code: def _laplace_kernel(x1, x2, batch=None):
      """The laplace kernel on scalar data."""
      mult = 1.0 if batch is None else np.linspace(1, 5, batch)
  
      return mult * np.exp(-math.fabs(x1 - x2))
  
imports: import math
  import sys
  from functools import partial
  import pytest
  import numpy
  import pennylane
  import pennylane.kernels
  from pennylane import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: _laplace_kernel(x1, x2, batch) and returns: unknown