mindspore.mint.tile
- 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
.If input.dim < d, prepend 1 to the shape of input until their lengths are consistent. Such as set the shape of input as
, then the shape of their corresponding positions can be multiplied, and the shape of Outputs is .If input.dim > d, prepend 1 to dims until their lengths are consistent. Such as set the dims as
, then the shape of their corresponding positions can be multiplied, and the shape of Outputs is .
- 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]]])