class_docstr: A custom representation module with minimal implementation.
class_docstr_tok: ["A","custom","representation","module","with","minimal","implementation","."]
code: def _plain_forward(
      self, indices: Optional[torch.LongTensor] = None
  ) -> torch.FloatTensor:  # noqa: D102
      n = self.max_id if indices is None else indices.shape[0]
      return self.x.unsqueeze(dim=0).repeat(n, *(1 for _ in self.shape))
  
file_path: pykeen/tests/mocks.py
imports: from typing import Iterable, Optional, Tuple
  import torch
  from torch import nn
  from pykeen.evaluation import Evaluator, MetricResults, RankBasedMetricResults
  from pykeen.nn import Representation
  from pykeen.typing import ExtendedTarget, MappedTriples, RankType, Target
label_desc: Use image node_id 2 for calling the CustomRepresentation obj's underlying member method code with example usage: obj._plain_forward(indices) and returns: self