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docs/attributes.md

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# Attributes
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Mathlib version: `de7ac7cb70710498104300af3c811b05efbb48c6`
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## Std.Internal.tree_tac
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simp theorems used by internal DTreeMap lemmas
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| _ => false
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```
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## measurability
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The `measurability` attribute used to tag measurability statements for the `measurability` tactic.
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## method_specs
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generate method specification theorems
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docs/commands.md

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# Commands
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## \#adaptation_note
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Defined in: `adaptationNoteCmd`

docs/options.md

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# Options
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Mathlib version: `de7ac7cb70710498104300af3c811b05efbb48c6`
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## Elab.async
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type: `Bool`

docs/tactics.md

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# Tactics
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## \#adaptation_note
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Defined in: `«tactic#adaptation_note_»`
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Backwards compatibility shim for `generalize`.
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## generalize_proofs
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Defined in: `Mathlib.Tactic.generalizeProofsElab`
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Defined in: `Batteries.Tactic.generalizeProofsElab`
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`generalize_proofs ids* [at locs]?` generalizes proofs in the current goal,
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turning them into new local hypotheses.
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`StronglyMeasurable f`, `AEStronglyMeasurable f μ`, or `MeasurableSet s` by applying lemmas tagged
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with the `measurability` user attribute.
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`fun_prop` is a (usually more powerful) alternative to `measurability`
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if your goal does not involve `MeasurableSet`.
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Note that `measurability` uses `fun_prop` for solving measurability of functions, so statements
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about `Measurable`, `AEMeasurable`, `StronglyMeasurable` and `AEStronglyMeasurable` should be tagged
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with `fun_prop` rather that `measurability`. The `measurability` attribute is equivalent to
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`fun_prop` in these cases for backward compatibility with the earlier implementation.
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## measurability!
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Defined in: `measurability!`

lake-manifest.json

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"type": "git",
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"subDir": null,
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"scope": "",
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"rev": "de7ac7cb70710498104300af3c811b05efbb48c6",
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"name": "mathlib",
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"manifestFile": "lake-manifest.json",
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"inputRev": "master",
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"type": "git",
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"scope": "leanprover-community",
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"rev": "e0442e0a213dfceca01d4c9beac9822be4b04a0a",
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"rev": "754186a55901dcfdfd4a15f0e4217d8dce65ac37",
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"name": "batteries",
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"manifestFile": "lake-manifest.json",
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"inputRev": "main",

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