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torch-mlir/lib/RefBackend/RefBackend.cpp

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//===----------------------------------------------------------------------===//
//
// 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
// Also available under a BSD-style license. See LICENSE.
//
//===----------------------------------------------------------------------===//
//
// The torch-mlir "reference backend" requires a few passes to glue things
// together so that the final IR will work with ExecutionEngine.
//
// There is no actual "backend".
//
//===----------------------------------------------------------------------===//
#include "PassDetail.h"
#include "mlir/Dialect/Arithmetic/Transforms/Passes.h"
#include "mlir/Dialect/Math/IR/Math.h"
#include "mlir/Dialect/Math/Transforms/Approximation.h"
#include "mlir/Dialect/Math/Transforms/Passes.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/Transforms/DialectConversion.h"
#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionOps.h"
#include "torch-mlir/RefBackend/Passes.h"
#include <numeric>
#include <set>
using namespace mlir;
using namespace mlir::torch;
using namespace mlir::torch::RefBackend;
//===----------------------------------------------------------------------===//
// Pass registration
//===----------------------------------------------------------------------===//
namespace {
#define GEN_PASS_REGISTRATION
#include "torch-mlir/RefBackend/Passes.h.inc"
} // end namespace
void mlir::torch::RefBackend::registerRefBackendPasses() { ::registerPasses(); }
//===----------------------------------------------------------------------===//
// MungeCallingConventions
//===----------------------------------------------------------------------===//
static bool isArgMemRefTypeValid(Type type) {
if (auto memRefType = type.dyn_cast<MemRefType>()) {
Type elemTy = memRefType.getElementType();
if (elemTy.isa<Float32Type>()) {
return true;
} else if (elemTy.isa<Float64Type>()) {
return true;
} else if (auto integerTy = elemTy.dyn_cast<IntegerType>()) {
if (integerTy.isSignlessInteger(64))
return true;
if (integerTy.isSignlessInteger(32))
return true;
if (integerTy.isSignlessInteger(1))
return true;
}
}
return false;
}
static void addEmitCInterfaceAttr(FuncOp func) {
func->setAttr("llvm.emit_c_interface", UnitAttr::get(func.getContext()));
}
static Type getAbiTypeForMemRef(Type type) {
return UnrankedMemRefType::get(type.cast<MemRefType>().getElementType(), 0);
}
// Helper function to get the type string for one return value like i32, f64,
// mri32 etc. The strings from multiple return values are concatenated to get
// the consumeFuncReturnFunc name.
static std::string getTypeToken(Type type) {
if (type.isSignlessInteger())
return ("i" + Twine(type.getIntOrFloatBitWidth())).str();
else if (type.isa<mlir::FloatType>())
return ("f" + Twine(type.getIntOrFloatBitWidth())).str();
else if (auto memRefType = type.dyn_cast<UnrankedMemRefType>())
return "mr" + getTypeToken(memRefType.getElementType());
llvm_unreachable(
"Type token should handle all types: memref, float and int type");
}
// Systematically derive the consumeFuncReturnFunc name from return value types.
static std::string getConsumeReturnFunctionNameForReturnTypes(TypeRange types) {
SmallVector<std::string> tokens = {"refbackend_consume_func_return"};
for (auto type : types)
tokens.push_back(getTypeToken(type));
return std::accumulate(tokens.begin(), tokens.end(), std::string(),
[](std::string &a, std::string &b) {
return a.empty() ? b : (a + "_" + b);
});
}
// Replace the original returnOp with a call to consumeFuncReturnFunc and add
// the op to the `toErase` vector.
static void replaceReturnWithCall(OpBuilder b, ReturnOp op, StringRef funcName,
TypeRange retTypes,
SmallVectorImpl<Value> &vals,
SmallVectorImpl<Operation *> &toErase) {
b.create<mlir::CallOp>(op.getLoc(), funcName, TypeRange({}), vals);
b.create<mlir::ReturnOp>(op.getLoc());
toErase.push_back(op);
}
static LogicalResult mungeFunction(
FuncOp func, std::set<std::string> &supportedConsumeFuncReturnFuncs,
std::map<std::string, std::vector<Type>> &invokedConsumeFuncReturnFuncs) {
// Only need to call mungeFunction for functions callable from outside of the
// module.
if (func.isPrivate())
return success();
// Add `llvm.emit_c_interface`.
// This allows ExecutionEngine to resolve the symbol properly.
addEmitCInterfaceAttr(func);
// Rewrite the function as follows:
// - replace all memref arguments with unranked memref
// - replace all returns with a call to a function, which is going to be
// supplied by the code setting up the ExecutionEngine to process the
// result. Additionally, ensure that all results are passed as unranked
// memrefs.
// - replace the function signature accordingly (unranked inputs, no returns).
