class_docstr: An abstract base class for implementing custom KGE models.
  
  Args:
      num_nodes (int): The number of nodes/entities in the graph.
      num_relations (int): The number of relations in the graph.
      hidden_channels (int): The hidden embedding size.
      sparse (bool, optional): If set to :obj:`True`, gradients w.r.t. to the
          embedding matrices will be sparse. (default: :obj:`False`)
docstr: Resets all learnable parameters of the module.
docstr_tok: ["Resets","all","learnable","parameters","of","the","module","."]
code: def reset_parameters(self):
      r"""Resets all learnable parameters of the module."""
      self.node_emb.reset_parameters()
      self.rel_emb.reset_parameters()
  
file_path: pytorch_geometric/torch_geometric/nn/kge/base.py
imports: from typing import Tuple
  import torch
  from torch import Tensor
  from torch.nn import Embedding
  from tqdm import tqdm
  from torch_geometric.nn.kge.loader import KGTripletLoader
label_desc: Use image node_id 2 for calling the KGEModel obj's underlying member method code with example usage: obj.reset_parameters() without return types