Is it possible to write recursive anonymous functions in SML? I know I could just use the fun syntax, but I'm curious.
I have written, as an example of what I want:
val fact =
fn n => case n of
0 => 1
| x => x * fact (n - 1)
The anonymous function aren't really anonymous anymore when you bind it to a
variable. And since val rec is just the derived form of fun with no
difference other than appearance, you could just as well have written it using
the fun syntax. Also you can do pattern matching in fn expressions as well
as in case, as cases are derived from fn.
So in all its simpleness you could have written your function as
val rec fact = fn 0 => 1
| x => x * fact (x - 1)
but this is the exact same as the below more readable (in my oppinion)
fun fact 0 = 1
| fact x = x * fact (x - 1)
As far as I think, there is only one reason to use write your code using the
long val rec, and that is because you can easier annotate your code with
comments and forced types. For examples if you have seen Haskell code before and
like the way they type annotate their functions, you could write it something
like this
val rec fact : int -> int =
fn 0 => 1
| x => x * fact (x - 1)
As templatetypedef mentioned, it is possible to do it using a fixed-point
combinator. Such a combinator might look like
fun Y f =
let
exception BlackHole
val r = ref (fn _ => raise BlackHole)
fun a x = !r x
fun ta f = (r := f ; f)
in
ta (f a)
end
And you could then calculate fact 5 with the below code, which uses anonymous
functions to express the faculty function and then binds the result of the
computation to res.
val res =
Y (fn fact =>
fn 0 => 1
| n => n * fact (n - 1)
)
5
The fixed-point code and example computation are courtesy of Morten Brøns-Pedersen.
Updated response to George Kangas' answer:
In languages I know, a recursive function will always get bound to a
name. The convenient and conventional way is provided by keywords like
"define", or "let", or "letrec",...
Trivially true by definition. If the function (recursive or not) wasn't bound to a name it would be anonymous.
The unconventional, more anonymous looking, way is by lambda binding.
I don't see what unconventional there is about anonymous functions, they are used all the time in SML, infact in any functional language. Its even starting to show up in more and more imperative languages as well.
Jesper Reenberg's answer shows lambda binding; the "anonymous"
function gets bound to the names "f" and "fact" by lambdas (called
"fn" in SML).
The anonymous function is in fact anonymous (not "anonymous" -- no quotes), and yes of course it will get bound in the scope of what ever function it is passed onto as an argument. In any other cases the language would be totally useless. The exact same thing happens when calling map (fn x => x) [.....], in this case the anonymous identity function, is still in fact anonymous.
The "normal" definition of an anonymous function (at least according to wikipedia), saying that it must not be bound to an identifier, is a bit weak and ought to include the implicit statement "in the current environment".
This is in fact true for my example, as seen by running it in mlton with the -show-basis argument on an file containing only fun Y ... and the val res ..
val Y: (('a -> 'b) -> 'a -> 'b) -> 'a -> 'b
val res: int32
From this it is seen that none of the anonymous functions are bound in the environment.
A shorter "lambdanonymous" alternative, which requires OCaml launched
by "ocaml -rectypes":
(fun f n -> f f n)
(fun f n -> if n = 0 then 1 else n * (f f (n - 1))
7;; Which produces 7! = 5040.
It seems that you have completely misunderstood the idea of the original question:
Is it possible to write recursive anonymous functions in SML?
And the simple answer is yes. The complex answer is (among others?) an example of this done using a fix point combinator, not a "lambdanonymous" (what ever that is supposed to mean) example done in another language using features not even remotely possible in SML.
All you have to do is put rec after val, as in
val rec fact =
fn n => case n of
0 => 1
| x => x * fact (n - 1)
Wikipedia describes this near the top of the first section.
let fun fact 0 = 1
| fact x = x * fact (x - 1)
in
fact
end
This is a recursive anonymous function. The name 'fact' is only used internally.
Some languages (such as Coq) use 'fix' as the primitive for recursive functions, while some languages (such as SML) use recursive-let as the primitive. These two primitives can encode each other:
fix f => e
:= let rec f = e in f end
let rec f = e ... in ... end
:= let f = fix f => e ... in ... end
In languages I know, a recursive function will always get bound to a name. The convenient and conventional way is provided by keywords like "define", or "let", or "letrec",...
The unconventional, more anonymous looking, way is by lambda binding. Jesper Reenberg's answer shows lambda binding; the "anonymous" function gets bound to the names "f" and "fact" by lambdas (called "fn" in SML).
