docstr: Returns the appropriate log prob integrand for quadrature.
  
  Quadrature expects f(X), here logp(F), to return shape [N_quad_points]
  + batch_shape + [d']. Here d'=1, but log_prob() only returns
  [N_quad_points] + batch_shape, so we add an extra dimension.
  
  Also see _quadrature_reduction.
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code: def _quadrature_log_prob(
      self, F: TensorType, X: TensorType, Y: TensorType
  ) -> tf.Tensor:
      """
      Returns the appropriate log prob integrand for quadrature.
  
      Quadrature expects f(X), here logp(F), to return shape [N_quad_points]
      + batch_shape + [d']. Here d'=1, but log_prob() only returns
      [N_quad_points] + batch_shape, so we add an extra dimension.
  
      Also see _quadrature_reduction.
      """
      return tf.expand_dims(self.log_prob(X, F, Y), axis=-1)
  
imports: import abc
  from typing import Any, Callable, Iterable, Optional, Sequence, Union
  import tensorflow
  from check_shapes import check_shapes, inherit_check_shapes
  from ..base import MeanAndVariance, Module, TensorType
  from ..quadrature import GaussianQuadrature, NDiagGHQuadrature, ndiag_mc
label_desc: Use image node_id 3 for calling the QuadratureLikelihood obj's underlying member method code with example usage: obj._quadrature_log_prob(F, X, Y) and returns: tf