Pads a packed batch of variable length sequences.

It is an inverse operation to nn_utils_rnn_pack_padded_sequence().

Usage

nn_utils_rnn_pad_packed_sequence(
  sequence,
  batch_first = FALSE,
  padding_value = 0,
  total_length = NULL
)

Arguments

sequence

(PackedSequence): batch to pad

batch_first

(bool, optional): if True, the output will be in “B x T x *` format.

padding_value

(float, optional): values for padded elements.

total_length

(int, optional): if not NULL, the output will be padded to have length total_length. This method will throw ValueError if total_length is less than the max sequence length in sequence.

Value

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().

Details

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.

Note

total_length is useful to implement the pack sequence -> recurrent network -> unpack sequence pattern in a nn_module wrapped in ~torch.nn.DataParallel.

Examples

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)
}
#> [[1]]
#> torch_tensor
#>  1  2  0
#>  3  0  0
#>  4  5  6
#> [ CPUFloatType{3,3} ]
#> 
#> [[2]]
#> torch_tensor
#>  2
#>  1
#>  3
#> [ CPULongType{3} ]
#>