class_docstr: A class for representing a model's predicted probabilities for each class
  in a multi-class classification problem. This class is not meant to be used by users.
class_docstr_tok: ["A","class","for","representing","a","model","'s","predicted","probabilities","for","each","class","in","a","multi-class","classification","problem",".","This","class","is","not","meant","to","be","used","by","users","."]
code: def validate(self):
      pred_probs = self.data
      if pred_probs.ndim != 2:
          raise ValueError(
              "pred_probs must be a 2D array for multi-class classification"
          )
      if not np.all(pred_probs >= 0) or not np.all(pred_probs <= 1):
          raise ValueError(
              "pred_probs must be between 0 and 1 for multi-class classification"
          )
      if not np.allclose(np.sum(pred_probs, axis=1), 1):
          raise ValueError(
              "pred_probs must sum to 1 for each row for multi-class classification"
          )
  
file_path: cleanlab/cleanlab/datalab/internal/model_outputs.py
imports: from abc import ABC, abstractmethod
  import numpy
  from dataclasses import dataclass
label_desc: Use image node_id 1 for calling the MultiClassPredProbs obj's underlying member method code with example usage: obj.validate() without return types