mianzhang / dialogue_gcn Goto Github PK

Hi, I'm running my own dataset using your code and the result is only 0.3 F1-macro, I'd like to ask you what do you think are the reasons? There are 7 classes in the dataset, then the text feature is a 768-dimensional tensor extracted using bert, and this dataset is a Chinese dataset.

/dgcn/model/functions.py
Line 17: edge_ind.append(edge_perms(lengths[j].cpu().item(), wp, wf))
Line 24: perms = edge_perms(cur_len, wp, wf)

Maybe the perms in line 24 can be assigned directly by edge_ind calculate in Line 17?
Is there any difference?

As title, may I know the difference with this implementation version with the original one?
https://github.com/declare-lab/conv-emotion/tree/master/DialogueGCN

Thanks.

i have downloaded iemocap yet found no pkl for utils to load_pkl.
is there any necessary process missing ?
.first time using this dataset

I am trying to use dialogueGCN for establishing baseline for my model, but I cannot run the code-
while executing ./scripts/iemocap.sh train

Error: RuntimeError: 'lengths' argument should be a 1D CPU int64 tensor, but got 1D cuda:1 Long tensor

Error log-
Traceback (most recent call last):
File "train.py", line 93, in
main(args)
File "train.py", line 35, in main
ret = coach.train()
File "/mnt/berry/home/prakhar/dialoguegcn/conv-emotion/DialogueGCN-mianzhang/dgcn/Coach.py", line 41, in train
self.train_epoch(epoch)
File "/mnt/berry/home/prakhar/dialoguegcn/conv-emotion/DialogueGCN-mianzhang/dgcn/Coach.py", line 74, in train_epoch
nll = self.model.get_loss(data)
File "/mnt/berry/home/prakhar/dialoguegcn/conv-emotion/DialogueGCN-mianzhang/dgcn/model/DialogueGCN.py", line 59, in get_loss
graph_out, features = self.get_rep(data)
File "/mnt/berry/home/prakhar/dialoguegcn/conv-emotion/DialogueGCN-mianzhang/dgcn/model/DialogueGCN.py", line 43, in get_rep
node_features = self.rnn(data["text_len_tensor"], data["text_tensor"]) # [batch_size, mx_len, D_g]
File "/mnt/berry/home/prakhar/dialoguegcn/conv-emotion/DialogueGCN-mianzhang/cudagcn/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/mnt/berry/home/prakhar/dialoguegcn/conv-emotion/DialogueGCN-mianzhang/dgcn/model/SeqContext.py", line 20, in forward
packed = pack_padded_sequence(
File "/mnt/berry/home/prakhar/dialoguegcn/conv-emotion/DialogueGCN-mianzhang/cudagcn/lib/python3.8/site-packages/torch/nn/utils/rnn.py", line 249, in pack_padded_sequence
_VF._pack_padded_sequence(input, lengths, batch_first)
RuntimeError: 'lengths' argument should be a 1D CPU int64 tensor, but got 1D cuda:1 Long tensor