in models/resnet.py [0:0]
def __init__(self, in_planes, mid_planes, out_planes, norm, stride=1):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(in_planes, mid_planes, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn1 = norm(mid_planes)
self.conv2 = nn.Conv2d(mid_planes, out_planes, kernel_size=3, stride=1, padding=1, bias=False)
self.bn2 = norm(out_planes)
self.shortcut = nn.Sequential()
if stride != 1 or in_planes != out_planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False),
norm(out_planes)
)