Debugging F# that just hangs - f#

Is it possible to debug F# or, like LINQ in C#, is this effectively impossible?
I'm working through Machine Learning Projects for .NET Developers and am using F# for the first time.
I tried to edit the example exercise. The C# version was easy to get running, but my attempt at the F# version just hangs.
What can I do to trace the problem?
open System.IO
type Observation = { Label:string; Pixels: int[] }
type Distance = int[] * int[] -> int
type Classifier = int[] -> string
let toObservation (csvData:string) =
let columns = csvData.Split(',')
let label = columns.[0]
let pixels = columns.[1..] |> Array.map int
{ Label = label; Pixels = pixels }
let reader path =
let data = File.ReadAllLines path
data.[1..]
|> Array.map toObservation
let trainingPath = __SOURCE_DIRECTORY__ + #"../../Data/trainingsample.csv"
let training = reader trainingPath
let manhattanDistance (pixels1,pixels2) =
Array.zip pixels1 pixels2
|> Array.map (fun (x,y) -> abs (x-y))
|> Array.sum
let euclideanDistance (pixels1,pixels2) =
Array.zip pixels1 pixels2
|> Array.map (fun (x,y) -> pown (x-y) 2)
|> Array.sum
let dotCountDistance(pixels1, pixels2) =
let t1 = pixels1 |> Array.map (fun(z) -> if z > 128 then 1 else 0) |> Array.sum
let t2 = pixels2 |> Array.map (fun(z) -> if z > 128 then 1 else 0) |> Array.sum
abs(t1 - t2)
let train (trainingset:Observation[]) (dist:Distance) =
let classify (pixels:int[]) =
trainingset
|> Array.minBy (fun x -> dist (x.Pixels, pixels))
|> fun x -> x.Label
classify
//
// This is my new function
//
let train2 (trainingset:Observation[]) (dist:Distance) =
let classify (pixels:int[]) =
trainingset
|> Array.map (fun(z) -> dist(z.Pixels, pixels), z.Label)
|> Array.groupBy(fun (a, y) -> y)
|> Array.map(fun (lbl, ds) -> lbl, (ds |> Array.map(fun (p, q) -> p) |> Array.sum ) * 100 / (ds |> Array.length))
|> Array.sortByDescending( fun (lbl, s) -> s)
|> fun z -> z.[0]
|> fun (lbl, s) -> lbl
classify
//
//
//
let validationPath = __SOURCE_DIRECTORY__ + #"../../Data/validationsample.csv"
let validation = reader validationPath
let evaluate validationSet classifier =
validationSet
|> Array.averageBy (fun x -> if classifier x.Pixels = x.Label then 1. else 0.)
|> printfn "Correct: %.3f"
let manhattanModel = train training manhattanDistance
let euclideanModel = train training euclideanDistance
let dotCountModel = train training dotCountDistance
let manhattanModel2 = train2 training manhattanDistance
let euclideanModel2 = train2 training euclideanDistance
let dotCountModel2 = train2 training dotCountDistance
printfn "Manhattan"
evaluate validation manhattanModel // <------------------- This just hangs.
printfn "Euclidean"
evaluate validation euclideanModel
printfn "Dot Count"
evaluate validation dotCountModel
// Illustration: full distance function
let d (X,Y) =
Array.zip X Y
|> Array.map (fun (x,y) -> pown (x-y) 2)
|> Array.sum
|> sqrt
Here is ,y C# version that works
return data.Select(z => new { z.Label, D = distance.Between(z.Pixels, pixels) })
.GroupBy(z => z.Label)
.Select(z => new { Label = z.Key, MeanDistance = z.Average(y => y.D) })
.OrderBy(z => z.MeanDistance).First()
.Label;

You can debug a script in F# Interactive (make sure you have this option turned on, first).
I had the same behavior you did, it hangs. I ran the same code as a console program, and it ran in a few seconds. (The output was "Correct: 0.934"). So, I believe this is a problem, perhaps a bug, with F# Interactive.

Related

parallel computation does not produce a result?

