Numpy function round throws error using numba jitclass - numpy

Question

I want to use the numpy.round_ ina method of a class.
Any calculation done by methods of this class I want to accelerate by using numba.
In general, it works fine. But I somehow do not get numpy.round_ running.
When using numpy.round_ numba throws an error.
Here is my code of a reduced example:
from numba import types
from numba.experimental import jitclass
import numpy as np
spec = [
('arr', types.Array(types.uint8, 1, 'C')),
('quot', types.Array(types.float64, 1, 'C')),
]
#jitclass(spec)
class test:
def __init__(self):
self.arr = np.array((130,190,130),dtype=np.uint8)
def rnd_(self):
quot = np.zeros(3, dtype=np.float64)
val = self.arr
quot = np.round(val/3.0)
return quot
t = test()
a = t.rnd_()
It throws the following error:
TypingError: - Resolution failure for literal arguments:
Failed in nopython mode pipeline (step: nopython frontend)
No implementation of function Function(<function round_ at 0x0000021B3500D870>) found for signature:
round_(array(float64, 1d, C))
There are 4 candidate implementations:
- Of which 4 did not match due to:
Overload in function '_OverloadWrapper._build.<locals>.ol_generated': File: numba\core\overload_glue.py: Line 131.
With argument(s): '(array(float64, 1d, C))':
Rejected as the implementation raised a specific error:
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
No implementation of function Function(<intrinsic stub>) found for signature:
stub(array(float64, 1d, C))
There are 2 candidate implementations:
- Of which 2 did not match due to:
Intrinsic of function 'stub': File: numba\core\overload_glue.py: Line 35.
With argument(s): '(array(float64, 1d, C))':
No match.
During: resolving callee type: Function(<intrinsic stub>)
During: typing of call at <string> (3)
File "<string>", line 3:
<source missing, REPL/exec in use?>
raised from C:\ProgramData\Anaconda3\envs\mybase_conda\lib\site-packages\numba\core\typeinfer.py:1086
During: resolving callee type: Function(<function round_ at 0x0000021B3500D870>)
During: typing of call at .......\python\playground\tmp.py (27)
File "tmp.py", line 27:
def rnd_(self):
<source elided>
val = self.arr
quot = np.round(val/3.0)
^
- Resolution failure for non-literal arguments:
None
During: resolving callee type: BoundFunction((<class 'numba.core.types.misc.ClassInstanceType'>, 'rnd_') for instance.jitclass.test#21b3c031930<arr:array(uint8, 1d, C),quot:array(float64, 1d, C)>)
During: typing of call at <string> (3)
What am I doing wrong?

Answer 1

Seems like you need to pass round's optional arguments as well. I could reproduce the error with an even smaller example:
#nb.jit(nopython=True)
def foo(x):
return np.round(x)
The fix to this is something like:
#nb.jit(nopython=True)
def foo(x):
out = np.empty_like(x)
np.round(x, 0, out)
return out
So for your case, it should be:
def rnd_(self):
quot = np.zeros(3, dtype=np.float64)
np.round(self.arr / 3.0, 0, quot)
return quot