We define discrimination trees for the purpose of unifying local expressions with library results.
This structure is based on Lean.Meta.DiscrTree
.
I document here what features are not in the original:
The keys
Key.lam
,Key.forall
andKey.bvar
have been introduced in order to allow for matching under lambda and forall binders.Key.lam
has arity 1 and indexes the body.Key.forall
has arity 2 and indexes the domain and the body. The reason for not indexing the domain of a lambda expression is that it is usually already determined, for example in∃ a : α, p
, which is@Exists α fun a : α => p
, we don't want to index the domainα
twice. In a forall expression it is necessary to index the domain, because in an implicationp → q
we need to index bothp
andq
.Key.bvar
works the same asKey.fvar
, but stores the De Bruijn index to identify it.For example, this allows for more specific matching with the left hand side of
∑ i ∈ range n, i = n * (n - 1) / 2
, which is indexed by[⟨Finset.sum, 5⟩, ⟨Nat, 0⟩, ⟨Nat, 0⟩, *0, ⟨Finset.Range, 1⟩, *1, λ, ⟨#0, 0⟩]
.The key
Key.star
takes aNat
identifier as an argument. For example, the library pattern?a + ?a
is encoded as[⟨HAdd.hAdd, 6⟩, *0, *0, *0, *1, *2, *2]
.*0
corresponds to the type ofa
,*1
to theHAdd
instance, and*2
toa
. This means that it will only match an expressionx + y
ifx
is definitionally equal toy
. The matching algorithm requires that the same stars from the discrimination tree match with the same patterns in the lookup expression, and similarly requires that the same metavariables form the lookup expression match with the same pattern in the discrimination tree.The key
Key.opaque
has been introduced in order to index existential variables in lemmas likeNat.exists_prime_and_dvd {n : ℕ} (hn : n ≠ 1) : ∃ p, Prime p ∧ p ∣ n
, where the partPrime p
gets the pattern[⟨Nat.Prime, 1⟩, ◾]
. (◾ representsKey.opaque
) When matching,Key.opaque
can only be matched byKey.star
.Using the
WhnfCoreConfig
argument, it is possible to disable β-reduction and ζ-reduction. As a result, we may get a lambda expression applied to an argument or a let-expression. Since there is no support for indexing these, they will be indexed byKey.opaque
.We keep track of the matching score of a unification. This score represents the number of keys that had to be the same for the unification to succeed. For example, matching
(1 + 2) + 3
withadd_comm
gives a score of 2, since the pattern of commutativity is [⟨HAdd.hAdd, 6⟩, *0, *0, *0, *1, *2, *3], so matching⟨HAdd.hAdd, 6⟩
gives 1 point, and matching*0
after its first appearence gives another point, but the third argument is an outParam, so this gets ignored. Similarly, matching it withadd_assoc
gives a score of 5.Patterns that have the potential to be η-reduced are put into the
RefinedDiscrTree
under all possible reduced key sequences. This is for terms of the formfun x => f (?m x₁ .. xₙ)
, where?m
is a metavariable, and one ofx₁, .., xₙ
inx
. For example, the patternContinuous fun y => Real.exp (f y)])
is indexed by both[⟨Continuous, 5⟩, *0, ⟨Real, 0⟩, *1, *2, λ, ⟨Real.exp⟩, *3]
and[⟨Continuous, 5⟩, *0, ⟨Real, 0⟩, *1, *2, ⟨Real.exp⟩]
so that it also comes up if you search withContinuous Real.exp
. Similarly,Continuous fun x => f x + g x
is indexed by both[⟨Continuous, 1⟩, λ, ⟨HAdd.hAdd, 6⟩, *0, *0, *0, *1, *2, *3]
and[⟨Continuous, 1⟩, ⟨HAdd.hAdd, 5⟩, *0, *0, *0, *1, *2]
.For sub-expressions not at the root of the original expression we have some additional reductions:
- Any combination of
ofNat
,Nat.zero
,Nat.succ
and number literals is stored as just a number literal. - The expression
fun a : α => a
is stored as@id α
.- This makes lemmata such as
continuous_id'
redundant, which is the same ascontinuous_id
, withid
replaced byfun x => x
.
