以下是对我有效的方法：

通过直接调用字符串中组合函数的decorator

• Creating并将其传递给 exec

，

1. 最初没有使用 cuda.jit 修饰我的函数，以便它们仍然拥有 __name__ attribute
2. Getting __name__ attribute
3. 现在将python应用于我的函数

确切的代码是：

from numba import cuda
import numpy as np
def a(x):
    return x+1
def b(x):
    return 2*x
# Here, pretend we've been passed the inner function and the outer function as arguments
inner_fun = a
outer_fun = b
# And pretend we have noooooo idea what functions these guys actually point to
inner_name = inner_fun.__name__
outer_name = outer_fun.__name__
# Now manually apply the decorator
a = cuda.jit('int32(int32)', device=True)(a)
b = cuda.jit('int32(int32)', device=True)(b)
# Now construct the definition string for the composition function, and exec it.
exec_string = '@cuda.jit(\'void(int32, int32[:])\')\n' \
              'def custom_comp(x, out_array):\n' \
              '    out_array[0]=' + outer_name + '(' + inner_name + '(x))\n'