def __init__(self, in_channels, out_channels, withBNRelu=True):
    super().__init__()
    self.add_module('conv1', nn.Conv2d(in_channels, out_channels, 1, 1, 0, bias=True, groups=1))
    self.add_module('conv2', nn.Conv2d(out_channels, out_channels, 3, 1, 1, bias=True, groups=out_channels))
    if withBNRelu:
        self.add_module('bn', nn.BatchNorm2d(out_channels))
        self.add_module('relu', nn.ReLU(inplace=True))
def __init__(self, in_channels, out_channels, withBNRelu=True):
    super().__init__()
    self.add_module('conv1', nn.Conv2d(in_channels, out_channels, 1, 1, 0, bias=True, groups=1))
    self.add_module('conv2', nn.Conv2d(out_channels, out_channels, 3, 1, 1, bias=True, groups=out_channels))
    if withBNRelu:
        self.add_module('bn', nn.BatchNorm2d(out_channels))
        self.add_module('relu', nn.ReLU(inplace=True))