I am new in coding pyton/pytorch… and I have a hard time in using pytorch lstm layers for predicting a high dimensional sequence. Let’s say I have a matrix of size 5* 10 of integer numbers as my data. This means sequence length is 10 and each point of my sequence has 5 features.

My goal is to build a network to predict this sequence. Let say I am going to feed two pints of this sequence (2*5) at each time to my network and network return me same size (2*5) just one step ahead in the sequence. Therefore data is something like

```
X=torch.LongTensor(5,10).random_(0, 10)) # 5 number of features and 10 size of sequence
```

My main problem is how to feed this data to my model? I find following code somewhere and change it a little bit. I read many posts about this issue but still confuse how to feed my data to this model

```
class LSTM(nn.Module):
def __init__(self, input_dim, hidden_dim, batch_size, output_dim=1,num_layers=2):
super(LSTM, self).__init__()
self.input_dim = input_dim
self.hidden_dim = hidden_dim
self.batch_size = batch_size
self.num_layers = num_layers
# LSTM layer
self.lstm = nn.LSTM(self.input_dim, self.hidden_dim, self.num_layers)
# output layer
self.linear = nn.Linear(self.hidden_dim, output_dim)
def init_hidden(self):
return (torch.zeros(self.num_layers, self.batch_size, self.hidden_dim),
torch.zeros(self.num_layers, self.batch_size, self.hidden_dim))
def forward(self, input):
lstm_out, self.hidden = self.lstm(input.view(len(input), self.batch_size, -1))
y_pred = self.linear(lstm_out[-1].view(self.batch_size, -1))
return y_pred.view(-1)
model = LSTM(lstm_input_size, h1, batch_size=num_train, output_dim=output_dim, num_layers=num_layers)
loss_fn = torch.nn.MSELoss(size_average=False)
optimiser = torch.optim.Adam(model.parameters(), lr=learning_rate)
# Training
for t in range(num_epochs):
model.zero_grad()
model.hidden = model.init_hidden()
# Forward pass
y_pred = model(x_train)
loss = loss_fn(x_train, x_train)
optimiser.zero_grad()
loss.backward()
optimiser.step()
```

Any help appreciated. Also if have any other suggestion to predict such a sequence please let me know. thank you