code: def test_periodic_kernel_compute(
      x1, x2, amplitude, length_scale, frequency
  ) -> None:
      tol = 1e-5
      batch_size = amplitude.shape[0]
      history_length_1 = x1.shape[0]
      history_length_2 = x2.shape[0]
      num_features = x1.shape[1]
      x1 = x1.reshape(batch_size, history_length_1, num_features)
      x2 = x2.reshape(batch_size, history_length_2, num_features)
      amplitude = amplitude.reshape(batch_size, 1, 1)
      length_scale = length_scale.reshape(batch_size, 1, 1)
      frequency = frequency.reshape(batch_size, 1, 1)
      periodic = PeriodicKernel(amplitude, length_scale, frequency)
  
      exact = nd.zeros((batch_size, history_length_1, history_length_2))
      for i in range(history_length_1):
          for j in range(history_length_2):
              val = (
                  2
                  * (
                      nd.sin(
                          frequency
                          * math.pi
                          * (x1[:, i, :] - x2[:, j, :])
                      )
                      / length_scale
                  )
                  ** 2
              )
              exact[:, i, j] = (amplitude * nd.exp(-val)).reshape(-1)
      res = periodic.kernel_matrix(x1, x2)
      assert nd.norm(res - exact) < tol
  
imports: import math
  import pytest
  from mxnet import nd
  from gluonts.mx.kernels import PeriodicKernel
label_desc: Use image node_id 2 for calling a global function with example usage: test_periodic_kernel_compute(x1, x2, amplitude, length_scale, frequency) without return types