Flock1:

conv1 = nn.Conv2d(3,8,kernel_size=(3,3), stride = 2)


Not sure where 12 came from. Your conv1 layer has 3 input channels, 8 output channels, kernel size of 3x3 and stride 2. Thus, you have 8 kernels, each has 3x(3x3) weights and 1 bias
Use conv1.bias.shape and conv1.weight.shape after initialization to get correct dimensions.