code: def _fast_hist(label_pred, label_true, num_classes):
      mask = (label_true >= 0) & (label_true < num_classes)
      hist = np.bincount(
          num_classes * label_true[mask].astype(int) + label_pred[mask],
          minlength=num_classes**2,
      ).reshape(num_classes, num_classes)
      return hist
  
imports: import os
  from math import ceil
  import numpy
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 4 for calling a global function with example usage: _fast_hist(label_pred, label_true, num_classes) and returns: hist