My code seems to freeze up after the last iteration on my async workflow. is it a bug in the code or does it simply take realy long (20 min plus) to wrap up the work flow?
let rec list_primes x y =
//returns an array with all primes between x and y
if x < y then
if is_prime x (x |> sqrt |> floor) then
printfn "%A" x
x :: list_primes (x + 1.0) y
else
let n_x = x |> next_prime
n_x :: list_primes (n_x + 1.0) y
else
[]
let filt (x:float) =
if x < 10000.0 then
true
else
false
let list_of_primes = List.filter (filt) (list_primes 1000.0 10000.0)
let iter = [0..((List.length list_of_primes)-3)]
let equal_difference (list:List<float>) iter =
printfn "%A" iter
async{
let mutable a = [|[||]|]
for x in (iter + 1)..(list.Length - 1) do
printfn "inside loop, x = %A" x
let temp = test_sum_in_list list.[x] list.[iter] list
//let temp1 = test_sum_in_list (list.[x] + list.[iter]) list.[x] list
if temp then
a <- Array.append a [|[|list.[x]; list.[iter]; (list.[x] + list.[iter]);|]|]
printf "added %A" a
let result = a
return result
}
let result = iter
|> List.map (equal_difference list_of_primes)
|> Async.Parallel
|> Async.RunSynchronously

F# stream of armstrong numbers

I am seeking help, mainly because I am very new to F# environment. I need to use F# stream to generate an infinite stream of Armstrong Numbers. Can any one help with this one. I have done some mambo jumbo but I have no clue where I'm going.
type 'a stream = | Cons of 'a * (unit -> 'a stream)
let rec take n (Cons(x, xsf)) =
if n = 0 then []
else x :: take (n-1) (xsf());;
//to test if two integers are equal
let test x y =
match (x,y) with
| (x,y) when x < y -> false
| (x,y) when x > y -> false
| _ -> true
//to check for armstrong number
let check n =
let mutable m = n
let mutable r = 0
let mutable s = 0
while m <> 0 do
r <- m%10
s <- s+r*r*r
m <- m/10
if (test n s) then true else false
let rec armstrong n =
Cons (n, fun () -> if check (n+1) then armstrong (n+1) else armstrong (n+2))
let pos = armstrong 0
take 5 pos
To be honest your code seems a bit like a mess.
The most basic version I could think of is this:
let isArmstrong (a,b,c) =
a*a*a + b*b*b + c*c*c = (a*100+b*10+c)
let armstrongs =
seq {
for a in [0..9] do
for b in [0..9] do
for c in [0..9] do
if isArmstrong (a,b,c) then yield (a*100+b*10+c)
}
of course assuming a armstrong number is a 3-digit number where the sum of the cubes of the digits is the number itself
this will yield you:
> Seq.toList armstrongs;;
val it : int list = [0; 1; 153; 370; 371; 407]
but it should be easy to add a wider range or remove the one-digit numbers (think about it).
general case
the problem seems so interesting that I choose to implement the general case (see here) too:
let numbers =
let rec create n =
if n = 0 then [(0,[])] else
[
for x in [0..9] do
for (_,xs) in create (n-1) do
yield (n, x::xs)
]
Seq.initInfinite create |> Seq.concat
let toNumber (ds : int list) =
ds |> List.fold (fun s d -> s*10I + bigint d) 0I
let armstrong (m : int, ds : int list) =
ds |> List.map (fun d -> bigint d ** m) |> List.sum
let leadingZero =
function
| 0::_ -> true
| _ -> false
let isArmstrong (m : int, ds : int list) =
if leadingZero ds then false else
let left = armstrong (m, ds)
let right = toNumber ds
left = right
let armstrongs =
numbers
|> Seq.filter isArmstrong
|> Seq.map (snd >> toNumber)
but the numbers get really sparse quickly and using this will soon get you out-of-memory but the
first 20 are:
> Seq.take 20 armstrongs |> Seq.map string |> Seq.toList;;
val it : string list =
["0"; "1"; "2"; "3"; "4"; "5"; "6"; "7"; "8"; "9"; "153"; "370"; "371";
"407"; "1634"; "8208"; "9474"; "54748"; "92727"; "93084"]
remark/disclaimer
this is the most basic version - you can get big speed/performance if you just enumerate all numbers and use basic math to get and exponentiate the digits ;) ... sure you can figure it out

