Solved by ptrblck in post #7 
              
              
                This would split the dataset before using any of the PyTorch classes. 
You would get different splits and create different Dataset classes: 

X = np.random.randn(1000, 2)
y = np.random.randint(0, 10, size=1000)

X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.1, stratify=y)
np.un…