This project translates the paper (Symbolic and Automatic Differentiation of Languages - Conal Elliott) from Agda to LeanProver.
The goals of this project are to:
- Discover the differences between Agda and Lean4.
- Define proofs on
Type
instead ofProp
, since each proof represents a different parse of the language. - Avoid tactics if possible, in favour of simple
trfl
(our version ofrfl
).
- The original paper: Symbolic and Automatic Differentiation of Languages - Conal Elliott
- If you are new to derivatives, here is an introduction to Brzozowski's derivatives
- Want to read the Agda code with the ability to "Go to Definition", but you do not want to install Agda. Then download the zip file in this gist: Generated HTML from the original Agda code.
- We streamed the development the foundations of this repo. You can find the recordings of your struggles on this Youtube Playlist.
This project requires setting up lean, see the official documentation.
Lean has Prop
and Type
and Agda has Set
, which we can think of as Type
in Lean. We want out proofs to be proof revelant, since each proof represents a different parse of our language. This means the theorems have to be defined on Type
. For example we have equality redefined in terms of Type
as TEq
(using the syntax ≡
) and we replace rfl
with trfl
, but we do not a replacement tactic for rfl
.
inductive TEq.{tu} {α: Type tu} (a b: α) : Type tu where
| mk : a = b -> TEq a b
def trfl {α : Type u} {a : α} : TEq a a := TEq.mk rfl
We needed to redefine the following types and functions to use Type
instead of Prop
:
Description | Prop | Type |
---|---|---|
equality | = |
≡ in Tipe.lean |
equivalance | Mathlib.Logic.Equiv.Defs.Equiv |
TEquiv or <=> in Function.lean |
decidability | Decidable |
Decidability.Dec in Decidability.lean |
Some things we renamed since they are simply called different things in Agda and Lean, while others were renamed to be closer to the Lean convention.
Description | Original Agda | Translated Lean |
---|---|---|
Set |
Type |
|
universe levels | ℓ , b |
u , v |
parametric types | A , B |
α , β |
isomorphism | ↔ |
<=> |
extensional isomorphism | ⟷ |
∀ {w: List α}, (P w) <=> (Q w) |
We use namespaces as much as possible to make dependencies clear to the reader without requiring "Go to Definition" and Lean to be installed.
Description | Original Agda | Translated Lean |
---|---|---|
List α -> Type u |
◇.Lang |
Language.Lang |
List α -> β |
◇.ν |
Calculus.null |
(List α -> β) -> (a: α) -> (List α -> β) |
◇.δ |
Calculus.derive |
Dec |
Decidability.Dec |
|
Decidable |
Decidability.DecPred |
We dropped most of the syntax, in favour of ([a-z]|[A-Z]|'|_|\.)*
names.
Description | Original Agda | Translated Lean |
---|---|---|
nullable | ν |
null |
derivative of a string | 𝒟 |
derives |
derivative of a character | δ |
derive |
∅ |
emptyset |
|
𝒰 |
universal |
|
empty string | 𝟏 |
emptystr |
character | ` c | char c |
∪ |
or |
|
∩ |
and |
|
scalar | s · P |
scalar s P |
P ⋆ Q |
concat P Q |
|
zero or more | P ☆ |
star P |
decidable bottom | ⊥? |
Decidability.empty |
decidable top | ⊤‽ |
Decidability.unit |
decidable sum | _⊎‽_ |
Decidability.sum |
decidable prod | _×‽_ |
Decidability.prod |
Dec α -> Dec (List α) |
_✶‽ |
Decidability.list |
(β <=> α) -> Dec α -> Dec β |
◃ |
Decidability.apply' |
decidable equality | _≟_ |
Decidability.decEq |
decidable denotation | ⟦_⟧‽ |
decDenote |
denotation | ⟦_⟧ |
denote |
All language operators defined in Language.lagda
are referenced in other modules as ◇.∅
, while in Lean they are references as qualified and non notational names Language.emptyset
. The exception is Calculus.lean
, where Language.lean
is opened, so they are not qualified.
We use explicit parameters and almost no module level parameters, for example Lang
in Agda is defined as Lang α
in Lean. In Agda the A
parameter for Lang
is lifted to the module level, but in this translation we make it explicit.
In Lean definitions need to be in the order they are used. So for example, in Automatic.lean
iso
needs to be defined before concat
, since concat uses iso
, but in Automatic.lagda
, this can be defined in any order.
