new solver: write canonicalization chapter (rust-lang#1595)

* write canonicalization chapter first half

* w

* review

* very good section

* whatever

* review

* ok

Author: lcnr

Diff for: src/solve/canonicalization.md

@@ -1,10 +1,84 @@
 # Canonicalization
 
-While the exact approach to canonicalization for this solver will differ slightly
-wrt to lifetimes, please visit [the relevant chalk chapter][chalk] for now.
+Canonicalization is the process of *isolating* a value from its context and is necessary
+for global caching of goals which include inference variables.
 
-<!-- date-check: jan 2023 -->
-As of 10 January 2023,  canonicalization is not yet fully implemented
-in the new solver.
+The idea is that given the goals `u32: Trait<?x>` and `u32: Trait<?y>`, where `?x` and `?y`
+are two different currently unconstrained inference variables, we should get the same result
+for both goals. We can therefore prove *the canonical query* `exists<T> u32: Trait<T>` once
+and reuse the result.
 
-[chalk]: https://rust-lang.github.io/chalk/book/canonical_queries/canonicalization.html#canonicalization
+Let's first go over the way canonical queries work and then dive into the specifics of
+how canonicalization works.
+
+## A walkthrough of canonical queries
+
+To make this a bit easier, let's use the trait goal `u32: Trait<?x>` as an example with the
+assumption that the only relevant impl is `impl<T> Trait<Vec<T>> for u32`.
+
+### Canonicalizing the input
+
+We start by *canonicalizing* the goal, replacing inference variables with existential and
+placeholders with universal bound variables. This would result in the *canonical goal*
+`exists<T> u32: Trait<T>`.
+
+We remember the original values of all bound variables in the original context. Here this would
+map `T` back to `?x`. These original values are used later on when dealing with the query
+response.
+
+We now call the canonical query with the canonical goal.
+
+### Instantiating the canonical goal inside of the query
+
+To actually try to prove the canonical goal we start by instantiating the bound variables with
+inference variables and placeholders again.
+
+This happens inside of the query in a completely separate `InferCtxt`. Inside of the query we
+now have a goal `u32: Trait<?0>`. We also remember which value we've used to instantiate the bound
+variables in the canonical goal, which maps `T` to `?0`.
+
+We now compute the goal `u32: Trait<?0>` and figure out that this holds, but we've constrained
+`?0` to `Vec<?1>`. We finally convert this result to something useful to the caller.
+
+### Canonicalizing the query response
+
+We have to return to the caller both whether the goal holds, and the inference constraints
+from inside of the query.
+
+To return the inference results to the caller we canonicalize the mapping from bound variables
+to the instantiated values in the query. This means that the query response is `Certainty::Yes`
+and a mapping from `T` to `exists<U> Vec<U>`.
+
+### Instantiating the query response
+
+The caller now has to apply the constraints returned by the query. For this they first
+instantiate the bound variables of the canonical response with inference variables and
+placeholders again, so the mapping in the response is now from `T` to `Vec<?z>`.
+
+It now equates the original value of `T` (`?x`) with the value for `T` in the
+response (`Vec<?z>`), which correctly constrains `?x` to `Vec<?z>`.
+
+## `ExternalConstraints`
+
+Computing a trait goal may not only constrain inference variables, it can also add region
+obligations, e.g. given a goal `(): AOutlivesB<'a, 'b>` we would like to return the fact that
+`'a: 'b` has to hold.
+
+This is done by not only returning the mapping from bound variables to the instantiated values
+from the query but also extracting additional `ExternalConstraints` from the `InferCtxt` context
+while building the response.
+
+## How exactly does canonicalization work
+
+TODO: link to code once the PR lands and elaborate
+
+- types and consts: infer to existentially bound var, placeholder to universally bound var,
+    considering universes
+- generic parameters in the input get treated as placeholders in the root universe
+- all regions in the input get all mapped to existentially bound vars and we "uniquify" them.
+    `&'a (): Trait<'a>` gets canonicalized to `exists<'0, '1> &'0 (): Trait<'1>`. We do not care
+    about their universes and simply put all regions into the highest universe of the input.
+- once we collected all canonical vars we compress their universes, see comment in `finalize`.
+- in the output everything in a universe of the caller gets put into the root universe and only
+    gets its correct universe when we unify the var values with the orig values of the caller
+- we do not uniquify regions in the response and don't canonicalize `'static`