I want to initialise the value of a tensor which doesn’t get value from a certain function as below -
img_path = "Path_to_single_image"
mask = function(img_path)
class0,class1 = mask.unique(return_counts = True)
class0,class1

The general default output looks like this -
tensor([0, 1, 2, 3]) tensor([304960, 13746, 10765, 489])  

I want to loop through multiple files and the issue is many files don’t have all the the same tensors -
so some file may just have only have data as below -
tensor([0, 1, 2]) tensor([304960, 13746, 10765]) 
I need the above tensor values for some additional operation and the data like above is creating issue.
class0 will always same 4 values if it is present in the file - tensor([0, 1, 2, 3])
while values of  class1 may differ.
If any of the value of class0 is present , then I want class1 to be initialised to 0
like
`tensor([0, 1, 2,3]) tensor([304960, 13746, 10765,0]) ` 

But I am not able to do it.
I also tried initialising it using the below method but was not able to do it.
img_path = "Path_to_single_image"
mask = function(img_path)
class0 = torch.tensor([0,1,2,3],dtype = torch.float32)
class1 = torch.zeros([4],dtype = torch.float32)
class0,class1 = mask.unique(return_counts = True)
class0,class1

Output for above code -
tensor([0, 1, 2]) tensor([304960, 13746, 10765])