This part of the tutorial is now covered by a new flow in Toy. This also removes a point of confusion as there is also a proper Linalg dialect.
PiperOrigin-RevId: 275338933
This chapters introduces the notion of a full conversion, and adds support for lowering down to the LLVM dialect, LLVM IR, and thus code generation.
PiperOrigin-RevId: 275337786
This chapter adds a partial lowering of toy operations, all but PrintOp, to a combination of the Affine and Std dialects. This chapter focuses on introducing the conversion framework, the benefits of partial lowering, and how easily dialects may co-exist in the IR.
PiperOrigin-RevId: 275150649
This Chapter now introduces and makes use of the Interface concept
in MLIR to demonstrate ShapeInference.
END_PUBLIC
Closestensorflow/mlir#191
PiperOrigin-RevId: 275085151
This is using Table-driven Declarative Rewrite Rules (DRR), the previous
version of the tutorial only showed the C++ patterns.
Closestensorflow/mlir#187
PiperOrigin-RevId: 274852321
This effectively rewrites Ch.2 to introduce dialects, operations, and registration instead of deferring to Ch.3. This allows for introducing the best practices up front(using ODS, registering operations, etc.), and limits the opaque API to the chapter document instead of the code.
PiperOrigin-RevId: 274724289
Some of the operations in the LLVM dialect are required to model the LLVM IR in
MLIR, for example "constant" operations are needed to declare a constant value
since MLIR, unlike LLVM, does not support immediate values as operands. To
avoid confusion with actual LLVM operations, we prefix such axuiliary
operations with "mlir.".
PiperOrigin-RevId: 266942838
This change generalizes the structure of the pass manager to allow arbitrary nesting pass managers for other operations, at any level. The only user visible change to existing code is the fact that a PassManager must now provide an MLIRContext on construction. A new class `OpPassManager` has been added that represents a pass manager on a specific operation type. `PassManager` will remain the top-level entry point into the pipeline, with OpPassManagers being nested underneath. OpPassManagers will still be implicitly nested if the operation type on the pass differs from the pass manager. To explicitly build a pipeline, the 'nest' methods on OpPassManager may be used:
// Pass manager for the top-level module.
PassManager pm(ctx);
// Nest a pipeline operating on FuncOp.
OpPassManager &fpm = pm.nest<FuncOp>();
fpm.addPass(...);
// Nest a pipeline under the FuncOp pipeline that operates on spirv::ModuleOp
OpPassManager &spvModulePM = pm.nest<spirv::ModuleOp>();
// Nest a pipeline on FuncOps inside of the spirv::ModuleOp.
OpPassManager &spvFuncPM = spvModulePM.nest<FuncOp>();
To help accomplish this a new general OperationPass is added that operates on opaque Operations. This pass can be inserted in a pass manager of any type to operate on any operation opaquely. An example of this opaque OperationPass is a VerifierPass, that simply runs the verifier opaquely on the current operation.
/// Pass to verify an operation and signal failure if necessary.
class VerifierPass : public OperationPass<VerifierPass> {
void runOnOperation() override {
Operation *op = getOperation();
if (failed(verify(op)))
signalPassFailure();
markAllAnalysesPreserved();
}
};
PiperOrigin-RevId: 266840344
The code and documentation for this chapter of the tutorial have been updated to follow the new flow. The toy 'array' type has been replaced by usages of the MLIR tensor type. The code has also been cleaned up and modernized.
Closestensorflow/mlir#101
PiperOrigin-RevId: 265744086
Change the use of 'array' to 'tensor' to reflect the new flow that the tutorial will follow. Also tidy up some of the documentation, code comments, and fix a few out-dated links.
PiperOrigin-RevId: 265174676
Switch to C++14 standard method as llvm::make_unique has been removed (
https://reviews.llvm.org/D66259). Also mark some targets as c++14 to ease next
integrates.
PiperOrigin-RevId: 263953918
This CL modifies the LowerLinalgToLoopsPass to use RewritePattern.
This will make it easier to inline Linalg generic functions and regions when emitting to loops in a subsequent CL.
PiperOrigin-RevId: 261894120
This allows for the attribute to hold symbolic references to other operations than FuncOp. This also allows for removing the dependence on FuncOp from the base Builder.
PiperOrigin-RevId: 257650017
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 CL implements the previously unsupported parsing for Range, View and Slice operations.
A pass is introduced to lower to the LLVM.
Tests are moved out of C++ land and into mlir/test/Examples.
This allows better fitting within standard developer workflows.
--
PiperOrigin-RevId: 245796600
Add a tutorial document explaining how to define a conversion from the Linalg
dialect to the LLVM IR dialect, bypassing the Affine dialect. It defines a
dynamic representation for a range and a view for the sake of type conversion.
Operation conversion becomes straightforward given the dynamic representation.
The code in the tutorial is better structured and better document that what we
currently have in the example, which will be updated separately.
--
PiperOrigin-RevId: 245498394
making the IR dumps much nicer.
This is part 2/3 of the path to making dialect types more nice. Part 3/3 will
slightly generalize the set of characters allowed in pretty types and make it
more principled.
--
PiperOrigin-RevId: 242249955
