code: def _expectation_gaussian_linear(
      p: Gaussian,
      mean: Union[mfn.Linear, mfn.Constant],
      _: None,
      __: None,
      ___: None,
      nghp: None = None,
  ) -> tf.Tensor:
      """
      Compute the expectation:
      <m(X)>_p(X)
          - m(x) :: Linear, Identity or Constant mean function
  
      :return: NxQ
      """
      return mean(p.mu)
  
file_path: GPflow/gpflow/expectations/mean_functions.py
imports: from typing import Type, Union
  import tensorflow
  from check_shapes import check_shapes
  from ..None import mean_functions
  from ..probability_distributions import Gaussian
  from .None import dispatch
  from .expectations import expectation
label_desc: Use image node_id 1 for calling a global function with example usage: _expectation_gaussian_linear(p, mean, _, __, ___, nghp) and returns: mean