class_docstr: An implementation of the Unstructured Model (UM) published by [bordes2014]_.
  
  UM computes the distance between head and tail entities then applies the $l_p$ norm.
  
  .. math::
  
      f(h, r, t) = - \|\textbf{e}_h  - \textbf{e}_t\|_p^2
  
  A small distance between the embeddings for the head and tail entity indicates a plausible triple. It is
  appropriate for networks with a single relationship type that is undirected.
  
  .. warning::
  
      In UM, neither the relations nor the directionality are considered, so it can't distinguish between them.
      However, it may serve as a baseline for comparison against relation-aware models.
  ---
  name: Unstructured Model
  citation:
      author: Bordes
      year: 2014
      link: https://link.springer.com/content/pdf/10.1007%2Fs10994-013-5363-6.pdf
docstr: Initialize UM.
  
  :param embedding_dim: The entity embedding dimension $d$. Is usually $d \in [50, 300]$.
  :param scoring_fct_norm: The $l_p$ norm. Usually 1 for UM.
  :param entity_initializer: The initializer for the entity embeddings.
      Defaults to the xavier normal distribution.
  :param kwargs: Remaining keyword arguments passed through to :class:`pykeen.models.ERModel`.
code: def __init__(
      self,
      *,
      embedding_dim: int = 50,
      scoring_fct_norm: int = 1,
      entity_initializer: Hint[Initializer] = xavier_normal_,
      **kwargs,
  ) -> None:
      r"""Initialize UM.
  
      :param embedding_dim: The entity embedding dimension $d$. Is usually $d \in [50, 300]$.
      :param scoring_fct_norm: The $l_p$ norm. Usually 1 for UM.
      :param entity_initializer: The initializer for the entity embeddings.
          Defaults to the xavier normal distribution.
      :param kwargs: Remaining keyword arguments passed through to :class:`pykeen.models.ERModel`.
      """
      super().__init__(
          interaction=UMInteraction,
          interaction_kwargs=dict(p=scoring_fct_norm),
          entity_representations_kwargs=dict(
              shape=embedding_dim,
              initializer=entity_initializer,
          ),
          relation_representations=[],
          **kwargs,
      )
  
file_path: pykeen/src/pykeen/models/unimodal/unstructured_model.py
imports: from typing import Any, ClassVar, Mapping
  from ..nbase import ERModel
  from ...constants import DEFAULT_EMBEDDING_HPO_EMBEDDING_DIM_RANGE
  from ...nn.init import xavier_normal_
  from ...nn.modules import UMInteraction
  from ...typing import Hint, Initializer
label_desc: Use image node_id 1 to create a new UM object from inherited base classes: ERModel with example: obj = UM()