grad(odeint)

[tesla-cat]

def intFunc(x):
    def func(y, t):
        return np.sin( x * t )
    y0 = 0.
    t = [0., 1.]
    y = odeint(func, y0, t)[-1]
    return y
print(intFunc(0.5))
intFuncGrad = grad(intFunc)
print(intFuncGrad(1.0))

• error:

[0.24483481]
TypeError: float() argument must be a string or a number, not 'ArrayBox'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "c:/Users/e0134117/Desktop/qoc/1 Implementations/AQUA/HIPS-autograd/basic-tests.py", line 16, in <module>
    print(intFuncGrad(1.0))
  File "C:\Python38\lib\site-packages\autograd\wrap_util.py", line 20, in nary_f
    return unary_operator(unary_f, x, *nary_op_args, **nary_op_kwargs)
  File "C:\Python38\lib\site-packages\autograd\differential_operators.py", line 25, in grad
    vjp, ans = _make_vjp(fun, x)
  File "C:\Python38\lib\site-packages\autograd\core.py", line 10, in make_vjp
    end_value, end_node =  trace(start_node, fun, x)
  File "C:\Python38\lib\site-packages\autograd\tracer.py", line 10, in trace
    end_box = fun(start_box)
  File "C:\Python38\lib\site-packages\autograd\wrap_util.py", line 15, in unary_f
    return fun(*subargs, **kwargs)
  File "c:/Users/e0134117/Desktop/qoc/1 Implementations/AQUA/HIPS-autograd/basic-tests.py", line 12, in intFunc
    y = odeint(func, y0, t)[-1]
  File "C:\Python38\lib\site-packages\autograd\tracer.py", line 48, in f_wrapped
    return f_raw(*args, **kwargs)
  File "C:\Python38\lib\site-packages\scipy\integrate\odepack.py", line 242, in odeint
    output = _odepack.odeint(func, y0, t, args, Dfun, col_deriv, ml, mu,
ValueError: setting an array element with a sequence.

[hannesmeinlschmidt]

It seems that autograd requires that the parameter in the ODE with respect to which you want the derivative must be passed in odeint as a parameter:

import autograd.numpy as np
from autograd.scipy.integrate import odeint
from autograd import grad
from autograd.builtins import tuple

def intFunc(x):
    def func(y, t, alpha):
        return np.sin(alpha * t)
    y0 = 0.
    t = np.linspace(0., 1., 10)
    y = odeint(func, y0, t, tuple([x]))[-1]
    return y

print(intFunc(0.5))
intFuncGrad = grad(intFunc)
print(intFuncGrad(1.0))