mindspore.ops.fmax
- mindspore.ops.fmax(input, other)[source]
Computes the maximum of input tensors element-wise.
\[output_i = \max(x1_i, x2_i)\]Note
Inputs of input and other comply with the implicit type conversion rules to make the data types consistent.
Shapes of input and other should be able to broadcast.
If one of the elements to be compared is NaN, another element is returned.
- Parameters
- Returns
A Tensor, the shape is the same as the one after broadcasting, and the data type is the one with higher precision or higher digits among the two inputs.
- Raises
TypeError – If input or other is not Tensor.
TypeError – If dtype of input or other is not one of: float16, float32, float64, int32, int64.
ValueError – If the shape of input and other can not broadcast.
- Supported Platforms:
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> x1 = Tensor(np.array([1.0, 5.0, 3.0]), mindspore.float32) >>> x2 = Tensor(np.array([4.0, 2.0, 6.0]), mindspore.float32) >>> output = ops.fmax(x1, x2) >>> print(output) [4. 5. 6.]