Get a list of invalid drive letters

let private GetDrives = seq{
let all=System.IO.DriveInfo.GetDrives()
for d in all do
//if(d.IsReady && d.DriveType=System.IO.DriveType.Fixed) then
yield d
}
let valid={'A'..'Z'}
let rec SearchRegistryForInvalidDrive (start:RegistryKey) = seq{
let validDrives=GetDrives |> Seq.map (fun x -> x.Name.Substring(0,1))
let invalidDrives= Seq.toList validDrives |> List.filter(fun x-> not (List.exists2 x b)) //(List.exists is the wrong method I think, but it doesn't compile
I followed F#: Filter items found in one list from another list but could not apply it to my problem as both the solutions I see don't seem to compile. List.Contains doesn't exist (missing a reference?) and ListA - ListB doesn't compile either.
open System.IO
let driveLetters = set [ for d in DriveInfo.GetDrives() -> d.Name.[0] ]
let unused = set ['A'..'Z'] - driveLetters
Your first error is mixing between char and string, it is good to start with char:
let all = {'A'..'Z'}
let validDrives = GetDrives |> Seq.map (fun x -> x.Name.[0])
Now invalid drive letters are those letters which are in all but not in validDrives:
let invalidDrives =
all |> Seq.filter (fun c -> validDrives |> List.forall ((<>) c))
Since validDrives is traversed many times to check for membership, turning it to a set is better in this example:
let all = {'A'..'Z'}
let validDrives = GetDrives |> Seq.map (fun x -> x.Name.[0]) |> Set.ofSeq
let invalidDrives = all |> Seq.filter (not << validDrives.Contains)

F# Swap arrays of data and get the correct results

let highs = [| 2; 4; 6 |]
let lows = [| 1; 5; 10 |]
I want to get 2 arrays from the above: if the element in highs is smaller than the corresponding element in lows, then swap them. So, I can get the final 2 arrays:
let trueHighs = [| 2; 5; 10 |]
let trueLows = [| 1; 4; 6 |]
How do I do this?
Similar with JaredPar's answer but simpler:
let trueHighs, trueLows =
Array.zip highs lows
|> Array.map (fun (x, y) -> if x >= y then (x, y) else (y, x))
|> Array.unzip
Another more concise version:
let trueHighs, trueLows =
(highs, lows)
||> Array.map2 (fun x y -> if x >= y then (x, y) else (y, x))
|> Array.unzip
Here is the code you should use:
let n = highs.Length
let trueHighs = Array.init n (fun i -> max highs.[i] lows.[i])
let trueLows = Array.init n (fun i -> min highs.[i] lows.[i])
If performance is uber-critical, you're probably better off with an imperative approach.
let n = highs.Length
let trueHighs = Array.zeroCreate n
let trueLows = Array.zeroCreate n
for i = 0 to n-1 do
let hi = highs.[i]
let lo = lows.[i]
if hi > lo then
trueHighs.[i] <- hi
trueLows.[i] <- lo
else
trueHighs.[i] <- lo
trueLows.[i] <- hi
Try the following
let trueHighs, trueLows =
let zipped =
highs
|> Seq.ofArray
|> Seq.zip (lows |> Seq.ofArray)
|> Seq.map (fun (x, y) -> min x y, max x y)
let lows = zipped |> Seq.map fst |> Array.ofSeq
let highs = zipped |> Seq.map snd |> Array.ofSeq
highs, lows

