code: def reset_parameters(self):
      self.embed_block1.reset_parameters()
      self.pool_block1.reset_parameters()
      for embed_block, pool_block in zip(
          self.embed_blocks, self.pool_blocks
      ):
          embed_block.reset_parameters()
          pool_block.reset_parameters()
      self.jump.reset_parameters()
      self.lin1.reset_parameters()
      self.lin2.reset_parameters()
  
file_path: pytorch_geometric/benchmark/kernel/diff_pool.py
imports: from math import ceil
  import torch
  import torch.nn.functional
  from torch.nn import Linear
  from torch_geometric.nn import DenseSAGEConv, JumpingKnowledge, dense_diff_pool
label_desc: Use image node_id 2 for calling the DiffPool obj's underlying member method code with example usage: obj.reset_parameters() without return types