Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

does match the last output.
• No, if you’re using a bidirectional network—you’re only getting the properly
aligned hidden states in the last output, so you’ll need to unpack it.
To unpack the actual sequence of hidden states for the shortest sequence, for
example, we could get the corresponding indices from the data tensor in the packed
output:
output_packed.data[[2, 5]] # x1 sequence
Output
tensor([[ 0.2911, -0.1811],
[ 0.3051, 0.7055]], grad_fn=<IndexBackward>)
But that would be extremely annoying so, no, you don’t have to.
Unpacking (to padded)
You can unpack a sequence using PyTorch’s
nn.utils.rnn.pad_packed_sequence(). The name does not help, I know; I would
rather call it unpack_sequence_to_padded() instead. Anyway, we can use it to
transform our packed output into a regular, yet padded, output:
output_unpacked, seq_sizes = \
rnn_utils.pad_packed_sequence(output_packed, batch_first=True)
output_unpacked, seq_sizes
Variable-Length Sequences | 661