A shorter "lambdanonymous" alternative, which requires OCaml launched by "ocaml -rectypes":
(fun f n -> f f n)
(fun f n -> if n = 0 then 1 else n * (f f (n - 1))
7;;
Which produces 7! = 5040.
Related
I'm new to F#, and functional languages. So this might be stupid question, or duplicated with this Recursive objects in F#?, but I don't know.
Here is a simple Fibonacci function:
let rec fib n =
match n with
| 0 -> 1
| 1 -> 1
| _ -> fib (n - 1) + fib (n - 2)
Its signature is int -> int.
It can be rewritten as:
let rec fib =
fun n ->
match n with
| 0 -> 1
| 1 -> 1
| _ -> fib (n - 1) + fib (n - 2)
Its signature is (int -> int) (in Visual Studio for Mac).
So what's the difference with the previous one?
If I add one more line like this:
let rec fib =
printfn "fib" // <-- this line
fun n ->
match n with
| 0 -> 1
| 1 -> 1
| _ -> fib (n - 1) + fib (n - 2)
The IDE gives me a warning:
warning FS0040: This and other recursive references to the object(s) being defined will be checked for initialization-soundness at runtime through the use of a delayed reference. This is because you are defining one or more recursive objects, rather than recursive functions. This warning may be suppressed by using '#nowarn "40"' or '--nowarn:40'.
How does this line affect the initialization?
What does "recursive object" mean? I can't find it in the documentation.
Update
Thanks for your replies, really nice explanation.
After reading your answers, I have some ideas about the Recursive Object.
First, I made a mistake about the signature. The first two code snippets above have a same signature, int -> int; but the last has signature (int -> int) (note: the signatures have different representation in vscode with Ionide extension).
I think the difference between the two signatures is, the first one means it's just a function, the other one means it's a reference to a function, that is, an object.
And every let rec something with no parameter-list is an object rather than a function, see the function definition, while the second snippet is an exception, possibly optimized by the compiler to a function.
One example:
let rec x = (fun () -> x + 1)() // same warning, says `x` is an recursive object
The only one reason I can think of is the compiler is not smart enough, it throws an warning just because it's a recursive object, like the warning indicates,
This is because you are defining one or more recursive objects, rather than recursive functions
even though this pattern would never have any problem.
let rec fib =
// do something here, if fib invoked here directly, it's definitely an error, not warning.
fun n ->
match n with
| 0 -> 1
| 1 -> 1
| _ -> fib (n - 1) + fib (n - 2)
What do you think about this?
"Recursive objects" are just like recursive functions, except they are, well, objects. Not functions.
A recursive function is a function that references itself, e.g.:
let rec f x = f (x-1) + 1
A recursive object is similar, in that it references itself, except it's not a function, e.g.:
let rec x = x + 1
The above will actually not compile. The F# compiler is able to correctly determine the problem and issue an error: The value 'x' will be evaluated as part of its own definition. Clearly, such definition is nonsensical: in order to calculate x, you need to already know x. Does not compute.
But let's see if we can be more clever. How about if I close x in a lambda expression?
let rec x = (fun() -> x + 1) ()
Here, I wrap the x in a function, and immediately call that function. This compiles, but with a warning - the same warning that you're getting, something about "checking for initialization-soundness at runtime".
So let's go to runtime:
> let rec x = (fun() -> x + 1) ()
System.InvalidOperationException: ValueFactory attempted to access the Value property of this instance.
Not surprisingly, we get an error: turns out, in this definition, you still need to know x in order to calculate x - same as with let rec x = x + 1.
But if this is the case, why does it compile at all? Well, it just so happens that, in general, it is impossible to strictly prove that x will or will not access itself during initialization. The compiler is just smart enough to notice that it might happen (and this is why it issues the warning), but not smart enough to prove that it will definitely happen.
