mindspore.ops.NanToNum
- class mindspore.ops.NanToNum(nan=None, posinf=None, neginf=None)[source]
Replaces NaN, positive infinity and negative infinity values in the input Tensor with the values specified by nan, posinf and neginf respectively.
Warning
This is an experimental API that is subject to change or deletion.
Refer to
mindspore.ops.nan_to_num()
for more details.- Parameters
nan (float, optional) – The value to replace NaN. Default value is
None
.posinf (float, optional) – If a Number, the value to replace positive infinity values with. If None, positive infinity values are replaced with the greatest finite value representable by x’s dtype. Default value is
None
.neginf (float, optional) – if a Number, the value to replace negative infinity values with. If None, negative infinity values are replaced with the lowest finite value representable by x’s dtype. Default value is
None
.
- Inputs:
x (Tensor) - Input Tensor of any dimensions. Supported data types: float32 or float16.
- Outputs:
Tensor, has the same shape and dtype as the x.
- Supported Platforms:
Ascend
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> nan_to_num = ops.NanToNum() >>> x = Tensor(np.array([float('nan'), float('inf'), -float('inf'), 3.14]), mindspore.float32) >>> output = nan_to_num(x) >>> print(output) [ 0.0000000e+00 3.4028235e+38 -3.4028235e+38 3.1400001e+00]