Normally we use pytorch like the following code.
class MyNet(nn.Module):
  def __init__(self):
    super().__init__()
    self.layer1 = nn.Conv2d(3, 32, 3)
    self.layer2 = nn.Conv2d(32, 64, 3)
    self.layer3 = nn.Conv2d(64, 2, 3)
  def forward(self, x):
    out = self.layer1(x)
    out = self.layer2(out)
    out = self.layer3(out)
    return out

My question is:
Do I have to instantiate layers in init() function? Are the following 2 code segments also okay?
Code_1
class MyNet(nn.Module):
  def __init__(self):
    super().__init__()
    self.layer1 = nn.Conv2d(3, 32, 3)

  def forward(self, x):
    out = self.layer1(x)

    self.layer2 = nn.Conv2d(32, 64, 3)
    self.layer3 = nn.Conv2d(64, 2, 3)
    out = self.layer2(out)
    out = self.layer3(out)
    return out

Code_2
layer2 = nn.Conv2d(32, 64, 3)
layer3 = nn.Conv2d(64, 2, 3)

class MyNet(nn.Module):
  def __init__(self):
    super().__init__()
    self.layer1 = nn.Conv2d(3, 32, 3)

  def forward(self, x):
    out = self.layer1(x)

    out = layer2(out)
    out = layer3(out)
    return out