code: def __init__(self, in_channels, out_channels, msg_dim, time_enc):
      super().__init__()
      self.time_enc = time_enc
      edge_dim = msg_dim + time_enc.out_channels
      self.conv = TransformerConv(
          in_channels,
          out_channels // 2,
          heads=2,
          dropout=0.1,
          edge_dim=edge_dim,
      )
  
file_path: pytorch_geometric/examples/tgn.py
imports: import os.path
  import torch
  from sklearn.metrics import average_precision_score, roc_auc_score
  from torch.nn import Linear
  from torch_geometric.datasets import JODIEDataset
  from torch_geometric.loader import TemporalDataLoader
  from torch_geometric.nn import TGNMemory, TransformerConv
  from torch_geometric.nn.models.tgn import IdentityMessage, LastAggregator, LastNeighborLoader
label_desc: Use image node_id 1 to create a new GraphAttentionEmbedding object from inherited base classes: torch.nn with example: obj = GraphAttentionEmbedding(in_channels, out_channels, msg_dim, time_enc)