code: def _log_prob(
      self, X: TensorType, F: TensorType, Y: TensorType
  ) -> tf.Tensor:
      hits = tf.equal(
          tf.expand_dims(tf.argmax(F, 1), 1), tf.cast(Y, tf.int64)
      )
      yes = (
          tf.ones(tf.shape(Y), dtype=default_float())
          - self.invlink.epsilon
      )
      no = (
          tf.zeros(tf.shape(Y), dtype=default_float())
          + self.invlink.eps_k1
      )
      p = tf.where(hits, yes, no)
      return tf.reduce_sum(tf.math.log(p), axis=-1)
  
imports: from typing import Any, Optional
  import numpy
  import tensorflow
  import tensorflow_probability
  from check_shapes import check_shapes, inherit_check_shapes
  from ..base import MeanAndVariance, Module, Parameter, TensorType
  from ..config import default_float
  from ..quadrature import hermgauss
  from ..utilities import to_default_float, to_default_int
  from .base import Likelihood, MonteCarloLikelihood
label_desc: Use image node_id 2 for calling the MultiClass obj's underlying member method code with example usage: obj._log_prob(X, F, Y) and returns: tf