class_docstr: A distance between neural networks based on solving a transportation problem. 
docstr: Gets a connectivity cost matrix. 
docstr_tok: ["Gets","a","connectivity","cost","matrix","."]
code: def get_struct_cost_matrix(self, x1, x2):
      """Gets a connectivity cost matrix."""
      (
          x1_bkwd_ip_dists,
          x1_fwd_op_dists,
      ) = x1.get_bkwd_ip_fwd_op_dists_of_all_layers(
          self.all_path_length_categories
      )
      (
          x2_bkwd_ip_dists,
          x2_fwd_op_dists,
      ) = x2.get_bkwd_ip_fwd_op_dists_of_all_layers(
          self.all_path_length_categories
      )
      bkwd_costs = self._get_cost_matrix_for_fwd_or_bkwd(
          x1_bkwd_ip_dists, x2_bkwd_ip_dists
      )
      fwd_costs = self._get_cost_matrix_for_fwd_or_bkwd(
          x1_fwd_op_dists, x2_fwd_op_dists
      )
      return (bkwd_costs + fwd_costs) / 2
  
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 5 for calling the OTMANNDistanceComputer obj's underlying member method code with example usage: obj.get_struct_cost_matrix(x1, x2) and returns: unknown