mindspore.mint.tile

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mindspore.mint.tile(input, dims)[source]

Creates a new tensor by repeating the elements in the input tensor dims times.

The i'th dimension of output tensor has input.shape[i] * dims[i] elements, and the values of input are repeated dims[i] times along the i'th dimension.

Note:
  • On Ascend, the number of dims should not exceed 8, and currently does not support scenarios where more than 4 dimensions are repeated simultaneously.

  • If input.dim = d, then the shape of their corresponding positions can be multiplied, and the shape of Outputs is (x1y1,x2y2,...,xSyS).

  • If input.dim < d, prepend 1 to the shape of input until their lengths are consistent. Such as set the shape of input as (1,...,x1,x2,...,xS), then the shape of their corresponding positions can be multiplied, and the shape of Outputs is (1y1,...,xRyR,xSyS).

  • If input.dim > d, prepend 1 to dims until their lengths are consistent. Such as set the dims as (1,...,y1,y2,...,yS), then the shape of their corresponding positions can be multiplied, and the shape of Outputs is (x11,...,xRyR,xSyS).

Args:

input (Tensor): The input tensor. dims (tuple[int]): The specified number of repetitions in each dimension.

Returns:

Tensor

tril
Supported Platforms:

Ascend

Examples:
>>> import mindspore
>>> input = mindspore.tensor([[1, 2], [3, 4]])
>>> mindspore.mint.tile(input, (2, 3))
Tensor(shape=[4, 6], dtype=Int64, value=
[[1, 2, 1, 2, 1, 2],
 [3, 4, 3, 4, 3, 4],
 [1, 2, 1, 2, 1, 2],
 [3, 4, 3, 4, 3, 4]])
>>> mindspore.mint.tile(input, (2, 3, 2))
Tensor(shape=[2, 6, 4], dtype=Int64, value=
[[[1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4]],
 [[1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4]]])