Assume I have a network in two parts like:
def forward(self, x):
  x = self.part_1(x)
  return self.part_2(x)

If I want to update only the second part in training phase, will this modification do the desired thing?
def forward(self, x):
  with torch.no_grad():
    x = self.part_1(x)
  return self.part_2(x)