.IntendedUses(*, purpose_of_model: Annotated[str | None, MaxLen(max_length=2048)] = None, intended_uses: Annotated[str | None, MaxLen(max_length=2048)] = None, factors_affecting_model_efficiency: Annotated[str | None, MaxLen(max_length=2048)] = None, risk_rating: RiskRating | None = None, explanations_for_risk_rating: Annotated[str | None, MaxLen(max_length=2048)] = None)

Bases: BaseModel

explanations_for_risk_rating: str | None

factors_affecting_model_efficiency: str | None

intended_uses: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

purpose_of_model: str | None

risk_rating: RiskRating | None

class sagemaker.core.shapes.model_card_shapes.LinearGraphMetric(*, name: Annotated[str, _PydanticGeneralMetadata(pattern='.{1,255}')], notes: Annotated[str | None, MaxLen(max_length=1024)] = None, type: Literal['linear_graph'] = None, value: List, x_axis_name: str | None = None, y_axis_name: str | None = None)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

notes: str | None

type: Literal['linear_graph']

value: List

x_axis_name: str | None

y_axis_name: str | None

class sagemaker.core.shapes.model_card_shapes.MatrixMetric(*, name: Annotated[str, _PydanticGeneralMetadata(pattern='.{1,255}')], notes: Annotated[str | None, MaxLen(max_length=1024)] = None, type: Literal['matrix'] = None, value: List, x_axis_name: List[str] | None = None, y_axis_name: List[str] | None = None)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

notes: str | None

type: Literal['matrix']

value: List

x_axis_name: List[str] | None

y_axis_name: List[str] | None

class sagemaker.core.shapes.model_card_shapes.MetricGroupsItem(*, name: Annotated[str, _PydanticGeneralMetadata(pattern='.{1,63}')], metric_data: List[SimpleMetric | LinearGraphMetric | BarChartMetric | MatrixMetric])

Bases: BaseModel

metric_data: List[SimpleMetric | LinearGraphMetric | BarChartMetric | MatrixMetric]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

class sagemaker.core.shapes.model_card_shapes.ModelCardContent(*, model_overview: ~sagemaker.core.shapes.model_card_shapes.ModelOverview | None = None, intended_uses: ~sagemaker.core.shapes.model_card_shapes.IntendedUses | None = None, business_details: ~sagemaker.core.shapes.model_card_shapes.BusinessDetails | None = None, training_details: ~sagemaker.core.shapes.model_card_shapes.TrainingDetails | None = None, evaluation_details: ~typing.List[~sagemaker.core.shapes.model_card_shapes.EvaluationDetailsItem] | None = <factory>, additional_information: ~sagemaker.core.shapes.model_card_shapes.AdditionalInformation | None = None)

Bases: BaseModel

additional_information: AdditionalInformation | None

business_details: BusinessDetails | None

evaluation_details: List[EvaluationDetailsItem] | None

intended_uses: IntendedUses | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_overview: ModelOverview | None

training_details: TrainingDetails | None

class sagemaker.core.shapes.model_card_shapes.ModelOverview(*, model_description: Annotated[str | None, MaxLen(max_length=1024)] = None, model_creator: Annotated[str | None, MaxLen(max_length=1024)] = None, model_artifact: List[str] | None = None, algorithm_type: Annotated[str | None, MaxLen(max_length=1024)] = None, problem_type: str | None = None, model_owner: Annotated[str | None, MaxLen(max_length=1024)] = None)

Bases: BaseModel

algorithm_type: str | None

model_artifact: List[str] | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_creator: str | None

model_description: str | None

model_owner: str | None

problem_type: str | None

class sagemaker.core.shapes.model_card_shapes.ObjectiveFunction(*, function: Function | None = None, facet: Annotated[str | None, MaxLen(max_length=63)] = None, condition: Annotated[str | None, MaxLen(max_length=63)] = None)

Bases: BaseModel

condition: str | None

facet: str | None

function: Function | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class sagemaker.core.shapes.model_card_shapes.RiskRating(value)

Bases: str, Enum

An enumeration.

HIGH = 'High'

LOW = 'Low'

MEDIUM = 'Medium'

UNKNOWN = 'Unknown'

class sagemaker.core.shapes.model_card_shapes.SimpleMetric(*, name: Annotated[str, _PydanticGeneralMetadata(pattern='.{1,255}')], notes: Annotated[str | None, MaxLen(max_length=1024)] = None, type: Literal['number', 'string', 'boolean'] = None, value: float | str | bool, x_axis_name: str | None = None, y_axis_name: str | None = None)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

notes: str | None

type: Literal['number', 'string', 'boolean']

value: float | str | bool

x_axis_name: str | None

y_axis_name: str | None

class sagemaker.core.shapes.model_card_shapes.TrainingDetails(*, objective_function: ObjectiveFunction | None = None, training_observations: Annotated[str | None, MaxLen(max_length=1024)] = None, training_job_details: TrainingJobDetails | None = None)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

objective_function: ObjectiveFunction | None

training_job_details: TrainingJobDetails | None

training_observations: str | None

class sagemaker.core.shapes.model_card_shapes.TrainingEnvironment(*, container_image: List[str] | None = None)

Bases: BaseModel

container_image: List[str] | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class sagemaker.core.shapes.model_card_shapes.TrainingHyperParameter(*, name: Annotated[str, _PydanticGeneralMetadata(pattern='.{1,255}')], value: Annotated[str | None, _PydanticGeneralMetadata(pattern='.{0,255}')] = None)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

value: str | None

class sagemaker.core.shapes.model_card_shapes.TrainingJobDetails(*, training_arn: Annotated[str | None, MaxLen(max_length=1024)] = None, training_datasets: List[str] | None = None, training_environment: TrainingEnvironment | None = None, training_metrics: List[TrainingMetric] | None = None, user_provided_training_metrics: List[TrainingMetric] | None = None, hyper_parameters: List[TrainingHyperParameter] | None = None, user_provided_hyper_parameters: List[TrainingHyperParameter] | None = None)

Bases: BaseModel

hyper_parameters: List[TrainingHyperParameter] | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

training_arn: str | None

training_datasets: List[str] | None

training_environment: TrainingEnvironment | None

training_metrics: List[TrainingMetric] | None

user_provided_hyper_parameters: List[TrainingHyperParameter] | None

user_provided_training_metrics: List[TrainingMetric] | None

class sagemaker.core.shapes.model_card_shapes.TrainingMetric(*, name: Annotated[str, _PydanticGeneralMetadata(pattern='.{1,255}')], notes: Annotated[str | None, MaxLen(max_length=1024)] = None, value: float)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

notes: str | None

value: float