code: def Kuu_generic(
      inducing_variable: InducingPoints,
      kernel: MultioutputKernel,
      *,
      jitter: float = 0.0,
  ) -> tf.Tensor:
      Kmm = kernel(
          inducing_variable.Z, full_cov=True, full_output_cov=True
      )
      M = tf.shape(Kmm)[0] * tf.shape(Kmm)[1]
      jittermat = jitter * tf.reshape(
          tf.eye(M, dtype=Kmm.dtype), tf.shape(Kmm)
      )
      return Kmm + jittermat
  
file_path: GPflow/gpflow/covariances/multioutput/kuus.py
imports: from typing import Union
  import tensorflow
  from check_shapes import check_shapes
  from ...inducing_variables import FallbackSeparateIndependentInducingVariables, FallbackSharedIndependentInducingVariables, InducingPoints
  from ...kernels import IndependentLatent, LinearCoregionalization, MultioutputKernel, SeparateIndependent, SharedIndependent
  from ..dispatch import Kuu
label_desc: Use image node_id 1 for calling a global function with example usage: Kuu_generic(inducing_variable, kernel) and returns: unknown