- This makes lemmata such as
- Any expressions involving
+
,*
,-
,/
or⁻¹
is normalized to not have a lambda in front and to always have the default amount of arguments. e.g.(f + g) a
is stored asf a + g a
andfun x => f x + g x
is stored asf + g
.- This makes lemmata such as
MeasureTheory.integral_integral_add'
redundant, which is the same asMeasureTheory.integral_integral_add
, withf a + g a
replaced by(f + g) a
- it also means that a lemma like
Continuous.mul
can be stated as talking aboutf * g
instead offun x => f x + g x
.
- This makes lemmata such as
- Any combination of
I have also made some changes in the implementation:
- Instead of directly converting from
Expr
toArray Key
during insertion, and directly looking up from anExpr
during lookup, I defined the intermediate structureDTExpr
, which is a form ofExpr
that only contains information relevant for the discrimination tree. EachExpr
is transformed into aDTExpr
before insertion or lookup. For insertion there could be multipleDTExpr
representations due to potential η-reductions as mentioned above.
TODO:
More thought could be put into the matching algorithm for non-trivial unifications. For example, when looking up the expression
?a + ?a
(for rewriting), there will only be results liken + n = 2 * n
ora + b = b + a
, but not liken + 1 = n.succ
, even though this would still unify.The reason why implicit arguments are not ignored by the discrimination tree is that they provide important type information. Because of this it seems more natural to index the types of expressions instead of indexing the implicit type arguments. Then each key would additionally index the type of that expression. So instead of indexing
?a + ?b
as[⟨HAdd.hAdd, 6⟩, *0, *0, *0, *1, *2, *3]
, it would be indexed by something like[(*0, ⟨HAdd.hAdd, 6⟩), _, _, _, _, (*0, *1), (*0, *2)]
. The advantage of this would be that there will be less duplicate indexing of types, because many functions index the types of their arguments and their return type with implicit arguments, meaning that types unnecessarily get indexed multiple times. This modification can be explored, but it could very well not be an improvement.
Definitions #
Discrimination tree key.
- star: ℕ → Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A metavariable. This key matches with anything. It stores an index.
- opaque: Mathlib.Meta.FunProp.RefinedDiscrTree.Key
An opaque variable. This key only matches with itself or
Key.star
. - const: Lean.Name → ℕ → Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A constant. It stores the name and the arity.
- fvar: Lean.FVarId → ℕ → Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A free variable. It stores the
FVarId
and the arity. - bvar: ℕ → ℕ → Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A bound variable, from a lambda or forall binder. It stores the De Bruijn index and the arity.
- lit: Lean.Literal → Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A literal.
- sort: Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A sort. Universe levels are ignored.
- lam: Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A lambda function.
- forall: Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A dependent arrow.
- proj: Lean.Name → ℕ → ℕ → Mathlib.Meta.FunProp.RefinedDiscrTree.Key
A projection. It stores the structure name, the projection index and the arity.
Instances For
Constructor index used for ordering Key
.
Note that the index of the star pattern is 0, so that when looking up in a Trie
,
we can look at the start of the sorted array for all .star
patterns.
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Return the number of arguments that the Key
takes.
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Discrimination tree trie. See RefinedDiscrTree
.
- node: {α : Type} → Array (Mathlib.Meta.FunProp.RefinedDiscrTree.Key × Mathlib.Meta.FunProp.RefinedDiscrTree.Trie α) → Mathlib.Meta.FunProp.RefinedDiscrTree.Trie α
- path: {α : Type} →
Array Mathlib.Meta.FunProp.RefinedDiscrTree.Key →
Mathlib.Meta.FunProp.RefinedDiscrTree.Trie α → Mathlib.Meta.FunProp.RefinedDiscrTree.Trie α
Sequence of nodes with only one child.
keys
is anArray
of size at least 1. - values: {α : Type} → Array α → Mathlib.Meta.FunProp.RefinedDiscrTree.Trie α
Instances For
Equations
- Mathlib.Meta.FunProp.RefinedDiscrTree.instInhabitedTrie = { default := Mathlib.Meta.FunProp.RefinedDiscrTree.Trie.node #[] }
Trie.path
constructor that only inserts the path if it is non-empty.
