See file DiscrTree.lean for the actual implementation and documentation.

inductive Lean.Meta.DiscrTree.Key : Type

Discrimination tree key. See DiscrTree

• const: Lake.Name → Nat → Lean.Meta.DiscrTree.Key
• fvar: Lean.FVarId → Nat → Lean.Meta.DiscrTree.Key
• lit: Lean.Literal → Lean.Meta.DiscrTree.Key
• star: Lean.Meta.DiscrTree.Key
• other: Lean.Meta.DiscrTree.Key
• arrow: Lean.Meta.DiscrTree.Key
• proj: Lake.Name → Nat → Nat → Lean.Meta.DiscrTree.Key

instance Lean.Meta.DiscrTree.instInhabitedKey : Inhabited Lean.Meta.DiscrTree.Key

Equations

• Lean.Meta.DiscrTree.instInhabitedKey = { default := Lean.Meta.DiscrTree.Key.const default default }

instance Lean.Meta.DiscrTree.instBEqKey : BEq Lean.Meta.DiscrTree.Key

Equations

• Lean.Meta.DiscrTree.instBEqKey = { beq := Lean.Meta.DiscrTree.beqKey✝ }

instance Lean.Meta.DiscrTree.instReprKey : Repr Lean.Meta.DiscrTree.Key

Equations

• Lean.Meta.DiscrTree.instReprKey = { reprPrec := Lean.Meta.DiscrTree.reprKey✝ }

def Lean.Meta.DiscrTree.Key.hash : Lean.Meta.DiscrTree.Key → UInt64

Equations

• (Lean.Meta.DiscrTree.Key.const a a_1).hash = mixHash 5237 (mixHash (hash a) (hash a_1))
• (Lean.Meta.DiscrTree.Key.fvar a a_1).hash = mixHash 3541 (mixHash (hash a) (hash a_1))
• (Lean.Meta.DiscrTree.Key.lit a).hash = mixHash 1879 (hash a)
• Lean.Meta.DiscrTree.Key.star.hash = 7883
• Lean.Meta.DiscrTree.Key.other.hash = 2411
• Lean.Meta.DiscrTree.Key.arrow.hash = 17
• (Lean.Meta.DiscrTree.Key.proj a a_1 a_2).hash = mixHash (hash a_2) (mixHash (hash a) (hash a_1))

instance Lean.Meta.DiscrTree.instHashableKey : Hashable Lean.Meta.DiscrTree.Key

Equations

• Lean.Meta.DiscrTree.instHashableKey = { hash := Lean.Meta.DiscrTree.Key.hash }

instance Lean.Meta.DiscrTree.instToExprKey : Lean.ToExpr Lean.Meta.DiscrTree.Key

Equations

• One or more equations did not get rendered due to their size.

inductive Lean.Meta.DiscrTree.Trie (α : Type) : Type

Discrimination tree trie. See DiscrTree.

• node: {α : Type} → Array α → Array (Lean.Meta.DiscrTree.Key × Lean.Meta.DiscrTree.Trie α) → Lean.Meta.DiscrTree.Trie α

Notes regarding term reduction at the DiscrTree module.

• In simp, we want to have simp theorem such as

@[simp] theorem liftOn_mk (a : α) (f : α → γ) (h : ∀ a₁ a₂, r a₁ a₂ → f a₁ = f a₂) :
    Quot.liftOn (Quot.mk r a) f h = f a := rfl

If we enable iota, then the lhs is reduced to f a. Note that when retrieving terms, we may also disable beta and zeta reduction. See issue https://github.com/leanprover/lean4/issues/2669

• During type class resolution, we often want to reduce types using even iota and projection reduction. Example:

inductive Ty where
  | int
  | bool

@[reducible] def Ty.interp (ty : Ty) : Type :=
  Ty.casesOn (motive := fun _ => Type) ty Int Bool

def test {a b c : Ty} (f : a.interp → b.interp → c.interp) (x : a.interp) (y : b.interp) : c.interp :=
  f x y

def f (a b : Ty.bool.interp) : Ty.bool.interp :=
  -- We want to synthesize `BEq Ty.bool.interp` here, and it will fail
  -- if we do not reduce `Ty.bool.interp` to `Bool`.
  test (.==.) a b

structure Lean.Meta.DiscrTree (α : Type) : Type

Discrimination trees. It is an index from terms to values of type α.

• root : Lean.PersistentHashMap Lean.Meta.DiscrTree.Key (Lean.Meta.DiscrTree.Trie α)