python import torch import torch.nn.functional as F from torch_geometric.nn import GCNConv, GATConv from torch_geometric.data import Data from torch.nn.utils.rnn import pad_sequence class DynamicGNN(torch.nn.Mo
units , number of layers,subset (values of entries to be considered for embeddings),epochs ")hidden_units=32num_layers=4subset=34epochs=10v_emb,v_graph=vgcn.get_gcn_embeddings(hidden_units,train_df,source_label,target_label,epochs,num_layers,subset)print(v_emb.shape)returnv_emb,v_graph ...