mindspore.ops.nextafter

mindspore.ops.nextafter(input, other)[source]

Returns the next representable floating-point value after input towards other element-wise.

\[\begin{split}out_i = \begin{cases} & input_i + eps, & \text{if } input_i < other_i \\ & input_i - eps, & \text{if } input_i > other_i \\ & input_i, & \text{if } input_i = other_i \end{cases}\end{split}\]

Where eps is the smallest representable increment value for the input tensor's dtype.

For more detailed information, refer to A Self Regularized Non-Monotonic Neural Activation Function.

Parameters

input (Tensor) – The first input tensor.
other (Tensor) – The second input tensor.

Returns

Tensor

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> eps = np.finfo(np.float32).eps
>>> input = mindspore.tensor([1.0], mindspore.float32)
>>> other = mindspore.tensor([2.0], mindspore.float32)
>>> output = mindspore.ops.nextafter(input, other)
>>> print(output == eps + 1)
[ True]
>>> input = mindspore.tensor([1.0, 2.0], mindspore.float32)
>>> other = mindspore.tensor([2.0, 1.0], mindspore.float32)
>>> output = mindspore.ops.nextafter(input, other)
>>> print(output == mindspore.tensor([eps + 1, 2 - eps], mindspore.float32))
[ True True]