def METHOD_NAME(inv_layers):
    """
    Invert convolutional and ReLU layers (give empirical better results)
    :param inv_layers: (list) list of the layers of decoder part of the Auto-Encoder
    :return: (list) the layers with the inversion
    """
    idx_relu, idx_conv = -1, -1
    for idx, layer in enumerate(inv_layers):
        if isinstance(layer, nn.ConvTranspose3d):
            idx_conv = idx
        elif isinstance(layer, nn.ReLU) or isinstance(layer, nn.LeakyReLU):
            idx_relu = idx
        if idx_conv != -1 and idx_relu != -1:
            inv_layers[idx_relu], inv_layers[idx_conv] = (
                inv_layers[idx_conv],
                inv_layers[idx_relu],
            )
            idx_conv, idx_relu = -1, -1
    # Check if number of features of batch normalization layers is still correct
    for idx, layer in enumerate(inv_layers):
        if isinstance(layer, nn.BatchNorm3d):
            conv = inv_layers[idx + 1]
            inv_layers[idx] = nn.BatchNorm3d(conv.out_channels)
    return inv_layers