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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.


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


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.


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()
#> [1]  25   3 300