Hello! If I want the feature_dimension in the output of gwnet in model.py to be 2 (the default feature_dimension=1 in the source code), how should I modify the gwnet part?
Additionally, I have a question: I understand that the convolution operations in gwnet are performed along the feature dimension, and the output shape of the model is [batch_size, feature_dim, num_nodes, seq_len] where feature_dimension=12 and seq_len=1. However, in line 18 of engine.py, the output is transposed directly, changing the feature dimension to the seq_len dimension. I wonder if this handling is reasonable.
Hello! If I want the feature_dimension in the output of
gwnetinmodel.pyto be 2 (the default feature_dimension=1 in the source code), how should I modify thegwnetpart? Additionally, I have a question: I understand that the convolution operations ingwnetare performed along the feature dimension, and the output shape of the model is [batch_size, feature_dim, num_nodes, seq_len] where feature_dimension=12 and seq_len=1. However, in line 18 ofengine.py, the output is transposed directly, changing the feature dimension to the seq_len dimension. I wonder if this handling is reasonable.