inputs = Variable(torch.Tensor([[h, e, l, l, o]]))
print("input size", inputs.size())
for one in inputs[0]:
one = one.view(1, 1, -1)
// Input: (batch, seq_len, input_size) when batch_first=True
out, hidden = cell(one, hidden)
After Change
// We can do the whole at once
// Propagate input through RNN
// Input: (batch, seq_len, input_size) when batch_first=True
inputs = inputs.view(1, 5, -1)
out, hidden = cell(inputs, hidden)
print("sequence input size", inputs.size(), "out size", out.size())
