The bound
attribute #
Any lemma tagged with @[bound]
is registered as an apply rule for the bound
tactic, by
converting it to either norm apply
or safe apply <priority>
. The classification is based
on the number and types of the lemma's hypotheses.
Check if an expression is zero
Equations
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Map the arguments of an inequality expression to a score
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Map a hypothesis type to a score
Map a type to a score
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Score the type of argument x
Equations
- Mathlib.Tactic.Bound.typePriority.argPriority x = do let __do_lift ← Lean.Meta.inferType x Mathlib.Tactic.Bound.hypPriority __do_lift
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Insist that our conclusion is an inequality
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Map a theorem decl to a score (0 means norm apply
, 0 <
means safe apply
)
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Map a score to either norm apply
or safe apply <priority>
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Attribute for forward
rules for the bound
tactic.
@[bound_forward]
lemmas should produce inequalities given other hypotheses that might be in the
context. A typical example is exposing an inequality field of a structure, such as
HasPowerSeriesOnBall.r_pos
.
Equations
- Mathlib.Tactic.Bound.attrBound_forward = Lean.ParserDescr.node `Mathlib.Tactic.Bound.attrBound_forward 1024 (Lean.ParserDescr.nonReservedSymbol "bound_forward" false)