mindspore.ops.meshgrid

mindspore.ops.meshgrid(*inputs, indexing='xy')[source]

Creates grids of coordinates specified by the 1D inputs。

Note

In graph mode, a tuple of N 1-D tensors and N should be greater than 1.
In pynative mode, a tuple of N 0-D or 1-D tensors and N should be greater than 0. The data type is Number.
In the 2-D case with inputs of length M and N, the outputs are of shape $(N, M)$ for 'xy' indexing and $(M, N)$ for 'ij' indexing.
In the 3-D case with inputs of length M, N and P, outputs are of shape $(N, M, P)$ for 'xy' indexing and $(M, N, P)$ for 'ij' indexing.

Parameters: inputs (Union[tuple[Tensor], list[Tensor]]) – Tuple of tensors or list of tensors.
Keyword Arguments: indexing (str, optional) – Cartesian ('xy', default) or matrix ('ij') indexing of output. Valid options 'xy' or 'ij'. Default 'xy' .
Returns: Tuple of N N-D tensors

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> x = mindspore.tensor([1, 2, 3, 4], mindspore.int32)
>>> y = mindspore.tensor([5, 6, 7], mindspore.int32)
>>> z = mindspore.tensor([8, 9, 0, 1, 2], mindspore.int32)
>>> output = mindspore.ops.meshgrid(x, y, z, indexing='xy')
>>> print(output)
(Tensor(shape=[3, 4, 5], dtype=Int32, value=
 [[[1, 1, 1, 1, 1],
   [2, 2, 2, 2, 2],
   [3, 3, 3, 3, 3],
   [4, 4, 4, 4, 4]],
  [[1, 1, 1, 1, 1],
   [2, 2, 2, 2, 2],
   [3, 3, 3, 3, 3],
   [4, 4, 4, 4, 4]],
  [[1, 1, 1, 1, 1],
   [2, 2, 2, 2, 2],
   [3, 3, 3, 3, 3],
   [4, 4, 4, 4, 4]]]),
 Tensor(shape=[3, 4, 5], dtype=Int32, value=
 [[[5, 5, 5, 5, 5],
   [5, 5, 5, 5, 5],
   [5, 5, 5, 5, 5],
   [5, 5, 5, 5, 5]],
  [[6, 6, 6, 6, 6],
   [6, 6, 6, 6, 6],
   [6, 6, 6, 6, 6],
   [6, 6, 6, 6, 6]],
  [[7, 7, 7, 7, 7],
   [7, 7, 7, 7, 7],
   [7, 7, 7, 7, 7],
   [7, 7, 7, 7, 7]]]),
 Tensor(shape=[3, 4, 5], dtype=Int32, value=
 [[[8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2]],
  [[8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2]],
  [[8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2],
   [8, 9, 0, 1, 2]]]))