torch: nn_utils_rnn_pack_sequence – R documentation

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nn_utils_rnn_pack_sequence

Packs a list of variable length Tensors

Description

sequences should be a list of Tensors of size L x *, where L is the length of a sequence and * is any number of trailing dimensions, including zero.

Usage

nn_utils_rnn_pack_sequence(sequences, enforce_sorted = TRUE)

Arguments

`sequences`	`(list[Tensor])`: A list of sequences of decreasing length.
`enforce_sorted`	(bool, optional): if `TRUE`, checks that the input contains sequences sorted by length in a decreasing order. If `FALSE`, this condition is not checked. Default: `TRUE`.

Details

For unsorted sequences, use enforce_sorted = FALSE. If enforce_sorted is TRUE, the sequences should be sorted in the order of decreasing length. enforce_sorted = TRUE is only necessary for ONNX export.

Value

a PackedSequence object

Examples

if (torch_is_installed()) {
x <- torch_tensor(c(1,2,3), dtype = torch_long())
y <- torch_tensor(c(4, 5), dtype = torch_long())
z <- torch_tensor(c(6), dtype = torch_long())

p <- nn_utils_rnn_pack_sequence(list(x, y, z))

}

torch

Tensors and Neural Networks with 'GPU' Acceleration

v0.3.0

MIT + file LICENSE

Authors

Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], RStudio [cph]

Initial release