langtest.transform.robustness.MultiplePerturbations#

class MultiplePerturbations#

Bases: BaseRobustness

A class for applying multiple perturbations to transform a sample list.

__init__()#

Methods

__init__()
async_run(sample_list, model, **kwargs)	Creates a task to run the robustness measure.
run(sample_list, model, **kwargs)	Abstract method that implements the robustness measure.
transform(sample_list, perturbations[, ...])	Transforms the given sample list by applying multiple perturbations.

Attributes

alias_name
supported_tasks
test_types

async classmethod async_run(sample_list: List[Sample], model: ModelAPI, **kwargs)#

Creates a task to run the robustness measure.

Parameters:

• sample_list (List[Sample]) – The input data to be transformed.

• model (ModelAPI) – The model to be used for evaluation.

• **kwargs – Additional arguments to be passed to the robustness measure.

Returns:

The task that runs the robustness measure.

Return type:

asyncio.Task

abstract async static run(sample_list: List[Sample], model: ModelAPI, **kwargs) → List[Sample]#

Abstract method that implements the robustness measure.

Parameters:

• sample_list (List[Sample]) – The input data to be transformed.

• model (ModelAPI) – The model to be used for evaluation.

• **kwargs – Additional arguments to be passed to the robustness measure.

Returns:

The transformed data based on the implemented robustness measure.

Return type:

List[Sample]

static transform(sample_list: List[Sample], perturbations: List[str], prob: float | None = 1.0, config=None) → List[Sample]#

Transforms the given sample list by applying multiple perturbations.

Parameters:

• sample_list (List[Sample]) – The list of samples to transform.

• perturbations (List[str]) – The list of perturbations to apply.

• prob (Optional[float]) – The probability controlling the proportion of words to be perturbed. Defaults to 1.0, which means all samples will be transformed.

Returns:

The transformed list of samples.

Return type:

transformed_list