!14285 numpy-native docstrings add mgrid ogrid not supported in graph mode

From: @jachua
Reviewed-by: @guoqi1024,@liangchenghui
Signed-off-by: @liangchenghui
pull/14285/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
commit c378c9fe75

@ -1296,13 +1296,13 @@ def meshgrid(*xi, sparse=False, indexing='xy'):
[[0. 0.5 1. ] [[0. 0.5 1. ]
[0. 0.5 1. ]] [0. 0.5 1. ]]
>>> print(yv) >>> print(yv)
[[0. 0. 0.], [[0. 0. 0.]
[1. 1. 1.]] [1. 1. 1.]]
>>> xv, yv = np.meshgrid(x, y, sparse=True) >>> xv, yv = np.meshgrid(x, y, sparse=True)
>>> print(xv) >>> print(xv)
[[0. 0.5 1. ]] [[0. 0.5 1. ]]
>>> print(yv) >>> print(yv)
[[0.], [[0.]
[1.] [1.]
""" """
_check_input_tensor(*xi) _check_input_tensor(*xi)
@ -1409,6 +1409,7 @@ class mGridClass(nd_grid):
stop values, where the stop value is inclusive. stop values, where the stop value is inclusive.
Note: Note:
Not supported in graph mode.
Unlike Numpy, if the step length is a complex number with a real Unlike Numpy, if the step length is a complex number with a real
component, the step length is handled as equivalent to component, the step length is handled as equivalent to
``int(abs(step))``. ``int(abs(step))``.
@ -1456,6 +1457,7 @@ class oGridClass(nd_grid):
stop values, where the stop value is inclusive. stop values, where the stop value is inclusive.
Note: Note:
Not supported in graph mode.
Unlike Numpy, if the step length is a complex number with a real Unlike Numpy, if the step length is a complex number with a real
component, the step length is handled as equivalent to component, the step length is handled as equivalent to
``int(abs(step))``. ``int(abs(step))``.

@ -689,7 +689,6 @@ def where(condition, x=None, y=None):
[[[7 5] [[[7 5]
[7 5] [7 5]
[7 5]] [7 5]]
[[7 5] [[7 5]
[7 5] [7 5]
[7 5]]] [7 5]]]

@ -450,9 +450,9 @@ def power(x1, x2, dtype=None):
>>> x2 = np.full((3, 2), [3, 4]).astype('float32') >>> x2 = np.full((3, 2), [3, 4]).astype('float32')
>>> output = np.power(x1, x2) >>> output = np.power(x1, x2)
>>> print(output) >>> print(output)
[[ 1 16] [[ 1. 16.]
[ 1 16] [ 1. 16.]
[ 1 16]] [ 1. 16.]]
""" """
return _apply_tensor_op(F.tensor_pow, x1, x2, dtype=dtype) return _apply_tensor_op(F.tensor_pow, x1, x2, dtype=dtype)

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