mindspore.ops.nansum

mindspore.ops.nansum(input, axis=None, keepdims=False, *, dtype=None)

忽略NaN值，按指定轴计算输入tensor的和。

参数：

• input (Tensor) - 输入Tensor。

• axis (Union[int, tuple(int)], 可选) - 求和的维度。假设 input 的秩为r，取值范围[-r,r)，默认 None ，对tensor中的所有元素求和。

• keepdims (bool, 可选) - 输出tensor是否保持维度，默认 False ，不保留维度。

关键字参数：

• dtype (mindspore.dtype, 可选) - 输出tensor的类型，默认 None 。

返回：

Tensor

支持平台：

Ascend GPU CPU

样例：

>>> import mindspore
>>> x = mindspore.tensor([[float("nan"), 2, 3], [1, float("nan"), 3], [1, 2, float("nan")]], mindspore.float32)
>>> # case1: axis is None, keepdims is False,
>>> output1 = mindspore.ops.nansum(x, axis=None, dtype=mindspore.float32)
>>> print(output1)
12.0
>>> # case2: axis is int, set as 0, and keepdims is False
>>> output2 = mindspore.ops.nansum(x, axis=0, dtype=mindspore.float32)
>>> print(output2)
[2. 4. 6.]
>>> # case3: axis is int, set as 0, and keepdims is False
>>> output3 = mindspore.ops.nansum(x, axis=0, keepdims=True, dtype=mindspore.float32)
>>> print(output3)
[[2. 4. 6.]]
>>> # case4: axis is tuple(int) or list(int), set as (0, 1), and keepdims is False
>>> output4 = mindspore.ops.nansum(x, axis=(0, 1), dtype=mindspore.float32)
>>> print(output4)
12.0