//===- PrepareForGlobalizeObjectGraph.cpp ------------------------*- C++-*-===// // // This file is licensed 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 // Also available under a BSD-style license. See LICENSE. // //===----------------------------------------------------------------------===// #include "PassDetail.h" #include "mlir/Dialect/Func/IR/FuncOps.h" #include "mlir/IR/BlockAndValueMapping.h" #include "mlir/IR/Builders.h" #include "mlir/IR/BuiltinOps.h" #include "mlir/Transforms/DialectConversion.h" #include "mlir/Transforms/GreedyPatternRewriteDriver.h" #include "torch-mlir/Dialect/Torch/IR/TorchDialect.h" #include "torch-mlir/Dialect/Torch/IR/TorchOps.h" #include "torch-mlir/Dialect/Torch/Transforms/Passes.h" using namespace mlir; using namespace mlir::torch; using namespace mlir::torch::Torch; namespace { class ConvertPrimCallMethodToCall : public OpRewritePattern { public: ConvertPrimCallMethodToCall(MLIRContext *context, SymbolTable &symbolTable) : OpRewritePattern(context), symbolTable(symbolTable) {} LogicalResult matchAndRewrite(PrimCallMethodOp op, PatternRewriter &rewriter) const override { auto classType = symbolTable.lookup( op.receiver().getType().cast().getClassName()); assert(classType && "malformed module -- missing ClassTypeOp"); FuncOp func; for (auto method : classType.getOps()) { if (method.name() == op.name()) { func = symbolTable.lookup(method.function()); break; } } assert(func); rewriter.replaceOpWithNewOp(op, func, op->getOperands()); return success(); } private: SymbolTable &symbolTable; }; } // namespace namespace { class EraseUnusedConstantOp : public OpRewritePattern { public: using OpRewritePattern::OpRewritePattern; LogicalResult matchAndRewrite(func::ConstantOp op, PatternRewriter &rewriter) const override { if (op.use_empty()) { rewriter.eraseOp(op); return success(); } return failure(); } }; } // namespace namespace { class PrepareForGlobalizeObjectGraphPass : public PrepareForGlobalizeObjectGraphBase< PrepareForGlobalizeObjectGraphPass> { void runOnOperation() override { SymbolTable symbolTable(getOperation()); MLIRContext *context = &getContext(); RewritePatternSet patterns(context); patterns.add(context, symbolTable); func::CallIndirectOp::getCanonicalizationPatterns(patterns, context); patterns.add(context); // Use applyPatternsAndFoldGreedily because the CallIndirectOp folding // makes the ConstantOp unused, which does not work with the visitation // order of the dialect conversion infrastructure. // TODO: Do this with the dialect conversion infrastructure to avoid doing // folding as part of this. Or avoid folding during greedy pattern // application. See: https://llvm.org/PR49502 if (failed(applyPatternsAndFoldGreedily(getOperation(), std::move(patterns)))) { return signalPassFailure(); } // Do a dummy full conversion to ensure that the program has been converted // to the form we want. ConversionTarget target(*context); target.addIllegalOp(); target.addDynamicallyLegalOp( [](func::ConstantOp op) { return !op.getType().isa(); }); target.addIllegalOp(); target.markUnknownOpDynamicallyLegal([](Operation *) { return true; }); RewritePatternSet dummyPatterns(context); if (failed(applyFullConversion(getOperation(), target, std::move(dummyPatterns)))) { return signalPassFailure(); } } }; } // namespace std::unique_ptr> mlir::torch::Torch::createPrepareForGlobalizeObjectGraphPass() { return std::make_unique(); }