class_docstr: An abstract class for computing link prediction retrieval metrics.
  
  Args:
      k (int): The number of top-:math:`k` predictions to evaluate against.
class_docstr_tok: ["An","abstract","class","for","computing","link","prediction","retrieval","metrics",".","Args",":","k","(","int",")",":","The","number","of","top-",":","math",":","`","k","`","predictions","to","evaluate","against","."]
docstr: Reset metric state variables to their default value.
docstr_tok: ["Reset","metric","state","variables","to","their","default","value","."]
code: def reset(self) -> "LinkPredMetric":
      r"""Reset metric state variables to their default value."""
      if WITH_TORCHMETRICS:
          super().reset()
      else:
          self.accum.zero_()
          self.total.zero_()
  
      return self
  
imports: from abc import ABC, abstractmethod
  from typing import Optional, Tuple, Union
  import torch
  from torch import Tensor
  from torch_geometric.utils import cumsum, scatter
label_desc: Use image node_id 4 for calling the LinkPredMetric obj's underlying member method code with example usage: obj.reset() and returns: self