class_docstr: Applies the element-wise function:
  
  .. math::
      \text{Mish}(x) = x * tanh(\text{softplus}(x)).
  
  Citation: Mish: A Self Regularized Non-Monotonic Activation Function, Diganta Misra, 2019, https://arxiv.org/abs/1908.08681.
  
  From Pytorch 1.9.0+, the optimized version of `Mish` is implemented,
  this class will utilize `torch.nn.functional.mish` to do the calculation if meets the version.
  
  Shape:
      - Input: :math:`(N, *)` where `*` means, any number of additional dimensions
      - Output: :math:`(N, *)`, same shape as the input
  
  
  Examples::
  
      >>> import torch
      >>> from monai.networks.layers.factories import Act
      >>> m = Act['mish']()
      >>> input = torch.randn(2)
      >>> output = m(input)
code: def __init__(self, inplace: bool = False):
      super().__init__()
      # inplace only works when using torch.nn.functional.mish
      self.inplace = inplace
  
imports: from __future__ import annotations
  import torch
  from torch import nn
  from monai.utils import optional_import
label_desc: Use image node_id 1 to create a new Mish object from inherited base classes: nn with example: obj = Mish(inplace)