Replace the isa::Legalize enumeration with a function pointer. This
allows an ISA to define its own specific legalization actions instead of
relying on the default two.
Generate a LEGALIZE_ACTIONS table for each ISA which contains
legalization function pointers indexed by the legalization codes that
are already in the encoding tables. Include this table in
isa/*/enc_tables.rs.
Give the `Encodings` iterator a reference to the action table and change
its `legalize()` method to return a function pointer instead of an
ISA-specific code.
The Result<> returned from TargetIsa::encode() no longer implements
Debug, so eliminate uses of unwrap and expect on that type.
When an instruction doesn't have a valid encoding for the target ISA, it
needs to be legalized. Different legalization strategies can be
expressed as separate XFormGroup objects.
Make the choice of XFormGroup configurable per CPU mode, rather than
depending on a hard-coded default.
Add a CPUMode.legalize_type() method which assigns an XFormGroup to
controlling type variables and lets you set a default.
Add a `legalize` field to Level1Entry so the first-level hash table
lookup gives us the configured default legalization action for the
instruction's controlling type variable.
As per the comment in TypeEnv.normalize_tv about cancellation, whenever we create a TypeVar we must assert that there is no under/overflow. To make sure this always happen move the safety checks to TypeVar.derived() from the other helper methods
* Add more rigorous type inference and encapsulate the type inferece code in its own file (ti.py).
Add constraints accumulation during type inference, to represent constraints that cannot be expressed
using bijective derivation functions between typevars.
Add testing for new type inference code.
* Additional annotations to appease mypy
The List and Dict types are no longer implicitly available. They must be
imported from typing.
Type annotations must appear before the doc comment in a function. Also
fix type errors in these functions that weren't detected before.
Each instruction used in a pattern has constraints on the types of its
operands. These constraints are expressed as symbolic type variables.
Compute type variables for each variable used in a transformation
pattern. Some are free type variables, and some are derived from the
free type variables.
The type variables associated with variables can be used for computing
the result types of replacement instructions that don't support simple
forward type inference from their inputs.
The type sets computed by this patch are conservatively too large, so
they can't yet be used to type check patterns.
