OK so is this correct?
> 
>     def forward(self, x)
>         b = x.size()[0]
>         out_batch = self.embedding(x.long())
>         # lstm - convert input to (seq_lengthxbatch sizexnum of features) dims
>         out_lstm, (h_t, o_t) = self.lstm(out_batch.view(-1, b, self.embedding_dim))
>         out_lstm = out_lstm[-1,:,:]
>         out_fc1 = self.fc1(out_lstm)
>         return out_fc1

where self.lstm = nn.LSTM(embedding_dim, hidden_dim_lstm, n_layers, batch_first=True)