Why to exclude features used for label generation during modeling?
What you are doing is right. You can build a ML model using this. In your case your input and output are correlated. Consider the salary of an employee wrt his experience. These both are related and sometimes used to derive salary based on experience.   

What you might have read is if one feature is used to derive other feature and dont use both features, as both will yield same results. You can point to that writing for further clarification.   

Additionally, what is the significance of variables T1,T2 and T3? If these are nowhere correlated to the output label then actually you would have to eliminate them.