Equations
- Mathlib.Meta.FunProp.RefinedDiscrTree.Trie.mkPath keys child = if keys.isEmpty = true then child else Mathlib.Meta.FunProp.RefinedDiscrTree.Trie.path keys child
Instances For
Trie
constructor for a single value, taking the keys starting at index i
.
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Trie.node
constructor for combining two Key
, Trie α
pairs.
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Return the values from a Trie α
, assuming that it is a leaf
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Return the children of a Trie α
, assuming that it is not a leaf.
The result is sorted by the Key
's
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Equations
- Mathlib.Meta.FunProp.RefinedDiscrTree.instToFormatTrie = { format := Mathlib.Meta.FunProp.RefinedDiscrTree.Trie.format }
Discrimination tree. It is an index from expressions to values of type α
.
- root : Lean.PersistentHashMap Mathlib.Meta.FunProp.RefinedDiscrTree.Key (Mathlib.Meta.FunProp.RefinedDiscrTree.Trie α)
The underlying
PersistentHashMap
of aRefinedDiscrTree
.
Instances For
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Equations
- Mathlib.Meta.FunProp.RefinedDiscrTree.instToFormat = { format := Mathlib.Meta.FunProp.RefinedDiscrTree.format }
DTExpr
is a simplified form of Expr
.
It is the intermediate step for converting from Expr
to Array Key
.
- star: Option Lean.MVarId → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A metavariable. It optionally stores an
MVarId
. - opaque: Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
An opaque variable or a let-expression in the case
WhnfCoreConfig.zeta := false
. - const: Lean.Name → Array Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A constant. It stores the name and the arguments.
- fvar: Lean.FVarId → Array Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A free variable. It stores the
FVarId
and the argumenst - bvar: ℕ → Array Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A bound variable. It stores the De Bruijn index and the arguments
- lit: Lean.Literal → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A literal.
- sort: Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A sort.
- lam: Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A lambda function. It stores the body.
- forall: Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr →
Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A dependent arrow. It stores the domain and body.
- proj: Lean.Name →
ℕ →
Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr →
Array Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr → Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr
A projection. It stores the structure name, projection index, struct body and arguments.
Instances For
Return the size of the DTExpr
. This is used for calculating the matching score when two
expressions are equal.
The score is not incremented at a lambda, which is so that the expressions
∀ x, p[x]
and ∃ x, p[x]
get the same size.
Encoding an Expr #
Given a DTExpr
, return the linearized encoding in terms of Key
,
which is used for RefinedDiscrTree
indexing.
Equations
- e.flatten initCapacity = StateT.run' (Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr.flattenAux (Array.mkEmpty initCapacity) e) { stars := #[] }
Instances For
Reduction procedure for the RefinedDiscrTree
indexing.
Repeatedly apply reduce while stripping lambda binders and introducing their variables
Check whether the expression is represented by Key.star
and has arg
as an argument.
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- Mathlib.Meta.FunProp.RefinedDiscrTree.isStarWithArg arg x = false
Instances For
Return true
if e
contains a loose bound variable.
Equations
- e.hasLooseBVars = Mathlib.Meta.FunProp.RefinedDiscrTree.DTExpr.hasLooseBVarsAux 0 e
Instances For
Return for each argument whether it should be ignored.
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Return whether the argument should be ignored.
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Introduce new lambdas by η-expansion.
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Normalize an application of a heterogenous binary operator like HAdd.hAdd
, using:
f = fun x => f x
to increase the arity to 6(f + g) a = f a + g a
to decrease the arity to 6(fun x => f x + g x) = f + g
to get rid of any lambdas in front
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use that (fun x => f x + g x) = f + g
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- Mathlib.Meta.FunProp.RefinedDiscrTree.MkDTExpr.reduceHBinOpAux.distributeLambdas [] type lhs rhs = pure (type, lhs, rhs, [])
Instances For
Normalize an application if the head is +
, *
, -
or /
.
Optionally return the (type, lhs, rhs, lambdas)
.
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Normalize an application of a unary operator like Inv.inv
, using:
f⁻¹ a = (f a)⁻¹
to decrease the arity to 3(fun x => (f a)⁻¹) = f⁻¹
to get rid of any lambdas in front
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use that (fun x => (f x)⁻¹) = f⁻¹
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- Mathlib.Meta.FunProp.RefinedDiscrTree.MkDTExpr.reduceUnOpAux.distributeLambdas [] type arg = pure (type, arg, [])
Instances For
Normalize an application if the head is ⁻¹
or -
.
