I’m a newbie of LSTM network.

I’m training below data form. Data is 64bit and sequence_length is ‘4’

```
class LSTM(nn.Module):
def __init__(self, num_classes, input_size, hidden_size, num_layers, seq_length):
'''
:param num_classes: 1
:param input_size: 64
:param hidden_size: 2
:param num_layers: 1
:param seq_length: 4
'''
super(LSTM, self).__init__()
self.num_classes = num_classes
self.num_layers = num_layers
self.input_size = input_size
self.hidden_size = hidden_size
self.seq_length = seq_length
self.lstm = nn.LSTM(input_size=input_size, hidden_size=hidden_size,
num_layers=num_layers, batch_first=True)
self.fc = nn.Linear(hidden_size, num_classes)
def forward(self, x):
h_0 = Variable(torch.zeros(
self.num_layers, x.size(0), self.hidden_size))
c_0 = Variable(torch.zeros(
self.num_layers, x.size(0), self.hidden_size))
# Propagate input through LSTM
ula, (h_out, _) = self.lstm(x, (h_0, c_0))
h_out = h_out.view(-1, self.hidden_size)
out = self.fc(h_out)
return out
```

But it occurs me that

‘Using a target size (torch.Size([50656, 64])) that is different to the input size (torch.Size([50656, 1]))’

I have trouble to traininig.

Could you help me??

I’ll appreciate your help.