I wanted to play around with RNN’s a bit, and was curious if LSTM could predict the next 2 number given a single number, e.g.

```
x = [1]
y = [2, 3]
```

For this, I tried the following:

```
def create_training_data(n):
x = torch.randint(0, 200, size=(n, 1), dtype=torch.float32, requires_grad=True)
y = torch.cat([x+1, x+2], dim=1)
return x, y
x, y = create_training_data(1000)
model= nn.Sequential(
nn.Linear(1, 10),
nn.ReLU(),
nn.LSTM(input_size=10, hidden_size=10),
nn.Linear(10, 2)
)
loss_fn = nn.MSELoss()
optimizer = torch.optim.SGD(model.parameters(), lr=0.01, momentum=0.9)
train = data_utils.TensorDataset(x, y)
train_dataloder = DataLoader(train, batch_size=64, shuffle=True)
for batch_idx, (x, y) in enumerate(train_dataloder):
res = model(x)
```

However, I get the error:

`TypeError: linear(): argument 'input' (position 1) must be Tensor, not tuple`

I do not understand why it is a tuple though, it should clearly be a tensor. What am I doing wrong?