So in cases like this, in addition to issuing a warning, the compiler will install a runtime guard, which will check whether x has already been initialized when it's being accessed. The compiled code with such guard might look something like this:
let mutable x_initialized = false
let rec x =
let x_temp =
(fun() ->
if not x_initialized then failwith "Not good!"
else x + 1
) ()
x_initialized <- true
x_temp
(the actual compiled code looks differently of course; use ILSpy to look if you're curious)
In certain special cases, the compiler can prove one way or another. In other cases it can't, so it installs runtime protection:
// Definitely bad => compile-time error
let rec x = x + 1
// Definitely good => no errors, no warnings
let rec x = fun() -> x() + 1
// Might be bad => compile-time warning + runtime guard
let rec x = (fun() -> x+1) ()
// Also might be bad: no way to tell what the `printfn` call will do
let rec x =
printfn "a"
fun() -> x() + 1
There's a major difference between the last two versions. Notice adding a printfn call to the first version generates no warning, and "fib" will be printed each time the function recurses:
let rec fib n =
printfn "fib"
match n with
| 0 -> 1
| 1 -> 1
| _ -> fib (n - 1) + fib (n - 2)
> fib 10;;
fib
fib
fib
...
val it : int = 89
The printfn call is part of the recursive function's body. But the 3rd/final version only prints "fib" once when the function is defined then never again.
What's the difference? In the 3rd version you're not defining just a recursive function, because there are other expressions creating a closure over the lambda, resulting in a recursive object. Consider this version:
let rec fib3 =
let x = 1
let y = 2
fun n ->
match n with
| 0 -> x
| 1 -> x
| _ -> fib3 (n - x) + fib3 (n - y)
fib3 is not a plain recursive function; there's a closure over the function capturing x and y (and same for the printfn version, although it's just a side-effect). This closure is the "recursive object" referred to in the warning. x and y will not be redefined in each recursion; they're part of the root-level closure/recursive object.
From the linked question/answer:
because [the compiler] cannot guarantee that the reference won't be accessed before it is initialized
Although it doesn't apply in your particular example, it's impossible for the compiler to know whether you're doing something harmless, or potentially referencing/invoking the lambda in fib3 definition before fib3 has a value/has been initialized. Here's another good answer explaining the same.
The function:
fn : 'a -> 'b
Now, are there any functions which can be defined and have this type?
There are two possible implementations for that function signature in Standard ML. One employs exceptions, the other recursion:
val raises : 'a -> 'b =
fn a => raise Fail "some error";
(* Infinite looping; satisfies the type signature, *)
(* but won't ever produce anything. *)
val rec loops : 'a -> 'b =
fn a => loops a;
The first solution may be useful for defining a helper function, say bug, which saves a few key strokes:
fun bug msg = raise Fail ("BUG: " ^ msg);
The other solution may be useful for defining server loops or REPLs.
In the Basis library, OS.Process.exit is such a function that returns an unknown generic type 'a:
- OS.Process.exit;
val it = fn : OS.Process.status -> 'a
A small echo REPL with type val repl = fn : unit -> 'a:
fun repl () =
let
val line = TextIO.inputLine TextIO.stdIn
in
case line of
NONE => OS.Process.exit OS.Process.failure
| SOME ":q\n" => OS.Process.exit OS.Process.success
| SOME line => (TextIO.print line ; repl ())
end
You might also find useful this question about the type signature of Haskell's forever function.
I can think of one example:
fun f a = raise Div;
I can think of several:
One that is recursive,
fun f x = f x
Any function that raises exceptions,
fun f x = raise SomeExn
Any function that is mutually recursive, e.g.,
fun f x = g x
and g x = f x
Any function that uses casting (requires specific compiler support, below is for Moscow ML),
fun f x = Obj.magic x
Breaking the type system like this is probably cheating, but unlike all the other functions with this type, this function actually returns something. (In the simplest case, it's the identity function.)
A function that throws if the Collatz conjecture is false, recurses infinitely if true,
fun f x =
let fun loop (i : IntInf.int) =
if collatz i
then loop (i+1)
else raise Collatz
in loop 1 end
which is really just a combination of the first two.
Any function that performs arbitrary I/O and recurses infinitely, e.g.
fun f x = (print "Woohoo!"; f x)
fun repl x =
let val y = read ()
val z = eval y
val _ = print z
in repl x end
One may argue that exceptions and infinite recursion represent the same theoretical value ⊥ (bottom) meaning "no result", although since you can catch exceptions and not infinitely recursive functions, you may also argue they're different.
If you restrict yourself to pure functions (e.g. no printing or exceptions) and only Standard ML (and not compiler-specific features) and you think of the mutually recursive cases as functionally equivalent in spite of their different recursion schemes, we're back to just fun f x = f x.
The reason why fun f x = f x has type 'a → 'b is perhaps obvious: The type-inference algorithm assumes that the input type and the output type are 'a and 'b respectively and goes on to conclude the function's only constraint: That f x's input type must be equal to f x's input type, and that f x's output type must be equal to f x's output type, at which point the types 'a and 'b have not been specialized any further.
