code: def _conditional_variance(
      self, X: TensorType, F: TensorType
  ) -> tf.Tensor:
      p = self.conditional_mean(X, F)
      return p - (p**2)
  
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 6 for calling the Bernoulli obj's underlying member method code with example usage: obj._conditional_variance(X, F) and returns: unknown