I was going through various examples in pytorch and was confused by the general implementation of the nn.Conv2d class. For example in the documentation it’s given:
import torch.nn as nn import torch.nn.functional as F class Model(nn.Module): def __init__(self): super(Model, self).__init__() self.conv1 = nn.Conv2d(1, 20, 5) self.conv2 = nn.Conv2d(20, 20, 5) def forward(self, x): x = F.relu(self.conv1(x)) return F.relu(self.conv2(x))
I understand that self.conv1 is an instance of the Conv2d class. However how is the forward pass implemented as simply
self.conv1(x)? Why isn’t it
self.conv1.forward(x), as defined in the source code for Conv2d?