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 __init__(self, num_classes):
      self.num_classes = num_classes
      super().__init__(average=False)
  
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 1 to create a new ClassificationReport object from inherited base classes: Metrics with example: obj = ClassificationReport(num_classes)