nn_utils_rnn_pad_sequence: Pad a list of variable length Tensors with 'padding_value'

View source: R/nn-utils-rnn.R

nn_utils_rnn_pad_sequenceR Documentation

Pad a list of variable length Tensors with padding_value


pad_sequence stacks a list of Tensors along a new dimension, and pads them to equal length. For example, if the input is list of sequences with size ⁠L x *⁠ and if batch_first is False, and ⁠T x B x *⁠ otherwise.


nn_utils_rnn_pad_sequence(sequences, batch_first = FALSE, padding_value = 0)



(list[Tensor]): list of variable length sequences.


(bool, optional): output will be in ⁠B x T x *⁠ if TRUE, or in ⁠T x B x *⁠ otherwise


(float, optional): value for padded elements. Default: 0.


B is batch size. It is equal to the number of elements in sequences. T is length of the longest sequence. L is length of the sequence. * is any number of trailing dimensions, including none.


Tensor of size ⁠T x B x *⁠ if batch_first is FALSE. Tensor of size ⁠B x T x *⁠ otherwise


This function returns a Tensor of size ⁠T x B x *⁠ or ⁠B x T x *⁠ where T is the length of the longest sequence. This function assumes trailing dimensions and type of all the Tensors in sequences are same.


if (torch_is_installed()) {
a <- torch_ones(25, 300)
b <- torch_ones(22, 300)
c <- torch_ones(15, 300)
nn_utils_rnn_pad_sequence(list(a, b, c))$size()

torch documentation built on June 7, 2023, 6:19 p.m.