Long story short, I came up with this funny function set, that takes a function, f : 'k -> 'v, a chosen value, k : 'k, a chosen result, v : 'v, uses f as the basis for a new function g : 'k -> 'v that is the exact same as f, except for that it now holds that, g k = v.
Here is the (pretty simple) F# code I wrote in order to make it:
let set : ('k -> 'v) -> 'k -> 'v -> 'k -> 'v =
fun f k v x ->
if x = k then v else f x
My questions are:
Does this function pose any problems?
I could imagine repeat use of the function, like this
let kvs : (int * int) List = ... // A very long list of random int pairs.
List.fold (fun f (k,v) -> set f k v) id kvs
would start building up a long list of functions on the heap. Is this something to be concerned about?
Is there a better way to do this, while still keeping the type?
I mean, I could do stuff like construct a type for holding the original function, f, a Map, setting key-value pairs to the map, and checking the map first, the function second, when using keys to get values, but that's not what interests me here - what interest me is having a function for "modifying" a single result for a given value, for a given function.
Potential problems:
The set-modified function leaks space if you override the same value twice:
let huge_object = ...
let small_object = ...
let f0 = set f 0 huge_object
let f1 = set f0 0 small_object
Even though it can never be the output of f1, huge_object cannot be garbage-collected until f1 can: huge_object is referenced by f0, which is in turn referenced by the f1.
The set-modified function has overhead linear in the number of set operations applied to it.
I don't know if these are actual problems for your intended application.
If you wish set to have exactly the type ('k -> 'v) -> 'k -> 'v -> 'k -> 'v then I don't see a better way(*). The obvious idea would be to have a "modification table" of functions you've already modified, then let set look up a given f in this table. But function types do not admit equality checking, so you cannot compare f to the set of functions known to your modification table.
(*) Reflection not withstanding.
This isn't a homework question, by the way. It got brought up in class but my teacher couldn't think of any. Thanks.
How do you define the identity functions ? If you're only considering the syntax, there are different identity functions, which all have the correct type:
let f x = x
let f2 x = (fun y -> y) x
let f3 x = (fun y -> y) (fun y -> y) x
let f4 x = (fun y -> (fun y -> y) y) x
let f5 x = (fun y z -> z) x x
let f6 x = if false then x else x
There are even weirder functions:
let f7 x = if Random.bool() then x else x
let f8 x = if Sys.argv < 5 then x else x
If you restrict yourself to a pure subset of OCaml (which rules out f7 and f8), all the functions you can build verify an observational equation that ensures, in a sense, that what they compute is the identity : for all value f : 'a -> 'a, we have that f x = x
This equation does not depend on the specific function, it is uniquely determined by the type. There are several theorems (framed in different contexts) that formalize the informal idea that "a polymorphic function can't change a parameter of polymorphic type, only pass it around". See for example the paper of Philip Wadler, Theorems for free!.
The nice thing with those theorems is that they don't only apply to the 'a -> 'a case, which is not so interesting. You can get a theorem out of the ('a -> 'a -> bool) -> 'a list -> 'a list type of a sorting function, which says that its application commutes with the mapping of a monotonous function.
More formally, if you have any function s with such a type, then for all types u, v, functions cmp_u : u -> u -> bool, cmp_v : v -> v -> bool, f : u -> v, and list li : u list, and if cmp_u u u' implies cmp_v (f u) (f u') (f is monotonous), you have :
map f (s cmp_u li) = s cmp_v (map f li)
This is indeed true when s is exactly a sorting function, but I find it impressive to be able to prove that it is true of any function s with the same type.
Once you allow non-termination, either by diverging (looping indefinitely, as with the let rec f x = f x function given above), or by raising exceptions, of course you can have anything : you can build a function of type 'a -> 'b, and types don't mean anything anymore. Using Obj.magic : 'a -> 'b has the same effect.
There are saner ways to lose the equivalence to identity : you could work inside a non-empty environment, with predefined values accessible from the function. Consider for example the following function :
let counter = ref 0
let f x = incr counter; x
You still that the property that for all x, f x = x : if you only consider the return value, your function still behaves as the identity. But once you consider side-effects, you're not equivalent to the (side-effect-free) identity anymore : if I know counter, I can write a separating function that returns true when given this function f, and would return false for pure identity functions.
let separate g =
let before = !counter in
g ();
!counter = before + 1
If counter is hidden (for example by a module signature, or simply let f = let counter = ... in fun x -> ...), and no other function can observe it, then we again can't distinguish f and the pure identity functions. So the story is much more subtle in presence of local state.
let rec f x = f (f x)
This function never terminates, but it does have type 'a -> 'a.
