class_docstr: Compute a classification report as a metric.
  
  Args:
      num_classes (int): the number of classes.
class_docstr_tok: ["Compute","a","classification","report","as","a","metric",".","Args",":","num_classes","(","int",")",":","the","number","of","classes","."]
code: def reset(self):
      self.class_data = np.zeros([self.num_classes, self.num_classes])
  
imports: import dataclasses
  import math
  import warnings
  from collections import defaultdict
  import numpy
  import torch
  from sklearn.metrics import confusion_matrix, auc
  from baal.utils.array_utils import to_prob
label_desc: Use image node_id 2 for calling the ClassificationReport obj's underlying member method code with example usage: obj.reset() without return types