mindspore.ops.Meshgrid

class mindspore.ops.Meshgrid(indexing='xy')[source]

Generates coordinate matrices from given coordinate tensors.

Refer to mindspore.ops.meshgrid() for more details.

Parameters: indexing (str, optional) – Cartesian 'xy' or matrix ('ij') indexing of output. Valid options: xy' or 'ij'. In the 2-D case with inputs of length M and N, for 'xy' indexing, the shape of outputs is \((N, M)\) for 'ij' indexing, the shape of outputs is \((M, N)\). In the 3-D case with inputs of length M, N and P, for 'xy' indexing, the shape of outputs is \((N, M, P)\) and for 'ij' indexing, the shape of outputs is \((M, N, P)\). Default: 'xy' .

Inputs:

inputs (Union(tuple[Tensor], list[Tensor])) - In GRAPH_MODE, a tuple of N 1-D Tensor objects and the length of input should be greater than 1. In PYNATIVE_MODE, a tuple of N 0-D or 1-D Tensor objects and the length of input should be greater than 0. The data type is Number.

Outputs:

Tensors, A Tuple of N N-D Tensor objects. The data type is the same with the Inputs.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([1, 2, 3, 4]).astype(np.int32))
>>> y = Tensor(np.array([5, 6, 7]).astype(np.int32))
>>> z = Tensor(np.array([8, 9, 0, 1, 2]).astype(np.int32))
>>> inputs = (x, y, z)
>>> meshgrid = ops.Meshgrid(indexing='xy')
>>> output = meshgrid(inputs)
>>> 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]]]))