class_docstr: An implementation of PairRE from [chao2020]_.
  
  ---
  citation:
      author: Chao
      year: 2020
      link: http://arxiv.org/abs/2011.03798
      github: alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE
class_docstr_tok: ["An","implementation","of","PairRE","from","[","chao2020","]","_",".","--","-","citation",":","author",":","Chao","year",":","2020","link",":","http",":","\/\/arxiv.org\/abs\/2011.03798","github",":","alipay\/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE"]
docstr: Update kwargs by dimension-based default init range.
docstr_tok: ["Update","kwargs","by","dimension-based","default","init","range","."]
code: def _update_embedding_init_with_default(
      init_kwargs: Optional[Mapping[str, Any]],
      embedding_dim: int,
  ) -> Mapping[str, float]:
      """Update kwargs by dimension-based default init range."""
      init_kwargs = dict(init_kwargs or {})
      embedding_range = 14 / embedding_dim
      init_kwargs.setdefault("a", -embedding_range)
      init_kwargs.setdefault("b", embedding_range)
      return init_kwargs
  
file_path: pykeen/src/pykeen/models/unimodal/pair_re.py
imports: from typing import Any, ClassVar, Mapping, Optional, Type
  from torch.nn import functional
  from torch.nn.init import uniform_
  from ..nbase import ERModel
  from ...constants import DEFAULT_EMBEDDING_HPO_EMBEDDING_DIM_RANGE
  from ...losses import Loss, NSSALoss
  from ...nn.modules import PairREInteraction
  from ...typing import Hint, Initializer, Normalizer
label_desc: Use image node_id 2 for calling the PairRE obj's underlying member method code with example usage: obj._update_embedding_init_with_default(init_kwargs, embedding_dim) and returns: init_kwargs