class_docstr: A custom representation module with minimal implementation.
class_docstr_tok: ["A","custom","representation","module","with","minimal","implementation","."]
code: def __init__(self, num_entities: int, shape: Tuple[int, ...] = (2,)):
      super().__init__(max_id=num_entities, shape=shape)
      self.x = nn.Parameter(torch.rand(*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 1 to create a new CustomRepresentation object from inherited base classes: Representation with example: obj = CustomRepresentation(num_entities, shape)