I would create a new conv layer with 6 channels and modify its parameters by hand:
trained_kernel = trained_layer.weight # this is the pretrained RGB kernel
new_conv = nn.ConvLayer2d( 6, out_channels, kernel_size, ...)
new_conv.weight[:,:3] = trained_kernel
# if d is the dimension over which you want to average:
new_conv.weight[:,3:] = torch.mean(trained_kernel, d).unsqueeze(d).expand_as(trained_kernel)