Combine memoization and tail-recursion

Is it possible to combine memoization and tail-recursion somehow? I'm learning F# at the moment and understand both concepts but can't seem to combine them.
Suppose I have the following memoize function (from Real-World Functional Programming):
let memoize f = let cache = new Dictionary<_, _>()
(fun x -> match cache.TryGetValue(x) with
| true, y -> y
| _ -> let v = f(x)
cache.Add(x, v)
v)
and the following factorial function:
let rec factorial(x) = if (x = 0) then 1 else x * factorial(x - 1)
Memoizing factorial isn't too difficult and making it tail-recursive isn't either:
let rec memoizedFactorial =
memoize (fun x -> if (x = 0) then 1 else x * memoizedFactorial(x - 1))
let tailRecursiveFactorial(x) =
let rec factorialUtil(x, res) = if (x = 0)
then res
else let newRes = x * res
factorialUtil(x - 1, newRes)
factorialUtil(x, 1)
But can you combine memoization and tail-recursion? I made some attempts but can't seem to get it working. Or is this simply not possible?
As always, continuations yield an elegant tailcall solution:
open System.Collections.Generic
let cache = Dictionary<_,_>() // TODO move inside
let memoizedTRFactorial =
let rec fac n k = // must make tailcalls to k
match cache.TryGetValue(n) with
| true, r -> k r
| _ ->
if n=0 then
k 1
else
fac (n-1) (fun r1 ->
printfn "multiplying by %d" n //***
let r = r1 * n
cache.Add(n,r)
k r)
fun n -> fac n id
printfn "---"
let r = memoizedTRFactorial 4
printfn "%d" r
for KeyValue(k,v) in cache do
printfn "%d: %d" k v
printfn "---"
let r2 = memoizedTRFactorial 5
printfn "%d" r2
printfn "---"
// comment out *** line, then run this
//let r3 = memoizedTRFactorial 100000
//printfn "%d" r3
There are two kinds of tests. First, this demos that calling F(4) caches F(4), F(3), F(2), F(1) as you would like.
Then, comment out the *** printf and uncomment the final test (and compile in Release mode) to show that it does not StackOverflow (it uses tailcalls correctly).
Perhaps I'll generalize out 'memoize' and demonstrate it on 'fib' next...
EDIT
Ok, here's the next step, I think, decoupling memoization from factorial:
open System.Collections.Generic
let cache = Dictionary<_,_>() // TODO move inside
let memoize fGuts n =
let rec newFunc n k = // must make tailcalls to k
match cache.TryGetValue(n) with
| true, r -> k r
| _ ->
fGuts n (fun r ->
cache.Add(n,r)
k r) newFunc
newFunc n id
let TRFactorialGuts n k memoGuts =
if n=0 then
k 1
else
memoGuts (n-1) (fun r1 ->
printfn "multiplying by %d" n //***
let r = r1 * n
k r)
let memoizedTRFactorial = memoize TRFactorialGuts
printfn "---"
let r = memoizedTRFactorial 4
printfn "%d" r
for KeyValue(k,v) in cache do
printfn "%d: %d" k v
printfn "---"
let r2 = memoizedTRFactorial 5
printfn "%d" r2
printfn "---"
// comment out *** line, then run this
//let r3 = memoizedTRFactorial 100000
//printfn "%d" r3
EDIT
Ok, here's a fully generalized version that seems to work.
open System.Collections.Generic
let memoize fGuts =
let cache = Dictionary<_,_>()
let rec newFunc n k = // must make tailcalls to k
match cache.TryGetValue(n) with
| true, r -> k r
| _ ->
fGuts n (fun r ->
cache.Add(n,r)
k r) newFunc
cache, (fun n -> newFunc n id)
let TRFactorialGuts n k memoGuts =
if n=0 then
k 1
else
memoGuts (n-1) (fun r1 ->
printfn "multiplying by %d" n //***
let r = r1 * n
k r)
let facCache,memoizedTRFactorial = memoize TRFactorialGuts
printfn "---"
let r = memoizedTRFactorial 4
printfn "%d" r
for KeyValue(k,v) in facCache do
printfn "%d: %d" k v
printfn "---"
let r2 = memoizedTRFactorial 5
printfn "%d" r2
printfn "---"
// comment out *** line, then run this
//let r3 = memoizedTRFactorial 100000
//printfn "%d" r3
let TRFibGuts n k memoGuts =
if n=0 || n=1 then
k 1
else
memoGuts (n-1) (fun r1 ->
memoGuts (n-2) (fun r2 ->
printfn "adding %d+%d" r1 r2 //%%%
let r = r1+r2
k r))
let fibCache, memoizedTRFib = memoize TRFibGuts
printfn "---"
let r5 = memoizedTRFib 4
printfn "%d" r5
for KeyValue(k,v) in fibCache do
printfn "%d: %d" k v
printfn "---"
let r6 = memoizedTRFib 5
printfn "%d" r6
printfn "---"
// comment out %%% line, then run this
//let r7 = memoizedTRFib 100000
//printfn "%d" r7
The predicament of memoizing tail-recursive functions is, of course, that when tail-recursive function
let f x =
......
f x1
calls itself, it is not allowed to do anything with a result of the recursive call, including putting it into cache. Tricky; so what can we do?
