def forward(self, input):
'''
Forward pass of the function.
'''
if torch.__version__ >= '1.9':
return F.mish(input)
else:
return Func.mish(input)
def forward(self, x):
# make sure the input tensor is flattened
x = x.view(x.shape[0], -1)
# apply Mila activation function
if (self.activation == MISH):
x = Func.mish(self.fc1(x))
x = F.relu(self.fc2(x))
x = F.relu(self.fc3(x))
x = F.log_softmax(self.fc4(x), dim=1)
return x
def forward(self, input):
'''
Forward pass of the function.
'''
return Func.mish(input)