code: def __call__(self, output: torch.Tensor, target: torch.Tensor):
      pred = output.view(-1) > 0
      target = target.view(-1)
  
      self.data.fn += ((pred == 0) & (target == 1)).sum().item()
      self.data.fp += ((pred == 1) & (target == 0)).sum().item()
      self.data.tn += ((pred == 0) & (target == 0)).sum().item()
      self.data.tp += ((pred == 1) & (target == 1)).sum().item()
  
file_path: labml/helpers/labml_helpers/metrics/recall_precision.py
imports: import dataclasses
  import torch
  from labml import tracker
  from .None import Metric
label_desc: Use image node_id 1 for calling the RecallPrecision obj's underlying member method code with example usage: obj.__call__(output, target) without return types