code: def test(data):
      model.eval()
      out = model(
          data.x_dict,
          data.edge_index_dict,
          data["user", "movie"].edge_label_index,
      ).clamp(min=0, max=5)
      rmse = F.mse_loss(out, data["user", "movie"].edge_label).sqrt()
      return float(rmse)
  
imports: import os.path
  import torch
  import torch.nn.functional
  from torch.nn import Embedding, Linear
  import torch_geometric.transforms
  from torch_geometric.datasets import MovieLens
  from torch_geometric.nn import SAGEConv
  from torch_geometric.nn.conv.gcn_conv import gcn_norm
label_desc: Use image node_id 2 for calling a global function with example usage: test(data) and returns: float