Shortcuts

Function torch::nn::utils::rnn::pad_sequence

Function Documentation

inline Tensor torch::nn::utils::rnn::pad_sequence(ArrayRef<Tensor> sequences, bool batch_first = false, double padding_value = 0, std::string_view padding_side = "right")

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.

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.

Note: 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.

Arguments: sequences (torch::ArrayRef<Tensor>): list of variable length sequences. batch_first (bool, optional): output will be in B x T x * if true, or in T x B x * otherwise padding_value (double, optional): value for padded elements. Default: 0. padding_side (str, optional): the side to pad the sequences on. Default: “right”.

Returns: Tensor of size T x B x * if batch_first is false. Tensor of size B x T x * otherwise

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources