# 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 syncronization 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.