Source code for asteroid.masknn.activations

import torch
from torch import nn


[docs]class Swish(nn.Module): def __init__(self): super(Swish, self).__init__()
[docs] def forward(self, x): return x * torch.sigmoid(x)
[docs]def linear(): return nn.Identity()
[docs]def relu(): return nn.ReLU()
[docs]def prelu(): return nn.PReLU()
[docs]def leaky_relu(): return nn.LeakyReLU()
[docs]def sigmoid(): return nn.Sigmoid()
[docs]def softmax(dim=None): return nn.Softmax(dim=dim)
[docs]def tanh(): return nn.Tanh()
[docs]def gelu(): return nn.GELU()
[docs]def swish(): return Swish()
[docs]def get(identifier): """ Returns an activation function from a string. Returns its input if it is callable (already an activation for example). Args: identifier (str or Callable or None): the activation identifier. Returns: :class:`nn.Module` or None """ if identifier is None: return None elif callable(identifier): return identifier elif isinstance(identifier, str): cls = globals().get(identifier) if cls is None: raise ValueError("Could not interpret activation identifier: " + str(identifier)) return cls else: raise ValueError("Could not interpret activation identifier: " + str(identifier))