def METHOD_NAME(net, mode):
    # Check the Encoder blocks
    for layer_num, res_block in enumerate(net.res_blocks):
        for inner_num, layer in enumerate(res_block.layers):
            if layer_num > 0 and inner_num == 0:
                sz = 2
            else:
                sz = 1
            if (
                layer.layers.conv1.kernel_size != (1, 1)
                or layer.layers.conv2.kernel_size != (3, 3)
                or layer.layers.conv3.kernel_size != (1, 1)
            ):
                return True
            if (
                layer.layers.conv1.stride != (1, 1)
                or layer.layers.conv2.stride != (sz, sz)
                or layer.layers.conv3.stride != (1, 1)
            ):
                return True
        sz2 = 1
        if layer_num > 0:
            sz2 = 2
        if res_block.shortcut.kernel_size != (1, 1) or res_block.shortcut.stride != (sz2, sz2):
            return True
    if net.bottleneck.conv_bottleneck.kernel_size != (1, 1) or net.bottleneck.conv_bottleneck.stride != (1, 1):
        return True
    # Check HV Branch
    if check_branch(net.horizontal_vertical.decoder_blocks, mode):
        return True
    if check_output(net.horizontal_vertical.output_features, mode):
        return True
    # Check NP Branch
    if check_branch(net.nucleus_prediction.decoder_blocks, mode):
        return True
    if check_output(net.nucleus_prediction.output_features, mode):
        return True
    # Check NC Branch
    if check_branch(net.type_prediction.decoder_blocks, mode):
        return True
    if check_output(net.type_prediction.output_features, mode):
        return True
    return False