code: def __init__(self, in_channels, out_channels, cache=False):
      super(SimpleConv, self).__init__(aggr="add")
      self.cache = cache
      self.reset_cache()
  
file_path: deepsnap/examples/graph_classification/skip_models.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torch_geometric.nn
  import torch_geometric.utils
label_desc: Use image node_id 1 to create a new SimpleConv object from inherited base classes: pyg_nn with example: obj = SimpleConv(in_channels, out_channels, cache)