Using pymc3 NUTS sampler for an "external model" having its derivatives with respect to its parameters

Questions
3

@junpenglao I apologize for late reply, and appreciate your help. Please let me explain more:
It is how I define my external model:

#%% defining model
@th.compile.ops.as_op(itypes=[t.dscalar],otypes=[t.dscalar,t.dscalar])
def dismodel(E):
    f = open("input.xxx", "w")#input for my external program 
    f.write("set ee "+str(E)+";\n")
    f.close()
    call("MyexternalProgram final.xxx")#run my external program via python
    return np.loadtxt("enddisp.out"),np.loadtxt("ddmdisp.out")
    #First output is the value for parameter E, and the second output is its gradient wtr E.

Now I do not know how to let NUTS that it is the gradient it should use in its algorithm. I can run the same model using Metropolis without gradient with no problem.