ah, ok, thanks. andrew
On Wednesday, 5 March 2014 19:03:49 UTC-3, Simon Kornblith wrote:
>
> If you have e.g. a function that always returns Int, then you can specify
> the associative type as Dict{Any,Int}, which allows type inference to
> determine that anything pulled out of it is an Int, so the return type of
> the memoized function can be inferred:
>
> julia> using Memoize
>
> julia> @memoize Dict{Any,Int} f(y) = y + 1
>
> julia> Base.return_types(f, (Int,))
> 1-element Array{Any,1}:
> Int64
>
> Of course this doesn't work if you don't specify the Dict type:
>
> julia> @memoize f(y) = y + 1
>
> julia> Base.return_types(f, (Int,))
> 1-element Array{Any,1}:
> Any
>
> Simon
>
> On Wednesday, March 5, 2014 2:53:09 PM UTC-5, andrew cooke wrote:
>>
>> we're talking about
>> https://github.com/simonster/Memoize.jl/blob/master/src/Memoize.jl ?
>>
>> i must be missing something. where is the type?
>>
>> thanks,
>> andrew
>>
>> On Wednesday, 5 March 2014 16:24:34 UTC-3, Pierre-Yves Gérardy wrote:
>>>
>>> It already accepts a type as an optional parameter.
>>>
>>> On Wednesday, March 5, 2014 7:41:42 PM UTC+1, andrew cooke wrote:
>>>>
>>>>
>>>> it seemed to me (when i looked at the code) that would be trivial to
>>>> add to Memoize.jl by adding a type parameter to the macro and reading from
>>>> the cache into a typed variable.
>>>>
>>>> but since i spilt coke all over my netbook yesterday my julia
>>>> programming is on hiatus :o(
>>>>
>>>> andrew
>>>>
>>>>
>>>> On Wednesday, 5 March 2014 10:26:37 UTC-3, Toivo Henningsson wrote:
>>>>>
>>>>> The trouble with memoization and type inference is that when type
>>>>> inference sees a memoized function, it will see that the return value is
>>>>> either computed, or looked up in the cache. The type of the cached value
>>>>> might be anything, unless the user supplies an explicit type restriction.
>>>>> There's no way to tell type inference that the cached must have been
>>>>> computed by the function previously, so that it can be disregarded when
>>>>> it
>>>>> comes to inferring the return type.
>>>>>
>>>>> On Wednesday, 5 March 2014 01:34:10 UTC+1, Pierre-Yves Gérardy wrote:
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Tuesday, March 4, 2014 3:01:13 AM UTC+1, andrew cooke wrote:
>>>>>>>
>>>>>>>
>>>>>>> i assumed that passing by value was an optimization, but i don't
>>>>>>> know what triggers it. it may be that it's only for immutable types
>>>>>>> without pointers to mutable types. or it may be based on size. it
>>>>>>> might
>>>>>>> be something to worry about if your instances are large.
>>>>>>>
>>>>>>> there's a memoize.jl module somewhere that defines a macro that
>>>>>>> automatically memoizes the function it's applied to. so you could use
>>>>>>> that
>>>>>>> on your constructor function, but:
>>>>>>>
>>>>>>> 1 - i'm not sure how nesting affects things
>>>>>>>
>>>>>> 2 - when i looked at memoize.jl, by default it used a simple map (no
>>>>>>> weak keys or lru eviction)
>>>>>>>
>>>>>>
>>>>>> Yes, but you can pass a collection of your choice as a cache. Julia
>>>>>> provides a WeakKeyDict, but if your function depends on multiple inputs,
>>>>>> using tuples as keys makes it moot.
>>>>>>
>>>>>> I'll go ahead and skip this whole identity thing for now :-)
>>>>>>
>>>>>> 3 - someone said that using memoize.jl broke type inference of
>>>>>>> return arguments (i don't understand why) which had a performance
>>>>>>> impact.
>>>>>>>
>>>>>>
>>>>>> That was Stephan Karpinski. I wonder if it holds when using a
>>>>>> `memoize` macro that creates a named function and a typed cache.
>>>>>>
>>>>>> —Pierre-Yves
>>>>>>
>>>>>
