langtest.transform.robustness.RandomizeOptions#

class RandomizeOptions#

Bases: BaseRobustness

__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[, prob, split_pattern])

Transforms the given sample list by randomizing the options in the input text :param sample_list: The list of samples to transform. :type sample_list: List[Sample] :param prob: The probability controlling the proportion of words to be perturbed. Defaults to 1.0, which means all samples will be transformed. :type prob: Optional[float].

Attributes

alias_name

supported_tasks

test_types

class TestConfig#

Bases: dict

clear() → None.  Remove all items from D.#
copy() → a shallow copy of D#
fromkeys(value=None, /)#

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)#

Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items#
keys() → a set-like object providing a view on D's keys#
pop(k[, d]) → v, remove specified key and return the corresponding value.#

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()#

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault(key, default=None, /)#

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) → None.  Update D from dict/iterable E and F.#

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values#
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], prob: float | None = 1.0, split_pattern: str = '\n|,') → List[Sample]#

Transforms the given sample list by randomizing the options in the input text :param sample_list: The list of samples to transform. :type sample_list: List[Sample] :param prob: 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 with options randomized.

Return type:

List[Sample]