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kolena.workflow.Model#

Model(name, infer=None, metadata=None, tags=None) #

Bases: Frozen, WithTelemetry

The descriptor of a model tested on Kolena. A model is a deterministic transformation from TestSample inputs to Inference outputs.

Rather than importing this class directly, use the Model type definition returned from define_workflow.

workflow: Workflow instance-attribute #

The workflow of this model. Automatically populated when constructing via the model type returned from define_workflow.

name: str instance-attribute #

Unique name of the model.

metadata: Dict[str, Any] instance-attribute #

Unstructured metadata associated with the model.

tags: Set[str] instance-attribute #

Tags associated with this model.

infer: Optional[Callable[[TestSample], Inference]] instance-attribute #

Function transforming a TestSample for a workflow into an Inference object. Required when using test or TestRun.run.

create(name, infer=None, metadata=None, tags=None) classmethod #

Create a new model.

Parameters:

Name Type Description Default
name str

The unique name of the new model to create.

required
infer Optional[Callable[[TestSample], Inference]]

Optional inference function for this model.

None
metadata Optional[Dict[str, Any]]

Optional unstructured metadata to store with this model.

None
tags Optional[Set[str]]

Optional set of tags to associate with this model.

None

Returns:

Type Description
Model

The newly created model.

load(name, infer=None) classmethod #

Load an existing model.

Parameters:

Name Type Description Default
name str

The name of the model to load.

required
infer Optional[Callable[[TestSample], Inference]]

Optional inference function for this model.

None

load_all(*, tags=None) classmethod #

Load all models with this workflow.

Parameters:

Name Type Description Default
tags Optional[Set[str]]

Optionally specify a set of tags to apply as a filter. The loaded models will include only models with tags matching each of these specified tags, i.e. model.tags.intersection(tags) == tags.

None

Returns:

Type Description
List[Model]

The models within this workflow, filtered by tags when specified.

load_inferences(test_case) #

Load all inferences stored for this model on the provided test case.

Parameters:

Name Type Description Default
test_case TestCase

The test case for which to load inferences.

required

Returns:

Type Description
List[Tuple[TestSample, GroundTruth, Inference]]

The ground truths and inferences for all test samples in the test case.

iter_inferences(test_case) #

Iterate over all inferences stored for this model on the provided test case.

Parameters:

Name Type Description Default
test_case TestCase

The test case over which to iterate inferences.

required

Returns:

Type Description
Iterator[Tuple[TestSample, GroundTruth, Inference]]

Iterator exposing the ground truths and inferences for all test samples in the test case.