CrossEncoderOutput

class lightning_ir.cross_encoder.cross_encoder_model.CrossEncoderOutput(scores: Tensor | None = None, embeddings: Tensor | None = None)

Bases: LightningIROutput

Dataclass containing the output of a cross-encoder model

__init__(scores: Tensor | None = None, embeddings: Tensor | None = None) → None

Args:

Methods

__init__([scores, embeddings])

Args:

Attributes

embeddings

Joint query-document embeddings

clear() → None.  Remove all items from od.

copy() → a shallow copy of od

embeddings: Tensor | None = None

Joint query-document embeddings

fromkeys(value=None)

Create a new ordered 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

move_to_end(key, last=True)

Move an existing element to the end (or beginning if last is false).

Raise KeyError if the element does not exist.

pop(key[, default]) → 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(last=True)

Remove and return a (key, value) pair from the dictionary.

Pairs are returned in LIFO order if last is true or FIFO order if false.

setdefault(*args, **kwargs)

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.

to_tuple() → tuple[Any]

Convert self to a tuple containing all the attributes/keys that are not None.

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