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- Aesop.time x = do let start ← liftM IO.monoNanosNow let a ← x let stop ← liftM IO.monoNanosNow pure (a, { nanos := stop - start })
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- Aesop.time' x = do let start ← liftM IO.monoNanosNow x let stop ← liftM IO.monoNanosNow pure { nanos := stop - start }
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- Aesop.HashSet.filter hs p = Lean.HashSet.fold (fun (hs : Lean.HashSet α) (a : α) => if p a = true then Lean.HashSet.insert hs a else hs) ∅ hs
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- Aesop.PersistentHashSet.toList s = Lean.PersistentHashSet.fold (fun (as : List α) (a : α) => a :: as) [] s
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- Aesop.PersistentHashSet.toArray s = Lean.PersistentHashSet.fold (fun (as : Array α) (a : α) => Array.push as a) (Array.mkEmpty (Lean.PersistentHashSet.size s)) s
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- Aesop.isEmptyTrie x = match x with | Lean.Meta.DiscrTree.Trie.node vs children => Array.isEmpty vs && Array.isEmpty children
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Remove elements for which p
returns false
from the given DiscrTree
.
The removed elements are monadically folded over using f
and init
, so f
is called once for each removed element and the final state of type σ
is
returned.
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Remove elements for which p
returns false
from the given DiscrTree
.
The removed elements are folded over using f
and init
, so f
is called
once for each removed element and the final state of type σ
is returned.
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- Aesop.filterDiscrTree p f init t = Id.run (Aesop.filterDiscrTreeM (fun (a : α) => pure { down := p a }) (fun (s : σ) (a : α) => pure (f s a)) init t)
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- Aesop.SimpTheorems.foldSimpEntriesM.processTheorem f thms s thm = if Lean.PersistentHashSet.contains thms.erased thm.origin = true then pure s else f s (Lean.Meta.SimpEntry.thm thm)
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- Aesop.SimpTheorems.foldSimpEntries f init thms = Id.run (Aesop.SimpTheorems.foldSimpEntriesM f init thms)
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- Aesop.SimpTheorems.simpEntries thms = Aesop.SimpTheorems.foldSimpEntries (fun (s : Array Lean.Meta.SimpEntry) (thm : Lean.Meta.SimpEntry) => Array.push s thm) #[] thms
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If the input expression e
reduces to f x₁ ... xₙ
via repeated whnf
, this
function returns f
and [x₁, ⋯, xₙ]
. Otherwise it returns e
(unchanged, not
in WHNF!) and []
.
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Partition an array of MVarId
s into 'goals' and 'proper mvars'. An MVarId
from the input array ms
is classified as a proper mvar if any of the ms
depend on it, and as a goal otherwise. Additionally, for each goal, we report
the set of mvars that the goal depends on.
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Runs a computation for at most the given number of heartbeats times 1000, ignoring the global heartbeat limit. Note that heartbeats spent on the computation still count towards the global heartbeat count.
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