openAI-math-dataset / lean /OAI /Combinatorics /LowSpaceSubsetSum /Counting /CountedRepresentationEmit.lean
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Add lean source and binary files (part 46)
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import OAI.Combinatorics.LowSpaceSubsetSum.Counting.CountedMaskChecks
namespace OAI
/-! # Executed validity, weight and mask construction for parent reports -/
namespace LowSpaceSubsetSum.CountedRepresentationEmit
variable {n : ℕ}
abbrev ParentRecord (n : ℕ) := (LeafRecord n × LeafRecord n) × (LeafRecord n × LeafRecord n)
def filterMask (selected : List (Fin n)) : List (Fin n) → List (Fin n) × ℕ
| [] => ([], 1)
| i :: xs =>
let hit := CountedWeights.member i selected
let rest := filterMask selected xs
(if hit.1 then i :: rest.1 else rest.1, hit.2 + rest.2 + 3)
theorem filterMask_value (selected xs : List (Fin n)) :
(filterMask selected xs).1 = xs.filter (fun i => decide (i ∈ selected)) := by
induction xs with
| nil => rfl
| cons i xs ih =>
simp only [filterMask, CountedWeights.member_value, ih, List.filter_cons]
theorem filterMask_length (selected xs : List (Fin n)) :
(filterMask selected xs).1.length ≤ xs.length := by
rw [filterMask_value]
exact List.length_filter_le _ _
theorem filterMask_work (selected xs : List (Fin n)) :
(filterMask selected xs).2 ≤ (selected.length + 4) * xs.length + 1 := by
induction xs with
| nil => simp [filterMask]
| cons i xs ih =>
have h := CountedWeights.member_work i selected
simp only [filterMask, List.length_cons, Nat.mul_add, Nat.mul_one]
omega
def topIndices (x : ParentRecord n) : List (Fin n) :=
x.1.1.top.indices ++ x.1.2.top.indices ++ x.2.1.top.indices ++ x.2.2.top.indices
theorem topIndices_length (x : ParentRecord n) : (topIndices x).length ≤ 4 * n := by
have h₁ := x.1.1.top.length_le
have h₂ := x.1.2.top.length_le
have h₃ := x.2.1.top.length_le
have h₄ := x.2.2.top.length_le
simp only [topIndices, List.length_append]
omega
def topMask (x : ParentRecord n) : IndexedMask n × ℕ :=
let out := filterMask (topIndices x) (List.finRange n)
(⟨out.1, by simpa only [List.length_finRange] using filterMask_length (topIndices x) (List.finRange n)⟩,
out.2 + 12 * n + 4)
theorem topMask_value (x : ParentRecord n) :
(topMask x).1.semantic = RepresentationUniverse.topMask
(RepresentationKeys.pairSemantic x.1, RepresentationKeys.pairSemantic x.2) := by
ext i
simp [topMask, IndexedMask.semantic, filterMask_value, topIndices,
RepresentationUniverse.topMask, RepresentationKeys.pairSemantic, LeafRecord.semantic]
theorem topMask_work (x : ParentRecord n) :
(topMask x).2 ≤ 8 * (n + 1) ^ 2 := by
have h := filterMask_work (topIndices x) (List.finRange n)
have hl := topIndices_length x
simp only [List.length_finRange] at h
have hm := Nat.mul_le_mul_right n (Nat.add_le_add_right hl 4)
change (filterMask (topIndices x) (List.finRange n)).2 + 12 * n + 4 ≤ _
nlinarith only [h, hm, Nat.zero_le n]
def parentWeight (I : Instance n) (F : IndexedMask n) (x : ParentRecord n) : ℤ × ℕ :=
let a := RepresentationKeys.leafWeight I F x.1.1
let b := RepresentationKeys.leafWeight I F x.1.2
let c := RepresentationKeys.leafWeight I F x.2.1
let d := RepresentationKeys.leafWeight I F x.2.2
((a.1 + b.1) + (c.1 + d.1), a.2 + b.2 + c.2 + d.2 + 3)
theorem parentWeight_value (I : Instance n) (F : IndexedMask n) (x : ParentRecord n) :
(parentWeight I F x).1 = RepresentationUniverse.parentWeight
(flip (fun i => (I.values i : ℤ)) F.semantic)
(RepresentationKeys.pairSemantic x.1, RepresentationKeys.pairSemantic x.2) := by
simp only [parentWeight, RepresentationKeys.leafWeight_value,
RepresentationUniverse.parentWeight, RepresentationUniverse.childWeight,
RepresentationKeys.pairSemantic]
theorem parentWeight_work (I : Instance n) (F : IndexedMask n) (x : ParentRecord n) :
(parentWeight I F x).2 ≤ 128 * (n + 1) ^ 2 + 3 := by
have ha := RepresentationKeys.leafWeight_work I F x.1.1
have hb := RepresentationKeys.leafWeight_work I F x.1.2
have hc := RepresentationKeys.leafWeight_work I F x.2.1
have hd := RepresentationKeys.leafWeight_work I F x.2.2
change _ + _ + _ + _ + 3 ≤ _
omega
def emit (I : Instance n) (F : IndexedMask n) (x y : LeafRecord n × LeafRecord n) :
Option (StoredEntry n) × ℕ :=
let checked := CountedMaskChecks.valid (x, y)
if checked.1 then
let w := parentWeight I F (x, y)
let m := topMask (x, y)
(some ⟨w.1, m.1⟩, checked.2 + w.2 + m.2 + 6)
else (none, checked.2 + 3)
theorem emit_value (D : RepresentationParentData n) (F : IndexedMask n)
(hF : F.semantic = D.signs) (x y : LeafRecord n × LeafRecord n) :
(emit D.input F x y).1.map StoredEntry.semantic =
D.emit (RepresentationKeys.pairSemantic x) (RepresentationKeys.pairSemantic y) := by
simp only [emit, CountedMaskChecks.valid_value, decide_eq_true_eq,
RepresentationParentData.emit]
split
· simp only [Option.map_some, StoredEntry.semantic, parentWeight_value, topMask_value, hF,
RepresentationUniverse.entry, RepresentationParentData.weights]
· rfl
theorem emit_work (I : Instance n) (F : IndexedMask n) (x y : LeafRecord n × LeafRecord n) :
(emit I F x y).2 ≤ 500 * (n + 1) ^ 2 := by
have hv := CountedMaskChecks.valid_work (x, y)
have hw := parentWeight_work I F (x, y)
have hm := topMask_work (x, y)
simp only [emit]
split <;> dsimp only <;> nlinarith only [hv, hw, hm, Nat.zero_le n]
theorem emit_scale (I : Instance n) (F : IndexedMask n) (x y : LeafRecord n × LeafRecord n)
(hn : 10000 ≤ n) : (emit I F x y).2 ≤ inputScale I ^ 3 := by
have h := emit_work I F x y
have hnu : n + 1 ≤ inputScale I := by unfold inputScale; omega
have hu : 500 ≤ inputScale I := by omega
calc
_ ≤ 500 * (n + 1) ^ 2 := h
_ ≤ 500 * inputScale I ^ 2 := Nat.mul_le_mul_left _ (Nat.pow_le_pow_left hnu _)
_ ≤ inputScale I * inputScale I ^ 2 := Nat.mul_le_mul_right _ hu
_ = _ := (pow_succ' _ _).symm
end LowSpaceSubsetSum.CountedRepresentationEmit
end OAI