Pads a packed batch of variable length sequences.
It is an inverse operation to nn_utils_rnn_pack_padded_sequence().
nn_utils_rnn_pad_packed_sequence( sequence, batch_first = FALSE, padding_value = 0, total_length = NULL )
sequence |
(PackedSequence): batch to pad |
batch_first |
(bool, optional): if |
padding_value |
(float, optional): values for padded elements. |
total_length |
(int, optional): if not |
The returned Tensor's data will be of size T x B x *, where T is the length
of the longest sequence and B is the batch size. If batch_first is TRUE,
the data will be transposed into B x T x * format.
Tuple of Tensor containing the padded sequence, and a Tensor
containing the list of lengths of each sequence in the batch.
Batch elements will be re-ordered as they were ordered originally when
the batch was passed to nn_utils_rnn_pack_padded_sequence() or
nn_utils_rnn_pack_sequence().
total_length is useful to implement the
pack sequence -> recurrent network -> unpack sequence pattern in a
nn_module wrapped in ~torch.nn.DataParallel.
if (torch_is_installed()) {
seq <- torch_tensor(rbind(c(1,2,0), c(3,0,0), c(4,5,6)))
lens <- c(2,1,3)
packed <- nn_utils_rnn_pack_padded_sequence(seq, lens, batch_first = TRUE,
enforce_sorted = FALSE)
packed
nn_utils_rnn_pad_packed_sequence(packed, batch_first=TRUE)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.