Also each function signature and its implementatio is grouped together in Lean, while in the Agda implementation the function type signatures are grouped together and the implementations of those functions are much lower down in the file.
Agda seems to be better at using type inference to infer bottom, while Lean typically prefers the use of a tactic.
For example, proving the derivative of the empty string is the empty set, requires proving a few cases of bottom (⊥
in Agda and PEmpty
in Lean). In Agda these proofs are completed with type inference:
δ𝟏 : δ 𝟏 a ⟷ ∅
δ𝟏 = mk↔′ (λ ()) (λ ()) (λ ()) (λ ())
In Lean we need to use the contradiction
tactic or the proof becomes very long.
def derive_emptystr {α: Type u} {a: α} {w: List α}:
(derive emptystr a) w <=> emptyset w := by
apply TEquiv.mk <;> (intro x; cases x) <;> contradiction
For non Lean users: <;>
is similar to the Monad bind operator (>>=
) over proof goals. It takes a list of goals to prove and applies the following tactics to each of the goals, which each produce another list of goals, which are all joined together into one list.
Lean does not have coinduction, which seems to be required for defining Automatic.Lang
. We attempt an inductive defintion:
inductive Lang {α: Type u} : Language.Lang α -> Type (u+1) where
| mk
(null: Decidability.Dec (Calculus.null R))
(derive: (a: α) -> Lang (Calculus.derive R a))
: Lang R
But this results in a lot of termination checking issues, when instantiating operators in Automatic.lean.
For example, when we instantiate emptyset
:
-- ∅ : Lang ◇.∅
def emptyset {α: Type u}: Lang (@Language.emptyset.{u} α) := Lang.mk
-- ν ∅ = ⊥‽
(null := Decidability.empty)
-- δ ∅ a = ∅
(derive := fun _ => emptyset)
We get the following error:
fail to show termination for
Automatic.emptyset
with errors
failed to infer structural recursion:
Not considering parameter α of Automatic.emptyset:
it is unchanged in the recursive calls
no parameters suitable for structural recursion
well-founded recursion cannot be used, 'Automatic.emptyset' does not take any (non-fixed) arguments
This seems to be a fundamental issue in regards to how inductive types work.
We can get around this issue by using unsafe
:
-- ∅ : Lang ◇.∅
unsafe -- failed to infer structural recursion
def emptyset {α: Type u}: Lang (@Language.emptyset.{u} α) := Lang.mk
-- ν ∅ = ⊥‽
(null := Decidability.empty)
-- δ ∅ a = ∅
(derive := fun _ => emptyset)
This issue was probably inevitable, given that the Agda version of Lang in Automatic.lagda required coinduction, which is not a feature of Lean:
record Lang (P : ◇.Lang) : Set (suc ℓ) where
coinductive
field
ν : Dec (◇.ν P)
δ : (a : A) → Lang (◇.δ P a)
Note, the Agda representation also encountered issues with Agda's termination checker, but only when defining the derivative of the concat operator, not all operators as in Lean. Also this was fixable in Agda using a sized version of the record:
record Lang i (P : ◇.Lang) : Set (suc ℓ) where
coinductive
field
ν : Dec (◇.ν P)
δ : ∀ {j : Size< i} → (a : A) → Lang j (◇.δ P a)
We hope to find help to remove the use of unsafe
in Lean or that it is possible to fix using a future coinductive
feature.
Apparently there are libraries in Lean that support coinduction, but none that support indexed coinductive types, which is what we require in this case.
Also note, sized types in Agda are fundamentally flawed, so whether Agda can represent Automatic.Lang without fault, is also an open question.
Thank you to the Conal Elliot for the idea of comparing LeanProver to Agda using the paper Symbolic and Automatic Differentiation of Languages - Conal Elliott. If you are interested in collaborating with Conal Elliott, see this Collaboration page.
Thank you to the Authors and Advisors:
And thank you to everyone on leanprover zulip chat:
- Adam Topaz
- Andrew Carter
- Arthur Adjedj
- Damiano Testa
- David Thrane Christiansen
- Eric Wieser
- Eric Rodriguez
- François G. Dorais
- Kim Morrison
- Kyle Miller
- Mario Carneiro
- Jannis Limperg
- Junyan Xu
- Sebastian Ullrich
- Shreyas Srinivas
- Siegmentation Fault
Where I asked many questions about: