Solved by ptrblck in post #2 
              
              
                You could iterate the tensor, index each sample, transform it to  PIL.Image and store it. 
Here is a small code snippet: 
import torchvision.transforms.functional as TF

x = torch.randn(5, 24, 24)
for idx in range(x.size(0)):
    tmp = x[idx]
    img = TF.to_pil_image(tmp)
    img.save('img{}.tiff'.…