Thanks.  I did that.  All the augmenting transforms ((Random Rotation, Random Crop, Random Horizontal Flip, Rescale) seem OK.  To circumvent the ToTensor scaling to [0,1], I added some code torch.from_numpy(images).unsqueeze(0) to convert the image to a tensor manually within the getitem function of the dataset after all the previously mentioned transformations are done.  Then I can just plug into the normalization transform.  If no issues arise here, then I can manually divide by 65536, and it should be good to go.
I am running into a problem however getting the Normalize transform to work. I keep getting this error: TypeError: ‘NoneType’ object is not callable
The below is the snippet of my code:
def __getitem__(self,idx):
    image_path = self.samples[idx]

    image = io.imread(image_path)
    image = (image).astype(np.float32)
    image = torch.from_numpy(image).unsqueeze(0)
    image = self.transform(image)   <<< **error occurs here**

(my definition of the transform): norm_transform = torchvision.transforms.Normalize(mean=data_mean,std=data_std)
my definition of hte dataloader and dataset):
dataset = One_Image_Dataset(dataloader_path, transform=norm_transform)
transform_dataloader = DataLoader(dataset, batch_size=1, shuffle=False)
Below is the stack trace:’    for i in dataloader:
File “/home/multiomyx/.local/share/virtualenvs/PyTorch-rjjGfeb_/lib/python3.7/site-packages/torch/utils/data/dataloader.py”, line 345, in next
data = self.next_data()
File "/home/multiomyx/.local/share/virtualenvs/PyTorch-rjjGfeb/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 385, in _next_data
data = self.dataset_fetcher.fetch(index)  # may raise StopIteration
File "/home/multiomyx/.local/share/virtualenvs/PyTorch-rjjGfeb/lib/python3.7/site-packages/torch/utils/data/utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/multiomyx/.local/share/virtualenvs/PyTorch-rjjGfeb/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in 
data = [self.dataset[idx] for idx in possibly_batched_index]
File “Inspect Image.py”, line 34, in getitem
image = self.transform(image)
TypeError: ‘NoneType’ object is not callable
Would you happen to know what could be causing this error?  Is it something internal? I don’t think I am passing in a callable as image is class torch.tensor?  Thank you.