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author | River Riddle <riverriddle@google.com> | 2019-12-17 10:07:26 -0800 |
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committer | A. Unique TensorFlower <gardener@tensorflow.org> | 2019-12-17 10:08:06 -0800 |
commit | f44cf23297089dd4beb6f81a7fdda4e59466dcdb (patch) | |
tree | 91fd982330235a7073376d589f9106a4a84522c4 /mlir/lib/Dialect/VectorOps/VectorTransforms.cpp | |
parent | 6e581e29a47b3005b14d8c1dac29bd9cd9c48381 (diff) | |
download | bcm5719-llvm-f44cf23297089dd4beb6f81a7fdda4e59466dcdb.tar.gz bcm5719-llvm-f44cf23297089dd4beb6f81a7fdda4e59466dcdb.zip |
Add a new utility class TypeSwitch to ADT.
This class provides a simplified mechanism for defining a switch over a set of types using llvm casting functionality. More specifically, this allows for defining a switch over a value of type T where each case corresponds to a type(CaseT) that can be used with dyn_cast<CaseT>(...). An example is shown below:
// Traditional piece of code:
Operation *op = ...;
if (auto constant = dyn_cast<ConstantOp>(op))
...;
else if (auto return = dyn_cast<ReturnOp>(op))
...;
else
...;
// New piece of code:
Operation *op = ...;
TypeSwitch<Operation *>(op)
.Case<ConstantOp>([](ConstantOp constant) { ... })
.Case<ReturnOp>([](ReturnOp return) { ... })
.Default([](Operation *op) { ... });
Aside from the above, TypeSwitch supports return values, void return, multiple types per case, etc. The usability is intended to be very similar to StringSwitch.
(Using c++14 template lambdas makes everything even nicer)
More complex example of how this makes certain things easier:
LogicalResult process(Constant op);
LogicalResult process(ReturnOp op);
LogicalResult process(FuncOp op);
TypeSwitch<Operation *, LogicalResult>(op)
.Case<ConstantOp, ReturnOp, FuncOp>([](auto op) { return process(op); })
.Default([](Operation *op) { return op->emitError() << "could not be processed"; });
PiperOrigin-RevId: 286003613
Diffstat (limited to 'mlir/lib/Dialect/VectorOps/VectorTransforms.cpp')
0 files changed, 0 insertions, 0 deletions