"""Implementation of TransF."""
from collections.abc import Mapping
from typing import Any, ClassVar, Optional
from ..nbase import ERModel
from ...constants import DEFAULT_EMBEDDING_HPO_EMBEDDING_DIM_RANGE
from ...nn.modules import TransFInteraction
from ...typing import FloatTensor, Hint, Initializer, Normalizer
__all__ = [
"TransF",
]
[docs]
class TransF(ERModel[FloatTensor, FloatTensor, FloatTensor]):
r"""An implementation of TransF from [feng2016]_.
This model represents both entities and relations as $d$-dimensional vectors stored in an
:class:`~pykeen.nn.representation.Embedding` matrix. The representations are then passed
to the :class:`~pykeen.nn.modules.TransFInteraction` function to obtain scores.
---
citation:
author: Feng
year: 2016
link: https://www.aaai.org/ocs/index.php/KR/KR16/paper/view/12887
arxiv: 1505.05253
"""
#: The default strategy for optimizing the model's hyper-parameters
hpo_default: ClassVar[Mapping[str, Any]] = dict(
embedding_dim=DEFAULT_EMBEDDING_HPO_EMBEDDING_DIM_RANGE,
)
def __init__(
self,
embedding_dim: int = 128,
entity_initializer: Hint[Initializer] = None,
entity_initializer_kwargs: Optional[Mapping[str, Any]] = None,
entity_normalizer: Hint[Normalizer] = None,
entity_normalizer_kwargs: Optional[Mapping[str, Any]] = None,
relation_initializer: Hint[Initializer] = None,
relation_initializer_kwargs: Optional[Mapping[str, Any]] = None,
**kwargs,
) -> None:
r"""Initialize the model.
:param embedding_dim: The entity embedding dimension $d$.
:param entity_initializer: Entity initializer function. Defaults to :func:`torch.nn.init.uniform_`
:param entity_initializer_kwargs: Keyword arguments to be used when calling the entity initializer
:param entity_normalizer: Entity normalizer function. Defaults to :func:`torch.nn.functional.normalize`
:param entity_normalizer_kwargs: Keyword arguments to be used when calling the entity normalizer
:param relation_initializer: Relation initializer function. Defaults to :func:`torch.nn.init.uniform_`
:param relation_initializer_kwargs: Keyword arguments to be used when calling the relation initializer
:param kwargs: Remaining keyword arguments passed through to :class:`pykeen.models.ERModel`.
"""
super().__init__(
interaction=TransFInteraction,
entity_representations_kwargs=dict(
shape=embedding_dim,
initializer=entity_initializer,
initializer_kwargs=entity_initializer_kwargs,
normalizer=entity_normalizer,
normalizer_kwargs=entity_normalizer_kwargs,
),
relation_representations_kwargs=dict(
shape=embedding_dim,
initializer=relation_initializer,
initializer_kwargs=relation_initializer_kwargs,
),
**kwargs,
)