CODEWITHSUNDEEP
pythonnumba
MB-F
MB-F

Reputation: 23647

Where do `@numba.jitclass`ed special methods go?

TL;DR: When decorating a class with @numba.jitclass special methods such as __add__ do not appear in instances of the class, while other methods work normally. Why does this happen?

Consider the following class declaration:

import numba as nb            

dual_spec = [('x', nb.float64), ('y', nb.float64)]                 

@nb.jitclass(dual_spec)
class xy:
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def addition(self, other):
        return xy(self.x + other.x, self.y + other.y)

    def __add__(self, other):
        return xy(self.x + other.x, self.y + other.y)

Without the decorator the class works perfectly fine. Due to the __add__ method expressions like xy(1, 2) + xy(3, 4) are possible and return expected results. However, with the decorator I get the following error message:

>>> xy(1, 2) + xy(3, 4)  # TypeError: unsupported operand type(s) for +: 'xy' and 'xy'
>>> xy(1, 2).addition(xy(3, 4))  # But this works nicely

It looks like the __add__ method is not present in xy objects:

>>> xy(1, 2).__add__  # AttributeError: 'xy' object has no attribute '__add__'

But the method is present in the class:

>>> xy.__add__  # <function __main__.xy.__add__>

What is numba doing to the __add__ method during instantiation? Is there another way to enable operators for jitted classes so that I can write xy(1, 2) + xy(3, 4)?

Upvotes: 3

Views: 372

Answers (1)

chrisb
chrisb

Reputation: 52286

Currently (as of numba version 0.33) operator overloading on jitclasses is not supported, open issue here: https://github.com/numba/numba/issues/1606#issuecomment-284552746

I don't know the exact internals, but it is likely the method is simply being discarded. Note that when you instantiate at a jitclass you are not directly instantiating the python class but instead are getting a wrapper around the low-level numba type.

v = xy(1, 2)

v
Out[8]: <numba.jitclass.boxing.xy at 0x2e700274950>

v._numba_type_
Out[9]: instance.jitclass.xy#2e77d394438<x:float64,y:float64>

Upvotes: 4

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