The critical insight here is that since the recursive function is not allowed to do anything with a result of recursive call, the result for all arguments to recursive calls will be the same! Therefore if recursion call trace is this
f x0 -> f x1 -> f x2 -> f x3 -> ... -> f xN -> res
then for all x in x0,x1,...,xN the result of f x will be the same, namely res. So the last invocation of a recursive function, the non-recursive call, knows the results for all the previous values - it is in a position to cache them. The only thing you need to do is to pass a list of visited values to it. Here is what it might look for factorial:
let cache = Dictionary<_,_>()
let rec fact0 l ((n,res) as arg) =
let commitToCache r =
l |> List.iter (fun a -> cache.Add(a,r))
match cache.TryGetValue(arg) with
| true, cachedResult -> commitToCache cachedResult; cachedResult
| false, _ ->
if n = 1 then
commitToCache res
cache.Add(arg, res)
res
else
fact0 (arg::l) (n-1, n*res)
let fact n = fact0 [] (n,1)
But wait! Look - l parameter of fact0 contains all the arguments to recursive calls to fact0 - just like the stack would in a non-tail-recursive version! That is exactly right. Any non-tail recursive algorithm can be converted to a tail-recursive one by moving the "list of stack frames" from stack to heap and converting the "postprocessing" of recursive call result into a walk over that data structure.
Pragmatic note: The factorial example above illustrates a general technique. It is quite useless as is - for factorial function it is quite enough to cache the top-level fact n result, because calculation of fact n for a particular n only hits a unique series of (n,res) pairs of arguments to fact0 - if (n,1) is not cached yet, then none of the pairs fact0 is going to be called on are.
Note that in this example, when we went from non-tail-recursive factorial to a tail-recursive factorial, we exploited the fact that multiplication is associative and commutative - tail-recursive factorial execute a different set of multiplications than a non-tail-recursive one.
In fact, a general technique exists for going from non-tail-recursive to tail-recursive algorithm, which yields an algorithm equivalent to a tee. This technique is called "continuatuion-passing transformation". Going that route, you can take a non-tail-recursive memoizing factorial and get a tail-recursive memoizing factorial by pretty much a mechanical transformation. See Brian's answer for exposition of this method.
I'm not sure if there's a simpler way to do this, but one approach would be to create a memoizing y-combinator:
let memoY f =
let cache = Dictionary<_,_>()
let rec fn x =
match cache.TryGetValue(x) with
| true,y -> y
| _ -> let v = f fn x
cache.Add(x,v)
v
fn
Then, you can use this combinator in lieu of "let rec", with the first argument representing the function to call recursively:
let tailRecFact =
let factHelper fact (x, res) =
printfn "%i,%i" x res
if x = 0 then res
else fact (x-1, x*res)
let memoized = memoY factHelper
fun x -> memoized (x,1)
EDIT
As Mitya pointed out, memoY doesn't preserve the tail recursive properties of the memoee. Here's a revised combinator which uses exceptions and mutable state to memoize any recursive function without overflowing the stack (even if the original function is not itself tail recursive!):
let memoY f =
let cache = Dictionary<_,_>()
fun x ->
let l = ResizeArray([x])
while l.Count <> 0 do
let v = l.[l.Count - 1]
if cache.ContainsKey(v) then l.RemoveAt(l.Count - 1)
else
try
cache.[v] <- f (fun x ->
if cache.ContainsKey(x) then cache.[x]
else
l.Add(x)
failwith "Need to recurse") v
with _ -> ()
cache.[x]
Unfortunately, the machinery which is inserted into each recursive call is somewhat heavy, so performance on un-memoized inputs requiring deep recursion can be a bit slow. However, compared to some other solutions, this has the benefit that it requires fairly minimal changes to the natural expression of recursive functions:
let fib = memoY (fun fib n ->
printfn "%i" n;
if n <= 1 then n
else (fib (n-1)) + (fib (n-2)))
let _ = fib 5000
EDIT
I'll expand a bit on how this compares to other solutions. This technique takes advantage of the fact that exceptions provide a side channel: a function of type 'a -> 'b doesn't actually need to return a value of type 'b, but can instead exit via an exception. We wouldn't need to use exceptions if the return type explicitly contained an additional value indicating failure. Of course, we could use the 'b option as the return type of the function for this purpose. This would lead to the following memoizing combinator:
