code: def kernel(X, Z, eta1, eta2, c):
      eta1sq, eta2sq = eta1.pow(2.0), eta2.pow(2.0)
      k1 = 0.5 * eta2sq * (1.0 + dot(X, Z)).pow(2.0)
      k2 = -0.5 * eta2sq * dot(X.pow(2.0), Z.pow(2.0))
      k3 = (eta1sq - eta2sq) * dot(X, Z)
      k4 = c**2 - 0.5 * eta2sq
      return k1 + k2 + k3 + k4
  
file_path: pyro/examples/sparse_regression.py
imports: import argparse
  import math
  import numpy
  import torch
  from torch.optim import Adam
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.infer import Trace_ELBO
  from pyro.infer.autoguide import AutoDelta, init_to_median
label_desc: Use image node_id 2 for calling a global function with example usage: kernel(X, Z, eta1, eta2, c) and returns: unknown