class_docstr: Implementation of MultiClass likelihood, which is used for multi-class
  classification problems.
  
  MultiClass likelihood uses :class:`~pyro.distributions.Categorical`
  distribution, so ``response_function`` should normalize its input's rightmost axis.
  By default, we use `softmax` function.
  
  :param int num_classes: Number of classes for prediction.
  :param callable response_function: A mapping to correct domain for MultiClass
      likelihood.
code: def __init__(self, num_classes, response_function=None):
      super().__init__()
      self.num_classes = num_classes
      self.response_function = (
          _softmax if response_function is None else response_function
      )
  
file_path: pyro/pyro/contrib/gp/likelihoods/multi_class.py
imports: import torch.nn.functional
  import pyro
  import pyro.distributions
  from pyro.contrib.gp.likelihoods.likelihood import Likelihood
label_desc: Use image node_id 1 to create a new MultiClass object from inherited base classes: Likelihood with example: obj = MultiClass(num_classes, response_function)