mindspore.ops.mish
- mindspore.ops.mish(x)[source]
Computes MISH(A Self Regularized Non-Monotonic Neural Activation Function) of input tensors element-wise.
The function is shown as follows:
\[\text{output} = x * \tanh(\log(1 + \exp(\text{x})))\]See more details in A Self Regularized Non-Monotonic Neural Activation Function.
Mish Activation Function Graph:
- Parameters
x (Tensor) –
The input Tensor. Supported dtypes:
GPU/CPU: float16, float32, float64.
Ascend: float16, float32.
- Returns
Tensor, with the same type and shape as the x.
- Raises
TypeError – If dtype of x is not float16, float32 or float64.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> input_x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]), mindspore.float32) >>> output = ops.mish(input_x) >>> print(output) [[-3.0340147e-01 3.9974129e+00 -2.68311895e-03] [ 1.9439590e+00 -3.3576239e-02 8.99999990e+00]] >>> input_x = Tensor(2.1, mindspore.float32) >>> output = ops.mish(input_x) >>> print(output) 2.050599