langtest.transform.toxicity.ToxicityTypes#

class ToxicityTypes#

Bases: BaseToxicity

Class for toxicity types

__init__()#

Methods

__init__()
async_run(sample_list, model, *args, **kwargs)	Computes the toxicity completion on the samples in async mode.
run(sample_list, model, *args, **kwargs)	Computes the toxicity completion on the samples
transform(sample_list, test_name)	Method that implements prompt toxicity transformations on the given samples

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, *args, **kwargs)#

Computes the toxicity completion on the samples in async mode.

Parameters:

• sample_list (List[Sample]) – list of samples to compute toxicity on

• model (ModelAPI) – model to use for toxicity completion

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

Computes the toxicity completion on the samples

Parameters:

• sample_list (List[Sample]) – list of samples to compute toxicity on

• model (ModelAPI) – model to use for toxicity completion

static transform(sample_list: List[Sample], test_name) → List[Sample]#

Method that implements prompt toxicity transformations on the given samples

Parameters:

sample_list (List[Sample]) – list of samples to compute toxicity prompt on

Returns:

list of transformed samples

Return type:

List[Sample]