lean4-htt/script/AnalyzeGrindAnnotations.lean
Kim Morrison 21f5263f2f
feat: minor quality of life improvements in script/AnalyzeGrindAnnotations (#10021)
This PR make some minor changes to the grind annotation analysis script,
including sorting results and handling errors. Still need to add an
external UI.
2025-08-21 04:12:21 +00:00

101 lines
3.6 KiB
Text

/-
Copyright (c) 2025 Amazon.com, Inc. or its affiliates. All Rights Reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura
-/
import Lean
namespace Lean.Meta.Grind.Analyzer
/-!
A simple E-matching annotation analyzer.
For each theorem annotated as an E-matching candidate, it creates an artificial goal, executes `grind` and shows the
number of instances created.
For a theorem of the form `params -> type`, the artificial goal is of the form `params -> type -> False`.
-/
/--
`grind` configuration for the analyzer. We disable case-splits and lookahead,
increase the number of generations, and limit the number of instances generated.
-/
def config : Grind.Config := {
splits := 0
lookahead := false
mbtc := false
ematch := 20
instances := 100
gen := 10
}
structure Config where
/-- Minimum number of instantiations to trigger summary report -/
min : Nat := 10
/-- Minimum number of instantiations to trigger detailed report -/
detailed : Nat := 50
def mkParams : MetaM Params := do
let params ← Grind.mkParams config
let ematch ← getEMatchTheorems
let casesTypes ← Grind.getCasesTypes
return { params with ematch, casesTypes }
/-- Returns the total number of generated instances. -/
private def sum (cs : PHashMap Origin Nat) : Nat := Id.run do
let mut r := 0
for (_, c) in cs do
r := r + c
return r
private def thmsToMessageData (thms : PHashMap Origin Nat) : MetaM MessageData := do
let data := thms.toArray.filterMap fun (origin, c) =>
match origin with
| .decl declName => some (declName, c)
| _ => none
let data := data.qsort fun (d₁, c₁) (d₂, c₂) => if c₁ == c₂ then Name.lt d₁ d₂ else c₁ > c₂
let data ← data.mapM fun (declName, counter) =>
return .trace { cls := `thm } m!"{.ofConst (← mkConstWithLevelParams declName)} ↦ {counter}" #[]
return .trace { cls := `thm } "instances" data
/--
Analyzes theorem `declName`. That is, creates the artificial goal based on `declName` type,
and invokes `grind` on it.
-/
def analyzeEMatchTheorem (declName : Name) (c : Config) : MetaM Unit := do
let info ← getConstInfo declName
let mvarId ← forallTelescope info.type fun _ type => do
withLocalDeclD `h type fun _ => do
return (← mkFreshExprMVar (mkConst ``False)).mvarId!
let result ← Grind.main mvarId (← mkParams) (pure ())
let thms := result.counters.thm
let s := sum thms
if s > c.min then
IO.println s!"{declName} : {s}"
if s > c.detailed then
logInfo m!"{declName}\n{← thmsToMessageData thms}"
-- Not sure why this is failing: `down_pure` perhaps has an unnecessary universe parameter?
run_meta analyzeEMatchTheorem ``Std.Do.SPred.down_pure {}
/-- Analyzes all theorems in the standard library marked as E-matching theorems. -/
def analyzeEMatchTheorems (c : Config := {}) : MetaM Unit := do
let origins := (← getEMatchTheorems).getOrigins
let decls := origins.filterMap fun | .decl declName => some declName | _ => none
for declName in decls.mergeSort Name.lt do
try
analyzeEMatchTheorem declName c
catch e =>
logError m!"{declName} failed with {e.toMessageData}"
logInfo m!"Finished analyzing {decls.length} theorems"
/-- Macro for analyzing E-match theorems with unlimited heartbeats -/
macro "#analyzeEMatchTheorems" : command => `(
set_option maxHeartbeats 0 in
run_meta analyzeEMatchTheorems
)
#analyzeEMatchTheorems
-- -- We can analyze specific theorems using commands such as
set_option trace.grind.ematch.instance true in
run_meta analyzeEMatchTheorem ``List.filterMap_some {}