[lstm](https://docs.pytorch.org/docs/stable/generated/torch.nn.LSTM.html#torch.nn.LSTM "torch.nn.LSTM") = [nn.LSTM](https://docs.pytorch.org/docs/stable/generated/torch.nn.LSTM.html#torch.nn.LSTM "torch.nn.LSTM")(3, 3)  # Input dim is 3, output dim is 3
[inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = [[torch.randn](https://docs.pytorch.org/docs/stable/generated/torch.randn.html#torch.randn "torch.randn")(1, 3) for _ in range(5)]  # make a sequence of length 5

# initialize the hidden state.
hidden = ([torch.randn](https://docs.pytorch.org/docs/stable/generated/torch.randn.html#torch.randn "torch.randn")(1, 1, 3),
          [torch.randn](https://docs.pytorch.org/docs/stable/generated/torch.randn.html#torch.randn "torch.randn")(1, 1, 3))
for [i](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") in [inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"):
    # Step through the sequence one element at a time.
    # after each step, hidden contains the hidden state.
    [out](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"), hidden = [lstm](https://docs.pytorch.org/docs/stable/generated/torch.nn.LSTM.html#torch.nn.LSTM "torch.nn.LSTM")([i](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor").view(1, 1, -1), hidden)

# alternatively, we can do the entire sequence all at once.
# the first value returned by LSTM is all of the hidden states throughout
# the sequence. the second is just the most recent hidden state
# (compare the last slice of "out" with "hidden" below, they are the same)
# The reason for this is that:
# "out" will give you access to all hidden states in the sequence
# "hidden" will allow you to continue the sequence and backpropagate,
# by passing it as an argument  to the lstm at a later time
# Add the extra 2nd dimension
[inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = [torch.cat](https://docs.pytorch.org/docs/stable/generated/torch.cat.html#torch.cat "torch.cat")([inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor")).view(len([inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor")), 1, -1)
hidden = ([torch.randn](https://docs.pytorch.org/docs/stable/generated/torch.randn.html#torch.randn "torch.randn")(1, 1, 3), [torch.randn](https://docs.pytorch.org/docs/stable/generated/torch.randn.html#torch.randn "torch.randn")(1, 1, 3))  # clean out hidden state
[out](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"), hidden = [lstm](https://docs.pytorch.org/docs/stable/generated/torch.nn.LSTM.html#torch.nn.LSTM "torch.nn.LSTM")([inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"), hidden)
print([out](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"))
print(hidden)