def METHOD_NAME(
    input_features, output_features, kernel=3, padding=1, dilation=1, modifier=None, batch_norm=False
):
    stride = 1
    if modifier == "S":
        stride = 2
        padding = 1
    elif modifier == "K":
        kernel = 4
        padding = 1
    layer = [
        nn.Conv2d(
            input_features, output_features, kernel_size=kernel, stride=stride, padding=padding, dilation=dilation
        )
    ]
    if batch_norm:
        layer.append(nn.BatchNorm2d(output_features))
    layer.append(nn.ReLU(inplace=True))
    return layer