The numba allows eager compilation by telling the function signature. But, I can not find some information about the list type. My test code is:
import numba as nb
import numpy as np
# @nb.jit(nb.ListType())
def Cal():
return [1, np.zeros(shape=[5, 5]), 3]
a = Cal()
What's the function signature for Cal?
In addition, what if there are three outputs? How to provide the function signature? For example:
def TwoOutput():
return 1, 2
Any suggestion is appreciated
You cannot return the list [1, np.zeros(shape=[5, 5]), 3] from a Numba jitted function. In fact, if you try, Numba will throw few error saying that the "compilation is falling back to object mode WITH looplifting enabled because Function "Cal" failed type inference" due to the output type being not well defined. Indeed, the type of the items in the list needs to be all the same and not objects (called typed list). This is not the case here (reflected list). Reflected lists are not supported by Numba (anymore). What makes Numba fast is the type inference enabling it to generate a fast native code. With Python dynamic objects there is no way to generate a fast code (due to many heavy overhead like type checking, reference counting, allocations, etc.).
Note that you can return a tuple if the output always have the same small number of item defined at compile-time. Also note that Numba can automatically infer the output type so you can use @nb.jit(()) here to enable the eager compilation of the target function.
Put it shortly, Numba is not meant to support/speed-up this use-case. Note that Cython can and be slightly faster. You need not to use reflected lists (nor dynamic objects) if you want to get a fast code.