torch-mlir/lib/Dialect/Torch/Transforms/PrepareForGlobalizeObjectGr...

116 lines
4.1 KiB
C++

//===- 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<PrimCallMethodOp> {
public:
ConvertPrimCallMethodToCall(MLIRContext *context, SymbolTable &symbolTable)
: OpRewritePattern(context), symbolTable(symbolTable) {}
LogicalResult matchAndRewrite(PrimCallMethodOp op,
PatternRewriter &rewriter) const override {
auto classType = symbolTable.lookup<ClassTypeOp>(
op.receiver().getType().cast<NnModuleType>().getClassName());
assert(classType && "malformed module -- missing ClassTypeOp");
FuncOp func;
for (auto method : classType.getOps<MethodOp>()) {
if (method.name() == op.name()) {
func = symbolTable.lookup<FuncOp>(method.function());
break;
}
}
assert(func);
rewriter.replaceOpWithNewOp<func::CallOp>(op, func, op->getOperands());
return success();
}
private:
SymbolTable &symbolTable;
};
} // namespace
namespace {
class EraseUnusedConstantOp : public OpRewritePattern<func::ConstantOp> {
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<ConvertPrimCallMethodToCall>(context, symbolTable);
func::CallIndirectOp::getCanonicalizationPatterns(patterns, context);
patterns.add<EraseUnusedConstantOp>(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<PrimCallMethodOp>();
target.addDynamicallyLegalOp<func::ConstantOp>(
[](func::ConstantOp op) { return !op.getType().isa<FunctionType>(); });
target.addIllegalOp<func::CallIndirectOp>();
target.markUnknownOpDynamicallyLegal([](Operation *) { return true; });
RewritePatternSet dummyPatterns(context);
if (failed(applyFullConversion(getOperation(), target,
std::move(dummyPatterns)))) {
return signalPassFailure();
}
}
};
} // namespace
std::unique_ptr<OperationPass<ModuleOp>>
mlir::torch::Torch::createPrepareForGlobalizeObjectGraphPass() {
return std::make_unique<PrepareForGlobalizeObjectGraphPass>();
}