I was trying trying to run tensorboard module in Pytorch with 3D image data with the following code:
class GetTB(object):
    def __init__(self, img, lbl, model):
        self.image = img
        self.label = lbl
        self.model = model

    def WorkTB(self):
        tb = SummaryWriter()
        grid = torchvision.utils.make_grid(self.image)
        tb.add_image("images", grid)
        tb.add_graph(model, self.image)
        tb.close()

A = GetTB(images, labels, model).WorkTB()

A bit about the images and labels is: images have B,C,H,W,D  dimensions.  which is C=1 for images and C=5/6 for the one-hot encoded label.
Now in my search the make_grid() documentation mentions images to be:
Args:
    tensor (Tensor or list): 4D mini-batch Tensor of shape (B x C x H x W)
        or a list of images all of the same size.

Does it indicate tensorboard only works with RGB image data?
I also couldn’t find any sort of implementation tutorial/article for specific 3D data. If anyone updates would be highly appreciated.
Thanks