def conv2d_layer(filters=256, kernel_size=None, strides=None):
    """Conv2D Layer
    Args:
        filters: int, the output channels of the conv2d layer
        kernel_size: list, the kernel size of the conv2d layer
        strides: list, the strides of the conv2d layer
    """
    if kernel_size is None:
        kernel_size = [1, 1]
    if strides is None:
        strides = [1, 1]
    conv2d = Conv2D(filters=filters, kernel_size=kernel_size, padding="same", activation='relu', strides=strides)
    return conv2d
Conv2D Layer
    Args:
        filters: int, the output channels of the conv2d layer
        kernel_size: list, the kernel size of the conv2d layer
        strides: list, the strides of the conv2d layer
    
code/train/model_paper.py