If we only allow total functions, the question becomes more interesting. Without using evil tricks, it's not possible to write a total function of type 'a -> 'a, but evil tricks are fun so:
let f (x:'a):'a = Obj.magic 42
Obj.magic is an evil abomination of type 'a -> 'b which allows all kinds of shenanigans to circumvent the type system.
On second thought that one isn't total either because it will crash when used with boxed types.
So the real answer is: the identity function is the only total function of type 'a -> 'a.
Throwing an exception can also give you an 'a -> 'a type:
# let f (x:'a) : 'a = raise (Failure "aaa");;
val f : 'a -> 'a = <fun>
If you restrict yourself to a "reasonable" strongly normalizing typed λ-calculus, there is a single function of type ∀α α→α, which is the identity function. You can prove it by examining the possible normal forms of a term of this type.
Philip Wadler's 1989 article "Theorems for Free" explains how functions having polymorphic types necessarily satisfy certain theorems (e.g. a map-like function commutes with composition).
There are however some nonintuitive issues when one deals with much polymorphism. For instance, there is a standard trick for encoding inductive types and recursion with impredicative polymorphism, by representing an inductive object (e.g. a list) using its recursor function. In some cases, there are terms belonging to the type of the recursor function that are not recursor functions; there is an example in §4.3.1 of Christine Paulin's PhD thesis.
I'm new to ocaml and tryin to write a continuation passing style function but quite confused what value i need to pass into additional argument on k
for example, I can write a recursive function that returns true if all elements of the list is even, otherwise false.
so its like
let rec even list = ....
on CPS, i know i need to add one argument to pass function
so like
let rec evenk list k = ....
but I have no clue how to deal with this k and how does this exactly work
for example for this even function, environment looks like
val evenk : int list -> (bool -> ’a) -> ’a = <fun>
evenk [4; 2; 12; 5; 6] (fun x -> x) (* output should give false *)
The continuation k is a function that takes the result from evenk and performs "the rest of the computation" and produces the "answer". What type the answer has and what you mean by "the rest of the computation" depends on what you are using CPS for. CPS is generally not an end in itself but is done with some purpose in mind. For example, in CPS form it is very easy to implement control operators or to optimize tail calls. Without knowing what you are trying to accomplish, it's hard to answer your question.
For what it is worth, if you are simply trying to convert from direct style to continuation-passing style, and all you care about is the value of the answer, passing the identity function as the continuation is about right.
A good next step would be to implement evenk using CPS. I'll do a simpler example.
If I have the direct-style function
let muladd x i n = x + i * n
and if I assume CPS primitives mulk and addk, I can write
let muladdk x i n k =
let k' product = addk x product k in
mulk i n k'
And you'll see that the mulptiplication is done first, then it "continues" with k', which does the add, and finally that continues with k, which returns to the caller. The key idea is that within the body of muladdk I allocated a fresh continuation k' which stands for an intermediate point in the multiply-add function. To make your evenk work you will have to allocate at least one such continuation.
I hope this helps.
Whenever I've played with CPS, the thing passed to the continuation is just the thing you would normally return to the caller. In this simple case, a nice "intuition lubricant" is to name the continuation "return".
let rec even list return =
if List.length list = 0
then return true
else if List.hd list mod 2 = 1
then return false
else even (List.tl list) return;;
let id = fun x -> x;;
Example usage: "even [2; 4; 6; 8] id;;".
Since you have the invocation of evenk correct (with the identity function - effectively converting the continuation-passing-style back to normal style), I assume that the difficulty is in defining evenk.
k is the continuation function representing the rest of the computation and producing a final value, as Norman said. So, what you need to do is compute the result of v of even and pass that result to k, returning k v rather than just v.
You want to give as input the result of your function as if it were not written with continuation passing style.
Here is your function which tests whether a list has only even integers:
(* val even_list : int list -> bool *)
let even_list input = List.for_all (fun x -> x mod 2=0) input
Now let's write it with a continuation cont:
(* val evenk : int list -> (bool -> 'a) -> 'a *)
let evenk input cont =
let result = even_list input in
(cont result)
You compute the result your function, and pass resultto the continuation ...