code: def _np_kernel_matrix_fn(amp, length_scale, x, y):
      x = np.expand_dims(x, -2)[..., 0]
      y = np.expand_dims(y, -3)[..., 0]
      return amp**2 * np.exp(
          -0.5 * ((x - y) ** 2) / (length_scale**2)
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import variational_gaussian_process
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import exponentiated_quadratic
label_desc: Use image node_id 1 for calling a global function with example usage: _np_kernel_matrix_fn(amp, length_scale, x, y) and returns: unknown