torch.repeat_interleave

torch.repeat_interleave(input, repeats, dim=None, *, output_size=None) → Tensor

Repeat elements of a tensor.

Warning

This is different from torch.Tensor.repeat() but similar to numpy.repeat.

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:

Tensor

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]])

torch.repeat_interleave(repeats, *, output_size=None) → Tensor

If the repeats is tensor([n1, n2, n3, …]), then the output will be tensor([0, 0, …, 1, 1, …, 2, 2, …, …]) where 0 appears n1 times, 1 appears n2 times, 2 appears n3 times, etc.