code: def _predict_log_density(
      self,
      X: TensorType,
      Fmu: TensorType,
      Fvar: TensorType,
      Y: TensorType,
  ) -> tf.Tensor:
      p = self.predict_mean_and_var(X, Fmu, Fvar)[0]
      return tf.reduce_sum(logdensities.bernoulli(Y, p), axis=-1)
  
imports: from typing import Any, Callable
  import numpy
  import tensorflow
  from check_shapes import check_shapes, inherit_check_shapes
  from ..None import logdensities
  from ..base import AnyNDArray, MeanAndVariance, Parameter, TensorType
  from ..config import default_float
  from ..utilities import positive, to_default_int
  from .base import ScalarLikelihood
  from .utils import inv_probit
label_desc: Use image node_id 4 for calling the Bernoulli obj's underlying member method code with example usage: obj._predict_log_density(X, Fmu, Fvar, Y) and returns: tf