`simp +ground` error with a cryptic message
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Description
Prerequisites
- Check that your issue is not already filed:
https://github.com/leanprover/lean4/issues - Reduce the issue to a minimal, self-contained, reproducible test case.
Avoid dependencies to Mathlib or Batteries. - Test your test case against the latest nightly release, for example on
https://live.lean-lang.org/#project=lean-nightly
(You can also use the settings there to switch to “Lean nightly”)
Description
In the snippet below, simp +ground fails with "Unknown constant _inhabitedExprDummy".
If I remove +ground, remove the cast to Rat, or even keep the cast to Rat but remove the division by const, there is no error.
import Mathlib.Data.Rat.Cast.Order
structure MyStruct (n : Nat) where
vec : Vector Nat n
const : Nat
theorem th {n : Nat} (s : MyStruct n) (i : Fin n) (h : s.const = 1) :
s.vec[i] = (s.vec[i] : Rat) / s.const := by
simp [h]
example : True := by
let s : MyStruct _ := {
vec := #v[1, 2, 3, 4]
const := 1,
}
have := th s 3 (by decide)
unfold s at this
simp +ground at this -- Error: Unknown constant `_inhabitedExprDummy`
trivial
Sorry for the silly example 😅.
Versions
Lean 4.28.0
Target: x86_64-unknown-linux-gnu
Impact
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Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the minimal example in the issue with Lean 4.28.0, focusing on the simp +ground invocation and the _inhabitedExprDummy error. Trace the relevant simplifier or grounding entry point and add a regression test for this example; done means the test no longer reports the unknown constant.
Written by the indexing model from the issue text.
Assessment
- Domain
- compilers
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Clearly specified
- Newbie friendliness
- 48/100