mlir currently fails to build on Solaris:
/vol/llvm/src/llvm-project/dist/mlir/lib/Conversion/VectorToLoops/ConvertVectorToLoops.cpp:78:20: error: reference to 'index_t' is ambiguous
IndexHandle zero(index_t(0)), one(index_t(1));
^
/usr/include/sys/types.h:103:16: note: candidate found by name lookup is 'index_t'
typedef short index_t;
^
/vol/llvm/src/llvm-project/dist/mlir/include/mlir/EDSC/Builders.h:27:8: note: candidate found by name lookup is 'mlir::edsc::index_t'
struct index_t {
^
and many more.
Given that POSIX reserves all identifiers ending in `_t` 2.2.2 The Name Space <https://pubs.opengroup.org/onlinepubs/9699919799/functions/V2_chap02.html>, it seems
quite unwise to use such identifiers in user code, even more so without a distinguished
prefix.
The following patch fixes this by renaming `index_t` to `index_type`.
cases.
Tested on `amd64-pc-solaris2.11` and `sparcv9-sun-solaris2.11`.
Differential Revision: https://reviews.llvm.org/D72619
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
Rename the 'shlis' operation in the standard dialect to 'shift_left'. Add tests
for this operation (these have been missing so far) and add a lowering to the
'shl' operation in the LLVM dialect.
Add also 'shift_right_signed' (lowered to LLVM's 'ashr') and 'shift_right_unsigned'
(lowered to 'lshr').
The original plan was to name these operations 'shift.left', 'shift.right.signed'
and 'shift.right.unsigned'. This works if the operations are prefixed with 'std.'
in MLIR assembly. Unfortunately during import the short form is ambigous with
operations from a hypothetical 'shift' dialect. The best solution seems to omit
dots in standard operations for now.
Closestensorflow/mlir#226
PiperOrigin-RevId: 286803388
This will be evolved into a simple programming model for custom ops and custom layers in followup CLs.
This CL also deletes the obsolete tablegen's reference-impl.td that was using EDSCs.
PiperOrigin-RevId: 285459545
This CL refactors some of the MLIR vector dependencies to allow decoupling VectorOps, vector analysis, vector transformations and vector conversions from each other.
This makes the system more modular and allows extracting VectorToVector into VectorTransforms that do not depend on vector conversions.
This refactoring exhibited a bunch of cyclic library dependencies that have been cleaned up.
PiperOrigin-RevId: 283660308
MLIRIR includes generated header for interfaces, including these headers require
an extra dependency to ensure these headers are generated before we attempt to
build MLIREDSCInterface.
PiperOrigin-RevId: 276518255
This allows mixing linalg operations with vector transfer operations (with additional modifications to affine ops) and is a step towards solving tensorflow/mlir#189.
PiperOrigin-RevId: 275543361
This CL adds support for loop.for operations in EDSC and adds a test.
This will be used in a followup commit to implement lowering of vector_transfer ops so that it works more generally and is not subject to affine constraints.
PiperOrigin-RevId: 275349796
Python bindings currently currently provide a makeScalarType function that
constructs one of the predefined types. It was implemented in the bindings
directly to circumvent the absence of standalone type parsing function. Now
that mlir::parseType has been made available, rely on the core parsing
procedure to construct types from strings in the bindings.
This changes includes a library reshuffling that splits out "CoreAPIs"
implementing the binding helper APIs into a separate library and makes that
dependent on the Parser library.
PiperOrigin-RevId: 274794516
This adds support for fcmp to the LLVM dialect and adds any necessary lowerings, as well as support for EDSCs.
Closestensorflow/mlir#69
PiperOrigin-RevId: 262475255
This field wasn't updated as the insertion point changed, making it potentially dangerous given the multi-level of MLIR(e.g. 'createBlock' would always insert the new block in 'region'). This also allows for building an OpBuilder with just a context.
PiperOrigin-RevId: 257829135
These methods assume that a function is a valid builtin top-level operation, and removing these methods allows for decoupling FuncOp and IR/. Utility "getParentOfType" methods have been added to Operation/OpState to allow for querying the first parent operation of a given type.
PiperOrigin-RevId: 257018913
Now that Locations are Attributes they contain a direct reference to the MLIRContext, i.e. the context can be directly accessed from the given location instead of being explicitly passed in.
PiperOrigin-RevId: 254568329
MemRefType may soon subclass ShapedType. ShapedType only guarantees that something has a shape (possibly dynamic), rank (or explicitly unranked), and fixed element type.
--
PiperOrigin-RevId: 250940537
Region body constructors in EDSC now take a callback to the function that fills
in the body. This callback is called immediately and not stored, so it is
sufficient to pass a reference to it and avoid a potentially expensive copy.
--
PiperOrigin-RevId: 250473793
Using ArrayRef introduces issues with the order of evaluation between a constructor and
the arguments of the subsequent calls to the `operator()`.
As a consequence the order of captures is not well-defined can go wrong with certain compilers (e.g. gcc-6.4).
This CL fixes the issue by using lambdas in lieu of ArrayRef.
--
PiperOrigin-RevId: 249114775
This is in preparation for making it also support/be a parent class of MemRefType. MemRefs have similar shape/rank/element semantics and it would be useful to be able to use these same utilities for them.
This CL should not change any semantics and only change variables, types, string literals, and comments. In follow-up CLs I will prepare all callers to handle MemRef types or remove their dependence on ShapedType.
Discussion/Rationale in https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/cHLoyfGu8y8
--
PiperOrigin-RevId: 248476449
* dyn_cast_or_null
- This will first check if the operation is null before trying to 'dyn_cast':
Value *v = ...;
if (auto forOp = dyn_cast_or_null<AffineForOp>(v->getDefiningOp()))
...
* isa_nonnull
- This will first check if the pointer is null before trying to 'isa':
Value *v = ...;
if (isa_nonnull<AffineForOp>(v->getDefiningOp());
...
--
PiperOrigin-RevId: 242171343
Some files were not built anymore internally but still referenced
from CMake. Delete them and unreference them in the CMake files.
--
PiperOrigin-RevId: 241744718
This version has been deprecated and can now be removed completely since the
last remaining user (Python bindings) migrated to declarative builders.
Several functions in lib/EDSC/Types.cpp construct core IR objects for the C
bindings. Move these functions into lib/EDSC/CoreAPIs.cpp until we decide
where they should live.
This completes the migration from the delayed-construction EDSC to Declarative
Builders.
--
PiperOrigin-RevId: 241716729
Most of the tests have been ported to be unit-tests and this pass is problematic in the way it depends on TableGen-generated files. This pass is also non-deterministic during multi-threading and a blocker to turning it on by default.
PiperOrigin-RevId: 240889154
Due to legacy reasons (ML/CFG function separation), regions in affine control
flow operations require contained blocks not to have terminators. This is
inconsistent with the notion of the block and may complicate code motion
between regions of affine control operations and other regions.
Introduce `affine.terminator`, a special terminator operation that must be used
to terminate blocks inside affine operations and transfers the control back to
he region enclosing the affine operation. For brevity and readability reasons,
allow `affine.for` and `affine.if` to omit the `affine.terminator` in their
regions when using custom printing and parsing format. The custom parser
injects the `affine.terminator` if it is missing so as to always have it
present in constructed operations.
Update transformations to account for the presence of terminator. In
particular, most code motion transformation between loops should leave the
terminator in place, and code motion between loops and non-affine blocks should
drop the terminator.
PiperOrigin-RevId: 240536998
Rainer Orth