src/audio_models/mish.py

"""
Applies the mish function element-wise:
mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x)))
"""

# import pytorch
import torch
import torch.nn.functional as F
from torch import nn

@torch.jit.script
def mish(input):
    """
    Applies the mish function element-wise:
    mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x)))
    See additional documentation for mish class.
    """
    return input * torch.tanh(F.softplus(input))

class Mish(nn.Module):
    """
    Applies the mish function element-wise:
    mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + exp(x)))

    Shape:
        - Input: (N, *) where * means, any number of additional
          dimensions
        - Output: (N, *), same shape as the input

    Examples:
        >>> m = Mish()
        >>> input = torch.randn(2)
        >>> output = m(input)

    Reference: https://pytorch.org/docs/stable/generated/torch.nn.Mish.html
    """

    def __init__(self):
        """
        Init method.
        """
        super().__init__()

    def forward(self, input):
        """
        Forward pass of the function.
        """
        if torch.__version__ >= "1.9":
            return F.mish(input)
        else:
            return mish(input)