Source code for pykeen.models.unimodal.mure

# -*- coding: utf-8 -*-

"""Implementation of MuRE."""

from typing import Any, ClassVar, Mapping, Optional

from torch.nn.init import normal_, uniform_, zeros_

from ..nbase import ERModel
from ...nn.modules import MuREInteraction
from ...typing import Hint, Initializer

__all__ = [

[docs]class MuRE(ERModel): r"""An implementation of MuRE from [balazevic2019b]_. --- citation: author: Balažević year: 2019 link: """ #: 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, p=dict(type=int, low=1, high=2), ) def __init__( self, *, embedding_dim: int = 200, p: int = 2, power_norm: bool = True, entity_initializer: Hint[Initializer] = normal_, entity_initializer_kwargs: Optional[Mapping[str, Any]] = None, entity_bias_initializer: Hint[Initializer] = zeros_, relation_initializer: Hint[Initializer] = normal_, relation_initializer_kwargs: Optional[Mapping[str, Any]] = None, relation_matrix_initializer: Hint[Initializer] = uniform_, relation_matrix_initializer_kwargs: Optional[Mapping[str, Any]] = None, **kwargs, ) -> None: r"""Initialize MuRE via the :class:`pykeen.nn.modules.MuREInteraction` interaction. :param embedding_dim: The entity embedding dimension $d$. Defaults to 200. Is usually $d \in [50, 300]$. :param p: The $l_p$ norm. Defaults to 2. :param power_norm: Should the power norm be used? Defaults to true. :param entity_initializer: Entity initializer function. Defaults to :func:`torch.nn.init.normal_` :param entity_initializer_kwargs: Keyword arguments to be used when calling the entity initializer :param entity_bias_initializer: Entity bias initializer function. Defaults to :func:`torch.nn.init.zeros_` :param relation_initializer: Relation initializer function. Defaults to :func:`torch.nn.init.normal_` :param relation_initializer_kwargs: Keyword arguments to be used when calling the relation initializer :param relation_matrix_initializer: Relation matrix initializer function. Defaults to :func:`torch.nn.init.uniform_` :param relation_matrix_initializer_kwargs: Keyword arguments to be used when calling the relation matrix initializer :param kwargs: Remaining keyword arguments passed through to :class:`pykeen.models.ERModel`. """ # comment: # # uses float64 super().__init__( interaction=MuREInteraction, interaction_kwargs=dict(p=p, power_norm=power_norm), entity_representations_kwargs=[ dict( shape=embedding_dim, initializer=entity_initializer, initializer_kwargs=entity_initializer_kwargs or dict( std=1.0e-03, ), ), # entity bias for head dict( shape=tuple(), # scalar initializer=entity_bias_initializer, ), # entity bias for tail dict( shape=tuple(), # scalar initializer=entity_bias_initializer, ), ], relation_representations_kwargs=[ # relation offset dict( shape=embedding_dim, initializer=relation_initializer, initializer_kwargs=relation_initializer_kwargs or dict( std=1.0e-03, ), ), # diagonal relation transformation matrix dict( shape=embedding_dim, initializer=relation_matrix_initializer, initializer_kwargs=relation_matrix_initializer_kwargs or dict( a=-1, b=1, ), ), ], **kwargs, )