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