torch.repeat_interleave — PyTorch 2.7 documentation (original) (raw)
torch.repeat_interleave(input, repeats, dim=None, *, output_size=None) → Tensor¶
Repeat elements of a tensor.
Parameters
- input (Tensor) – the input tensor.
- repeats (Tensor or int) – The number of repetitions for each element. repeats is broadcasted to fit the shape of the given axis.
- dim (int, optional) – The dimension along which to repeat values. By default, use the flattened input array, and return a flat output array.
Keyword Arguments
output_size (int, optional) – Total output size for the given axis ( e.g. sum of repeats). If given, it will avoid stream synchronization needed to calculate output shape of the tensor.
Returns
Repeated tensor which has the same shape as input, except along the given axis.
Return type
Example:
x = torch.tensor([1, 2, 3]) x.repeat_interleave(2) tensor([1, 1, 2, 2, 3, 3]) y = torch.tensor([[1, 2], [3, 4]]) torch.repeat_interleave(y, 2) tensor([1, 1, 2, 2, 3, 3, 4, 4]) torch.repeat_interleave(y, 3, dim=1) tensor([[1, 1, 1, 2, 2, 2], [3, 3, 3, 4, 4, 4]]) torch.repeat_interleave(y, torch.tensor([1, 2]), dim=0) tensor([[1, 2], [3, 4], [3, 4]]) torch.repeat_interleave(y, torch.tensor([1, 2]), dim=0, output_size=3) tensor([[1, 2], [3, 4], [3, 4]])
If the repeats is tensor([n1, n2, n3, …]), then the output will betensor([0, 0, …, 1, 1, …, 2, 2, …, …]) where 0 appears n1 times,1 appears n2 times, 2 appears n3 times, etc.
torch.repeat_interleave(repeats, *) → Tensor
Repeats 0 repeats[0] times, 1 repeats[1] times, 2 repeats[2] times, etc.
Parameters
repeats (Tensor) – The number of repetitions for each element.
Returns
Repeated tensor of size sum(repeats).
Return type
Example:
torch.repeat_interleave(torch.tensor([1, 2, 3])) tensor([0, 1, 1, 2, 2, 2])