[Cython] CF based type inference

[Nathaniel Smith]

On Sun, Jun 2, 2013 at 7:22 AM, Stefan Behnel <stefan_ml at behnel.de> wrote:
> mark florisson, 21.05.2013 15:32:
>> On 21 May 2013 14:14, Vitja Makarov wrote:
>>>
>>> def foo(int N):
>>>     x = 1
>>>     y = 0
>>>     for i in range(N):
>>>         x = x * 0.1 + y * 0.2
>>>         y = x * 0.3 + y * 0.4
>>>     print typeof(x), typeof(y)
>>>
>>> Here both x and y will be inferred as double
>>
>> Ok, so I assume it promotes the incoming types (all reaching
>> definitions)? If N == 0, then when using objects you get an int,
>> otherwise a double.
>
> I'm not sure what you mean here. I certainly don't think the inferred type
> of x and y should depend on the value of N. It should always be a double,
> because that's the spanning type for all paths. In the very unlikely case
> that that's not what the user wants, explicit typing will easily fix it for
> them.

But 'double' does not actually span 'int', floats and integers are
different in all kinds of corner cases. Both have values that are
unrepresentable in the other, etc. So this optimization as stated
is... not an optimization, it's just wrong.

I mean obviously in this example double would be fine, but how do you
decide when it's okay to randomly reinterpret users' code as meaning
something different than what they wrote, and when it isn't? It's not
that I think the Python rules here are particularly awesome, or that I
on purpose write code that sometimes returns ints and sometimes
doubles. But at least I know what the Python rules are, which means I
can always look at a chunk of code and figure out what the interpreter
will do. This is why people writing serious C compilers are so anal
about obscure problems like aliasing and guaranteeing that you get
segfaults at the right time, and generally insisting that
optimizations must *exactly* preserve semantics. I'm worried from this
discussion that in Cython, the rule for how variables are typed will
become "well, you get whatever types our type inference engine
guessed; dropping ordinary Python code into Cython might change the
outputs or might not; if you want to know 100% what your code will do
then your only option is to either put explicit types on every single
variable or else go read the source code for the inference engine in
the specific version of Cython you're using".

-n