Optionally return the (type, arg, lambdas)
.
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Return the encoding of e
as a DTExpr
.
If root = false
, then e
is a strict sub expression of the original expression.
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Return all pairs of body, bound variables that could possibly appear due to η-reduction
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- Mathlib.Meta.FunProp.RefinedDiscrTree.MkDTExpr.etaPossibilities e lambdas k = HOrElse.hOrElse (k e lambdas) fun (x : Unit) => failure
Instances For
run etaPossibilities
, and cache the result if there are multiple possibilities.
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Return all encodings of e
as a DTExpr
, taking possible η-reductions into account.
If root = false
, then e
is a strict sub expression of the original expression.
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Return the encoding of e
as a DTExpr
.
Warning: to account for potential η-reductions of e
, use mkDTExprs
instead.
The argument fvarInContext
allows you to specify which free variables in e
will still be
in the context when the RefinedDiscrTree
is being used for lookup.
It should return true only if the RefinedDiscrTree
is built and used locally.
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Similar to mkDTExpr
.
Return all encodings of e
as a DTExpr
, taking potential further η-reductions into account.
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Instances For
Inserting intro a RefinedDiscrTree #
Insert the value v
at index keys : Array Key
in a RefinedDiscrTree
.
Warning: to accound for η-reduction, an entry may need to be added at multiple indexes,
so it is recommended to use RefinedDiscrTree.insert
for insertion.
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Insert the value v
at index e : DTExpr
in a RefinedDiscrTree
.
Warning: to accound for η-reduction, an entry may need to be added at multiple indexes,
so it is recommended to use RefinedDiscrTree.insert
for insertion.
Equations
- d.insertDTExpr e v = d.insertInRefinedDiscrTree e.flatten v
Instances For
Insert the value v
at index e : Expr
in a RefinedDiscrTree
.
The argument fvarInContext
allows you to specify which free variables in e
will still be
in the context when the RefinedDiscrTree
is being used for lookup.
It should return true only if the RefinedDiscrTree
is built and used locally.
if onlySpecific := true
, then we filter out the patterns *
and Eq * * *
.
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Insert the value vLhs
at index lhs
, and if rhs
is indexed differently, then also
insert the value vRhs
at index rhs
.
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Matching with a RefinedDiscrTree #
We use a very simple unification algorithm. For all star/metavariable patterns in the
RefinedDiscrTree
and in the target, we store the assignment, and when it is assigned again,
we check that it is the same assignment.
If k
is a key in children
, return the corresponding Trie α
. Otherwise return none
.
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Return the possible Trie α
that match with n
metavariable.
Return the possible Trie α
that match with anything.
We add 1 to the matching score when the key is .opaque
,
since this pattern is "harder" to match with.
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Return the possible Trie α
that come from a Key.star
,
while keeping track of the Key.star
assignments.
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Return the possible Trie α
that match with e
.
If e
is not a metavariable, return the possible Trie α
that exactly match with e
.
Return the results from the RefinedDiscrTree
that match the given expression,
together with their matching scores, in decreasing order of score.
Each entry of type Array α × Nat
corresponds to one pattern.
If unify := false
, then metavariables in e
are treated as opaque variables.
This is for when you don't want to instantiate metavariables in e
.
If allowRootStar := false
, then we don't allow e
or the matched key in d
to be a star pattern.
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Similar to getMatchWithScore
, but also returns matches with prefixes of e
.
We store the score, followed by the number of ignored arguments.
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go
Apply a monadic function to the array of values at each node in a RefinedDiscrTree
.
Apply a monadic function to the array of values at each node in a RefinedDiscrTree
.
Equations
- d.mapArraysM f = do let __do_lift ← d.root.mapM fun (x : Mathlib.Meta.FunProp.RefinedDiscrTree.Trie α) => x.mapArraysM f pure { root := __do_lift }
Instances For
Apply a function to the array of values at each node in a RefinedDiscrTree
.
Equations
- d.mapArrays f = d.mapArraysM f