class_docstr: Computes a kernel using the transportation distance as the distance. 
docstr: Computes gradient of kernel w.r.t the param 
docstr_tok: ["Computes","gradient","of","kernel","w.r.t","the","param"]
code: def _child_gradient(self, param, X1, X2, param_num=None):
      """Computes gradient of kernel w.r.t the param"""
      # TODO: Need to implement this.
      raise NotImplementedError("Should implement this gradient!")
  
imports: import numpy
  from .None import neural_network
  from ..gp.kernel import ExpSumOfDistsKernel, SumOfExpSumOfDistsKernel
  from ..utils.oper_utils import opt_transport
label_desc: Use image node_id 3 for calling the DistProdNNKernel obj's underlying member method code with example usage: obj._child_gradient(param, X1, X2, param_num) without return types