no 'GraphAttention' function implementation

[jiyanbio]

class SequenceModel(nn.Module):
def init(self, num_letters, hidden_dim, num_layers=3,
vocab=20, top_k=30, num_positional_embeddings=16):
""" Graph labeling network """
super(SequenceModel, self).init()

    # Hyperparameters
    self.top_k = top_k
    self.hidden_dim = hidden_dim
    self.positional_embeddings = PositionalEmbeddings(num_positional_embeddings)

    # Embedding layers
    self.W_e = nn.Linear(num_positional_embeddings, hidden_dim, bias=True)
    self.W_s = nn.Embedding(vocab, hidden_dim)

    # Decoder
    self.decoder_layers = nn.ModuleList([
        **GraphAttention(hidden_dim, hidden_dim*3)**
        for _ in range(2 * num_layers)
    ])
    self.W_out = nn.Linear(hidden_dim, num_letters, bias=True)

    # Initialization
    for p in self.parameters():
        if p.dim() > 1:
            nn.init.xavier_uniform_(p)

[jingraham]

Ah, thanks. This was due to an incomplete refactor of the module names. I started a patch here that should fix it and will merge when I can test the code.