Hi.

I have problem with printing weights between inputs and first layer.

```
class LSTMClassifier(nn.Module):
"""Very simple implementation of LSTM-based time-series classifier."""
def __init__(self, input_size, hidden_size, n_layers, output_size):
super().__init__()
self.hidden_size = hidden_size
self.n_layers = n_layers
self.rnn = nn.LSTM(input_size, hidden_size, n_layers, batch_first=True)
self.fc = nn.Linear(hidden_size, output_size)
self.batch_size = None
self.hidden = None
def forward(self, x):
h0, c0 = self.init_hidden(x)
out, (hn, cn) = self.rnn(x, (h0, c0))
out = self.fc(out[:, -1, :])
return out
def init_hidden(self, x):
h0 = torch.zeros(self.n_layers, x.size(0), self.hidden_size)
c0 = torch.zeros(self.n_layers, x.size(0), self.hidden_size)
return [t for t in (h0, c0)]
return y
```

I know how to do this with feedforward Neural Network but with LSTM it’s not working.

Thanks for help.