torch.nn.utils.rnn.pack_sequence — PyTorch 2.7 documentation (original) (raw)
torch.nn.utils.rnn.pack_sequence(sequences, enforce_sorted=True)[source][source]¶
Packs a list of variable length Tensors.
Consecutive call of the next functions: pad_sequence, pack_padded_sequence.
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 0.
For unsorted sequences, use enforce_sorted = False. If enforce_sortedis True, the sequences should be sorted in the order of decreasing length.enforce_sorted = True is only necessary for ONNX export.
Example
from torch.nn.utils.rnn import pack_sequence a = torch.tensor([1, 2, 3]) b = torch.tensor([4, 5]) c = torch.tensor([6]) pack_sequence([a, b, c]) PackedSequence(data=tensor([1, 4, 6, 2, 5, 3]), batch_sizes=tensor([3, 2, 1]), sorted_indices=None, unsorted_indices=None)
Parameters
- 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. IfFalse, this condition is not checked. Default:True.
Returns
a PackedSequence object
Return type