(in_channels, out_channels, stride=1, 
            padding=1, bias=True, groups=1)
return nn.Conv2d(
        in_channels, 
        out_channels, 
        kernel_size=3, 
        stride=stride,
        padding=padding,
        bias=bias,
        groups=groups)
3x3 convolution with padding
3x3 convolution with padding
3x3 convolution with padding
def conv3x3(in_channels, out_channels, stride=1, 
            padding=1, bias=True, groups=1):    
    """3x3 convolution with padding
    """
    return nn.Conv2d(
        in_channels, 
        out_channels, 
        kernel_size=3, 
        stride=stride,
        padding=padding,
        bias=bias,
        groups=groups)
def conv3x3 ( in_channels , out_channels , stride = 1 , padding = 1 , bias = True , groups = 1 ) : return nn . Conv2d ( in_channels , out_channels , kernel_size = 3 , stride = stride , padding = padding , bias = bias , groups = groups )