let memoO f =
let cache = Dictionary<_,_>()
fun x ->
let l = ResizeArray([x])
while l.Count <> 0 do
let v = l.[l.Count - 1]
if cache.ContainsKey v then l.RemoveAt(l.Count - 1)
else
match f(fun x -> if cache.ContainsKey x then Some(cache.[x]) else l.Add(x); None) v with
| Some(r) -> cache.[v] <- r;
| None -> ()
cache.[x]
Previously, our memoization process looked like:
fun fib n ->
printfn "%i" n;
if n <= 1 then n
else (fib (n-1)) + (fib (n-2))
|> memoY
Now, we need to incorporate the fact that fib should return an int option instead of an int. Given a suitable workflow for option types, this could be written as follows:
fun fib n -> option {
printfn "%i" n
if n <= 1 then return n
else
let! x = fib (n-1)
let! y = fib (n-2)
return x + y
} |> memoO
However, if we're willing to change the return type of the first parameter (from int to int option in this case), we may as well go all the way and just use continuations in the return type instead, as in Brian's solution. Here's a variation on his definitions:
let memoC f =
let cache = Dictionary<_,_>()
let rec fn n k =
match cache.TryGetValue(n) with
| true, r -> k r
| _ ->
f fn n (fun r ->
cache.Add(n,r)
k r)
fun n -> fn n id
And again, if we have a suitable computation expression for building CPS functions, we can define our recursive function like this:
fun fib n -> cps {
printfn "%i" n
if n <= 1 then return n
else
let! x = fib (n-1)
let! y = fib (n-2)
return x + y
} |> memoC
This is exactly the same as what Brian has done, but I find the syntax here is easier to follow. To make this work, all we need are the following two definitions:
type CpsBuilder() =
member this.Return x k = k x
member this.Bind(m,f) k = m (fun a -> f a k)
let cps = CpsBuilder()
I wrote a test to visualize the memoization. Each dot is a recursive call.
......720 // factorial 6
......720 // factorial 6
.....120 // factorial 5
......720 // memoizedFactorial 6
720 // memoizedFactorial 6
120 // memoizedFactorial 5
......720 // tailRecFact 6
720 // tailRecFact 6
.....120 // tailRecFact 5
......720 // tailRecursiveMemoizedFactorial 6
720 // tailRecursiveMemoizedFactorial 6
.....120 // tailRecursiveMemoizedFactorial 5
kvb's solution returns the same results are straight memoization like this function.
let tailRecursiveMemoizedFactorial =
memoize
(fun x ->
let rec factorialUtil x res =
if x = 0 then
res
else
printf "."
let newRes = x * res
factorialUtil (x - 1) newRes
factorialUtil x 1
)
Test source code.
open System.Collections.Generic
let memoize f =
let cache = new Dictionary<_, _>()
(fun x ->
match cache.TryGetValue(x) with
| true, y -> y
| _ ->
let v = f(x)
cache.Add(x, v)
v)
let rec factorial(x) =
if (x = 0) then
1
else
printf "."
x * factorial(x - 1)
let rec memoizedFactorial =
memoize (
fun x ->
if (x = 0) then
1
else
printf "."
x * memoizedFactorial(x - 1))
let memoY f =
let cache = Dictionary<_,_>()
let rec fn x =
match cache.TryGetValue(x) with
| true,y -> y
| _ -> let v = f fn x
cache.Add(x,v)
v
fn
let tailRecFact =
let factHelper fact (x, res) =
if x = 0 then
res
else
printf "."
fact (x-1, x*res)
let memoized = memoY factHelper
fun x -> memoized (x,1)
let tailRecursiveMemoizedFactorial =
memoize
(fun x ->
let rec factorialUtil x res =
if x = 0 then
res
else
printf "."
let newRes = x * res
factorialUtil (x - 1) newRes
factorialUtil x 1
)
factorial 6 |> printfn "%A"
factorial 6 |> printfn "%A"
factorial 5 |> printfn "%A\n"
memoizedFactorial 6 |> printfn "%A"
memoizedFactorial 6 |> printfn "%A"
memoizedFactorial 5 |> printfn "%A\n"
tailRecFact 6 |> printfn "%A"
tailRecFact 6 |> printfn "%A"
tailRecFact 5 |> printfn "%A\n"
tailRecursiveMemoizedFactorial 6 |> printfn "%A"
tailRecursiveMemoizedFactorial 6 |> printfn "%A"
tailRecursiveMemoizedFactorial 5 |> printfn "%A\n"
System.Console.ReadLine() |> ignore
That should work if mutual tail recursion through y are not creating stack frames:
let rec y f x = f (y f) x
let memoize (d:System.Collections.Generic.Dictionary<_,_>) f n =
if d.ContainsKey n then d.[n]
else d.Add(n, f n);d.[n]
let rec factorialucps factorial' n cont =
if n = 0I then cont(1I) else factorial' (n-1I) (fun k -> cont (n*k))
let factorialdpcps =
let d = System.Collections.Generic.Dictionary<_, _>()
fun n -> y (factorialucps >> fun f n -> memoize d f n ) n id
factorialdpcps 15I //1307674368000

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