mindspore.mint.repeat_interleave

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

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

Warning

Only support on Atlas A2 training series.

Parameters

• input (Tensor) – The tensor to repeat values for. Must be of types: float16, float32, int8, uint8, int16, int32, or int64.

• 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. If dims is None, the input Tensor will be flattened and the output will alse be flattened.

Keyword Arguments

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

Returns

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

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, mint
>>> input = Tensor(np.array([[0, 1, 2], [3, 4, 5]]), mindspore.int32)
>>> output = mint.repeat_interleave(input, repeats=2, dim=0)
>>> print(output)
[[0 1 2]
 [0 1 2]
 [3 4 5]
 [3 4 5]]