Refactors operation parsing to share functionality between CFG and ML functions. ML function construction now goes through a builder, similar to the way it is done for
CFG functions.
PiperOrigin-RevId: 204779279
is no strong reason to prefer one or the other, but // is nice for consistency
given the rest of the compiler is written in C++.
PiperOrigin-RevId: 204628476
- fold constants when possible.
- for a mul expression, canonicalize to always keep the LHS as the
constant/symbolic term, and similarly, the RHS for an add expression to keep
it closer to the mathematical form. (Eg: f(x) = 3*x + 5)); other similar simplifications;
- verify binary op expressions at creation time.
TODO: we can completely drop AffineSubExpr, and instead use add and mul by -1.
This way something like x - 4 and -4 + x get canonicalized to x + -1 * 4
instead of being x - 4 and x + -4. (The other alternative if wanted to retain
AffineSubExpr would be to simplify x + -1*y to x - y and x + <neg number> to x
- <pos number>).
PiperOrigin-RevId: 204240258
- check for non-affine expressions
- handle negative numbers and negation of id's, expressions
- functions to check if a map is pure affine or semi-affine
- simplify/clean up affine map parsing code
- report more errors messages, more accurate error messages
PiperOrigin-RevId: 203773633
reducing the memory impact on Operation to one word instead of 3 from an
std::vector.
Implement Jacques' suggestion to merge OpImpl::Storage into OpImpl::Base.
PiperOrigin-RevId: 203426518
properties:
- They allow type checked dynamic casting from their base Operation.
- They allow nice accessors for C++ clients, e.g. a "getIndex()" method on
'dim' that returns an unsigned.
- They work with both OperationInst/OperationStmt (once OperationStmt is
implemented).
- They get custom printing logic. They will eventually get custom parsing,
verifier, and builder logic as well.
- Out of tree clients can register their own operation set without having to
change MLIR core, e.g. for TensorFlow or custom target instructions.
This registers addf and dim as examples.
PiperOrigin-RevId: 203382993
A recursive descent parser for affine maps/expressions with operator precedence and
associativity. (While on this, sketch out uniqui'ing functionality for affine maps
and affine binary op expressions (partly).)
PiperOrigin-RevId: 203222063
important for low-bitwidth inference cases and hardware synthesis targets.
Rename 'int' to 'affineint' to avoid confusion between "the integers" and "the int
type".
PiperOrigin-RevId: 202751508
Run test case:
$ mlir-opt test/IR/parser-affine-map.mlir
test/IR/parser-affine-map.mlir:3:30: error: expect '(' at start of map range
#hello_world2 (i, j) [s0] -> i+s0, j)
^
PiperOrigin-RevId: 202736856
class.
Introduce an Identifier class to MLIRContext to represent uniqued identifiers,
introduce string literal support to the lexer, introducing parser and printer
support etc.
PiperOrigin-RevId: 202592007
Add parsing tests with errors. Follows direct path of splitting file into test groups (using a marker) and parsing each section individually. The expected errors are checked using FileCheck and parser error does not result in terminating parsing the rest of the file if check-parser-error.
This is an interim approach until refactoring lexer/parser.
PiperOrigin-RevId: 201867941
This is pretty much minimal scaffolding for this step. Basic block arguments,
instructions, other terminators, a proper IR representation for
blocks/instructions, etc are all coming.
PiperOrigin-RevId: 201826439
Semi-affine maps and address spaces are not yet supported (someone want to take
this on?). We also don't generate IR objects for types yet, which I plan to
tackle next.
PiperOrigin-RevId: 201754283
Tatiana Shpeisman