mindspore.mint.repeat_interleave

mindspore.mint.repeat_interleave(input, repeats, dim=None, *, output_size=None) → Tensor[source]

Repeat elements of a tensor along an axis, like mindspore.numpy.repeat().

Parameters:

input (Tensor) – The input tensor.
repeats (Union[int, tuple, list, Tensor]) – The number of times to repeat, must be positive.
dim (int, optional) – The dim along which to repeat. Default None, which means the input tensor will be flattened and the output will also be flattened.

Keyword Arguments:

output_size (int, optional) – Total output size for the given axis (e.g. sum of repeats ). Default None.

Returns:

Tensor, values repeated along the specified dimension. If input has shape \((s1, s2, ..., sn)\) and dim is i, the output will have shape \((s1, s2, ..., si * repeats, ..., sn)\). The output type will be the same as the type of input.

Supported Platforms:: Ascend

Examples

>>> import mindspore
>>> input = mindspore.tensor([[0, 1, 2], [3, 4, 5]])
>>> mindspore.mint.repeat_interleave(input, repeats=2, dim=0)
    Tensor(shape=[4, 3], dtype=Int64, value=
    [[0, 1, 2],
     [0, 1, 2],
     [3, 4, 5],
     [3, 4, 5]])
>>> mindspore.mint.repeat_interleave(input, repeats=[1,2], dim=0)
    Tensor(shape=[3, 3], dtype=Int64, value=
    [[0, 1, 2],
     [3, 4, 5],
     [3, 4, 5]])
>>> mindspore.mint.repeat_interleave(input, repeats=2, dim=1)
    Tensor(shape=[2, 6], dtype=Int64, value=
    [[0, 0, 1, 1, 2, 2],
     [3, 3, 4, 4, 5, 5]])
>>> mindspore.mint.repeat_interleave(input, repeats=[1,2], dim=0, output_size=3)
    Tensor(shape=[3, 3], dtype=Int64, value=
    [[0, 1, 2],
     [3, 4, 5],
     [3, 4, 5]])