code: def load_plans(self, plan_path):
      with open(plan_path, "rb") as f:
          plans = pickle.load(f)
      if self.stage is None:
          assert len(list(plans["plans_per_stage"].keys())) == 1, (
              "If self.stage is None then there can be only one stage in the plans file. That seems to not be the "
              "case. Please specify which stage of the cascade must be trained"
          )
          self.stage = list(plans["plans_per_stage"].keys())[0]
      self.plans = plans
  
      stage_plans = self.plans["plans_per_stage"][self.stage]
  
      if "pool_op_kernel_sizes" not in stage_plans.keys():
          assert "num_pool_per_axis" in stage_plans.keys()
          self.print_to_log_file(
              "WARNING! old plans file with missing pool_op_kernel_sizes. Attempting to fix it..."
          )
          self.net_num_pool_op_kernel_sizes = []
          for i in range(max(self.net_pool_per_axis)):
              curr = []
              for j in self.net_pool_per_axis:
                  if (max(self.net_pool_per_axis) - j) <= i:
                      curr.append(2)
                  else:
                      curr.append(1)
              self.net_num_pool_op_kernel_sizes.append(curr)
      else:
          self.net_num_pool_op_kernel_sizes = stage_plans[
              "pool_op_kernel_sizes"
          ]
  
file_path: PaddleSeg/contrib/MedicalSeg/nnunet/losses/multiple_losses.py
imports: import pickle
  import numpy
  from paddle import nn
  from medicalseg.cvlibs import manager
label_desc: Use image node_id 2 for calling the MultipleLoss obj's underlying member method code with example usage: obj.load_plans(plan_path) without return types