This PR allows `simp` to recognize and warn about simp lemmas that are
likely looping in the current simp set. It does so automatically
whenever simplification fails with the dreaded “max recursion depth”
error fails, but it can be made to do it always with `set_option
linter.loopingSimpArgs true`. This check is not on by default because it
is somewhat costly, and can warn about simp calls that still happen to
work.
This closes#5111. In the end, this implemented much simpler logic than
described there (and tried in the abandoned #8688; see that PR
description for more background information), but it didn’t work as well
as I thought. The current logic is:
“Simplify the RHS of the simp theorem, complain if that fails”.
It is a reasonable policy for a Lean project to say that all simp
invocation should be so that this linter does not complain. Often it is
just a matter of explicitly disabling some simp theorems from the
default simp set, to make it clear and robust that in this call, we do
not want them to trigger. But given that often such simp call happen to
work, it’s too pedantic to impose it on everyone.
This PR ensures that the configuration in `Simp.Config` is used when
reducing terms and checking definitional equality in `simp`.
closes#5455
---------
Co-authored-by: Kim Morrison <kim@tqft.net>
This PR removes unnecessary parameters from the funcion induction
principles. This is a breaking change; broken code can typically be adjusted
simply by passing fewer parameters.
Part 2, adjusting after stage0 update.
Closes#6320
This PR adds the Lean.RArray data structure.
This data structure is equivalent to `Fin n → α` or `Array α`, but
optimized for a fast kernel-reduction `get` operation.
It is not suitable as a general-purpose data structure. The primary
intended use case is the “denote” function of a typical proof by
reflection proof, where only the `get` operation is necessary, and where
using `List.get` unnecessarily slows down proofs with more than a
hand-full of atomic expressions.
There is no well-formedness invariant attached to this data structure,
to keep it concise; it's semantics is given through `RArray.get`. In
that way one can also view an `RArray` as a decision tree implementing
`Nat → α`.
In #6068 this data structure is used in `simp_arith`.
