!47912 [OPS] modify meshgrid funtional input form tuple to tensor sequence

Merge pull request !47912 from yangruoqi713/ops

docs/api/api_python/ops/mindspore.ops.func_meshgrid.rst

@@ -1,14 +1,16 @@
 mindspore.ops.meshgrid
 ======================
 
-.. py:function:: mindspore.ops.meshgrid(inputs, indexing='xy')
+.. py:function:: mindspore.ops.meshgrid(*inputs, indexing='xy')
 
     从给定的Tensor生成网格矩阵。
 
     给定N个一维Tensor，对每个Tensor做扩张操作，返回N个N维的Tensor。
 
     参数：
-        - **inputs** (Union[tuple]) - N个一维Tensor。输入的长度应大于1。数据类型为Number。
+        - **inputs** (tuple[Tensor]) - N个一维Tensor。输入的长度应大于1。数据类型为Number。
+
+    关键字参数：
         - **indexing** ('xy', 'ij', 可选) - 'xy'或'ij'。影响输出的网格矩阵的size。对于长度为 `M` 和 `N` 的二维输入，取值为'xy'时，输出的shape为 :math:`(N, M)` ，取值为'ij'时，输出的shape为 :math:`(M, N)` 。以长度为 `M` ， `N` 和 `P` 的三维输入，取值为'xy'时，输出的shape为 :math:`(N, M, P)` ，取值为'ij'时，输出的shape为 :math:`(M, N, P)` 。默认值：'xy'。
 
     返回：

mindspore/python/mindspore/ops/function/array_func.py

@@ -4003,7 +4003,7 @@ def matrix_set_diag(x, diagonal, k=0, align="RIGHT_LEFT"): # pylint: disable=red
     return matrix_set_diag_v3_op(x, diagonal, k)
 
 
-def meshgrid(inputs, indexing='xy'):
+def meshgrid(*inputs, indexing='xy'):
     """
     Generates coordinate matrices from given coordinate tensors.
 
@@ -4011,14 +4011,16 @@ def meshgrid(inputs, indexing='xy'):
     coordinate tensors for evaluating expressions on an N-D grid.
 
     Args:
-        inputs (Union[tuple]): A Tuple of N 1-D Tensor objects.
+        inputs (tuple[Tensor]): A list of N 1-D Tensor objects.
             The length of input should be greater than 1. The data type is Number.
+
+    Keyword Args:
         indexing ('xy', 'ij', optional): Cartesian ('xy', default) or
             matrix ('ij') indexing of output. 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.
+            `(N, M, P)` for 'xy' indexing and `(M, N, P)` for 'ij' indexing.  Default: 'xy'.
 
     Returns:
         Tensors, a Tuple of N N-D Tensor objects. The data type is the same with the Inputs.

tests/st/ops/cpu/test_meshgrid_op.py

@@ -81,7 +81,7 @@ def test_meshgrid(dtype, indexing):
     assert np.array_equal(output[1].asnumpy(), np_output[1])
 
     # test functional interface
-    output = F.meshgrid((Tensor(x), Tensor(y)), indexing)
+    output = F.meshgrid(Tensor(x), Tensor(y), indexing=indexing)
     assert np.array_equal(output[0].asnumpy(), np_output[0])
     assert np.array_equal(output[1].asnumpy(), np_output[1])
 
@@ -93,7 +93,7 @@ def test_meshgrid(dtype, indexing):
     assert np.array_equal(output[2].asnumpy(), np_output[2])
 
     # test functional interface
-    output = F.meshgrid((Tensor(x), Tensor(y), Tensor(z)), indexing)
+    output = F.meshgrid(Tensor(x), Tensor(y), Tensor(z), indexing=indexing)
     assert np.array_equal(output[0].asnumpy(), np_output[0])
     assert np.array_equal(output[1].asnumpy(), np_output[1])
     assert np.array_equal(output[2].asnumpy(), np_output[2])