| //===- TestTensorCopyInsertion.cpp - Bufferization Analysis -----*- c++ -*-===// |
| // |
| // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| // See https://llvm.org/LICENSE.txt for license information. |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #include "mlir/Dialect/Bufferization/IR/Bufferization.h" |
| #include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h" |
| #include "mlir/Dialect/Bufferization/Transforms/Transforms.h" |
| #include "mlir/Pass/Pass.h" |
| |
| using namespace mlir; |
| |
| namespace { |
| /// This pass runs One-Shot Analysis and inserts copies for all OpOperands that |
| /// were decided to bufferize out-of-place. After running this pass, a |
| /// bufferization can write to buffers directly (without making copies) and no |
| /// longer has to care about potential read-after-write conflicts. |
| /// |
| /// Note: By default, all newly inserted tensor copies/allocs (i.e., newly |
| /// created `bufferization.alloc_tensor` ops) that do not escape block are |
| /// annotated with `escape = false`. If `create-allocs` is unset, all newly |
| /// inserted tensor copies/allocs are annotated with `escape = true`. In that |
| /// case, they are not getting deallocated when bufferizing the IR. |
| struct TestTensorCopyInsertionPass |
| : public PassWrapper<TestTensorCopyInsertionPass, OperationPass<ModuleOp>> { |
| MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestTensorCopyInsertionPass) |
| |
| TestTensorCopyInsertionPass() = default; |
| TestTensorCopyInsertionPass(const TestTensorCopyInsertionPass &pass) |
| : PassWrapper(pass) {} |
| |
| void getDependentDialects(DialectRegistry ®istry) const override { |
| registry.insert<bufferization::BufferizationDialect>(); |
| } |
| StringRef getArgument() const final { return "test-tensor-copy-insertion"; } |
| StringRef getDescription() const final { |
| return "Module pass to test Tensor Copy Insertion"; |
| } |
| |
| void runOnOperation() override { |
| bufferization::OneShotBufferizationOptions options; |
| options.allowReturnAllocsFromLoops = allowReturnAllocsFromLoops; |
| options.bufferizeFunctionBoundaries = bufferizeFunctionBoundaries; |
| if (mustInferMemorySpace) { |
| options.defaultMemorySpaceFn = |
| [](TensorType t) -> std::optional<Attribute> { return std::nullopt; }; |
| } |
| if (failed(bufferization::insertTensorCopies(getOperation(), options))) |
| signalPassFailure(); |
| } |
| |
| Option<bool> allowReturnAllocsFromLoops{ |
| *this, "allow-return-allocs-from-loops", |
| llvm::cl::desc("Allows returning/yielding new allocations from a loop."), |
| llvm::cl::init(false)}; |
| Option<bool> bufferizeFunctionBoundaries{ |
| *this, "bufferize-function-boundaries", |
| llvm::cl::desc("Bufferize function boundaries."), llvm::cl::init(false)}; |
| Option<bool> mustInferMemorySpace{ |
| *this, "must-infer-memory-space", |
| llvm::cl::desc( |
| "The memory space of an memref types must always be inferred. If " |
| "unset, a default memory space of 0 is used otherwise."), |
| llvm::cl::init(false)}; |
| }; |
| } // namespace |
| |
| namespace mlir::test { |
| void registerTestTensorCopyInsertionPass() { |
| PassRegistration<TestTensorCopyInsertionPass>(); |
| } |
| } // namespace mlir::test |