Hi thank you so much for sharing your work. I am trying to recreate the results. I am using the CMU-MOSEi dataset you provided . The code has an error on GPU, but no problem on CPU. So I find out in rnn.py has some issue so I fix out to make sure x and lengths are in the same device:
class PackSequence(nn.Module):
def __init__(self, batch_first=True, device="cpu",):
super(PackSequence, self).__init__()
self.batch_first = batch_first
self.device = device
def forward(self, x, lengths):
x = pack_padded_sequence(
x, lengths, batch_first=self.batch_first, enforce_sorted=False
)
lengths = lengths.to(self.device)
lengths = lengths[x.sorted_indices]
return x, lengths
But I get NaN out from Train Loss . Could you please suggest why this happened.
return loss_value:4.928342342376709
Epoch [1/100]: [1/511] 0%| , Train Loss=4.93 [00:00<?]
return loss_value:nan
Epoch [1/100]: [2/511] 0%| , Train Loss=nan [00:00<00:54]
return loss_value:nan
Epoch [1/100]: [2/511] 0%| , Train Loss=nan [00:00<00:54]
return loss_value:nan
Epoch [1/100]: [4/511] 1%|▏ , Train Loss=nan [00:00<00:42]
return loss_value:nan
Epoch [1/100]: [4/511] 1%|▏ , Train Loss=nan [00:00<00:42]
return loss_value:nan
Epoch [1/100]: [6/511] 1%|▎ , Train Loss=nan [00:00<00:38]
return loss_value:nan
Epoch [1/100]: [6/511] 1%|▎ , Train Loss=nan [00:00<00:38]
Hi thank you so much for sharing your work. I am trying to recreate the results. I am using the CMU-MOSEi dataset you provided . The code has an error on GPU, but no problem on CPU. So I find out in rnn.py has some issue so I fix out to make sure x and lengths are in the same device:
But I get NaN out from Train Loss . Could you please suggest why this happened.