I’m trying to load my training data. I do it this way.
    batch_sizeDif = len (imagDif_Tenzor)
    batchDif = torch.zeros (batch_sizeDif, 3, 493, 733, dtype = torch.uint8)
        
    batch_sizeD = len (imagD_Tenzor)
    batchD = torch.zeros (batch_sizeD, 3, 493, 733, dtype = torch.uint8)
    
    for i, filename in enumerate (imagDif_Tenzor):
     batchDif [i] = torchvision.io.read_image (os.path.join (imagDif_path, filename))
    
    batchDif = setup_aug_tfms ([Saturation (max_lighting = 0.0, p = 1.0, draw = 0.0)])
    
    for i, filename in enumerate (imagD_Tenzor):
     batchD [i] = torchvision.io.read_image (os.path.join (imagD_path, filename))

Notice the third line from the end. I desaturate the tensor. And then the following code stops working.
    fig = plt.figure ()
    ax1 = fig.add_subplot (2,2,1)
    ax1.imshow (batchDif [0] .permute (1, 2, 0))
    ax2 = fig.add_subplot (2,2,2)
    ax2.imshow (batchD [0] .permute (1, 2, 0))
    ax3 = fig.add_subplot (2,2,3)
    ax3.imshow (batchDif [20] .permute (1, 2, 0))
    ax4 = fig.add_subplot (2,2,4)
    ax4.imshow (batchD [20] .permute (1, 2, 0))
    plt.show ()

there is an error in line 3 from the top. ‘Saturation’ object has no attribute ‘permute’.
What attribute to use to display the image? Or do we act differently? If you do not desaturate the images are displayed without errors.