code: def __call__(self, inputs, y_pred, y_true, is_val):
      y_pred_round = y_pred.round().long()
      self.correct_count += y_pred_round.eq(y_true).float().sum().item()
      self.total_count += len(y_pred)
      accuracy = (
          100.0 * float(self.correct_count) / float(self.total_count)
      )
      return accuracy
  
imports: import torch
  from .utils import th_matrixcorr
  from .meters.averagemeter import AverageMeter
  from .callbacks import Callback
  from .losses import lovaszloss, hingeloss, dice_coeff
label_desc: Use image node_id 3 for calling the BinaryAccuracy obj's underlying member method code with example usage: obj.__call__(inputs, y_pred, y_true, is_val) and returns: accuracy