OpBuilder b(func.getBody());
SmallVector<Type> newArgTypes;
for (auto arg : func.getArguments()) {
auto type = arg.getType();
if (!isArgMemRefTypeValid(type))
return emitError(arg.getLoc(),
"argument must be a memref of f32, f64, i32, i64, i1");
auto cast = b.create<memref::CastOp>(arg.getLoc(), arg, type);
arg.replaceAllUsesExcept(cast, cast);
arg.setType(getAbiTypeForMemRef(type));
newArgTypes.push_back(arg.getType());
}
SmallVector<Operation *> toErase;
bool isSupported = true;
func.walk([&](ReturnOp op) {
auto types = op.getOperandTypes();
b.setInsertionPoint(op);
// Memref Types.
std::vector<Type> retTypes;
SmallVector<Value> retVals;
for (auto en : llvm::enumerate(types)) {
Type retType = en.value();
Value retVal = op.getOperand(en.index());
if (auto memrefReturnType = retType.dyn_cast<MemRefType>()) {
auto elemType = memrefReturnType.getElementType();
retType = UnrankedMemRefType::get(elemType, 0);
// Cast to unranked memref type before sending it as a function
// argument.
retVal = b.create<memref::CastOp>(
op.getLoc(), retVal, getAbiTypeForMemRef(types[en.index()]));
}
retTypes.push_back(retType);
retVals.push_back(retVal);
}
auto supportedFuncsEnd = supportedConsumeFuncReturnFuncs.end();
std::string funcName = getConsumeReturnFunctionNameForReturnTypes(retTypes);
if (supportedConsumeFuncReturnFuncs.find(funcName) == supportedFuncsEnd) {
op.emitError("Supported return types:"
"mri1, mri32, mri64, mrf32, mrf64, i64, f32, f64,"
"(mrf32, mri64), (mrf32, mrf32), (mrf64, mrf64),"
"(mrf32, mrf32, mrf32)");
isSupported = false;
}
auto invokedFuncsEnd = invokedConsumeFuncReturnFuncs.end();
if (invokedConsumeFuncReturnFuncs.find(funcName) == invokedFuncsEnd)
invokedConsumeFuncReturnFuncs.insert({funcName, retTypes});
replaceReturnWithCall(b, op, funcName, retTypes, retVals, toErase);
});
if (!isSupported)
return failure();
func.setType(FunctionType::get(func.getContext(), newArgTypes, {}));
for (Operation *op : toErase)
op->erase();
return success();
}
static std::set<std::string> getSupportedConsumeFuncReturnFuncs(OpBuilder &b) {
std::set<std::string> funcNames;
Type mri1 = UnrankedMemRefType::get(b.getI1Type(), 0);
Type mri32 = UnrankedMemRefType::get(b.getI32Type(), 0);
Type mri64 = UnrankedMemRefType::get(b.getI64Type(), 0);
Type mrf32 = UnrankedMemRefType::get(b.getF32Type(), 0);
Type mrf64 = UnrankedMemRefType::get(b.getF64Type(), 0);
Type i64 = b.getI64Type();
Type f32 = b.getF32Type();
Type f64 = b.getF64Type();
SmallVector<TypeRange> supportedReturnTypes = {mri1,
mri32,
mri64,
mrf32,
mrf64,
i64,
f32,
f64,
{mrf32, mri64},
{mrf32, mrf32},
{mrf64, mrf64},
{mrf32, mrf32, mrf32}};
llvm::for_each(supportedReturnTypes, [&](TypeRange &types) {
funcNames.insert(getConsumeReturnFunctionNameForReturnTypes(types));
});
return funcNames;
}
namespace {
class MungeCallingConventions
: public MungeCallingConventionsBase<MungeCallingConventions> {
void runOnOperation() override {
auto module = getOperation();
OpBuilder b(module.getBodyRegion());
static std::set<std::string> supported =
getSupportedConsumeFuncReturnFuncs(b);
std::map<std::string, std::vector<Type>> invokedConsumeFuncReturnFuncs;
for (auto func : module.getOps<FuncOp>()) {
if (failed(mungeFunction(func, supported, invokedConsumeFuncReturnFuncs)))
return signalPassFailure();
}
// Create FuncOp for consumeFuncReturnFuncs that are used.
for (auto &p : invokedConsumeFuncReturnFuncs) {
auto consumeFuncReturnFunc =
b.create<FuncOp>(module.getLoc(), p.first,
FunctionType::get(module.getContext(), p.second, {}),
b.getStringAttr("private"));
addEmitCInterfaceAttr(consumeFuncReturnFunc);
}
}
};
} // namespace
std::unique_ptr<OperationPass<ModuleOp>>
mlir::torch::RefBackend::createMungeCallingConventionsPass() {
return std::make_unique<MungeCallingConventions>();
}
//===----------------------------------------------------------------------===//
// InsertRngGlobals
//===----------------------------------------------------------------------===//
static constexpr StringRef getSeedGobalVarName() { return "global_seed"; }
// Declare a memref<i64> global variable for the seed.
static void createGlobalVariableForSeed(OpBuilder &b, ModuleOp module) {
b.setInsertionPointToStart(module.getBody());
Type elemTy = b.getI64Type();
auto memref0D = MemRefType::get({}, elemTy);
auto tensor0D = RankedTensorType::get({}, elemTy);
b.create<memref::GlobalOp>(
UnknownLoc::get(b.getContext()), getSeedGobalVarName(),
/*sym_visibility=*/b.getStringAttr("private"),
/*type=*/memref0D,
/*initial_value=*/DenseIntElementsAttr::get(tensor0D, {APInt(64, 0)}),
/*constant=*/false,
/*alignment=*/nullptr);
}
// Generate sequence for getting the next seed with LCG step:
// nextSeed = (multiplier * currentSeed + incrementStep) mod 64.
// Refer to https://en.wikipedia.org/wiki/Linear_congruential_generator.
static Value lowerGetNextSeed(OpBuilder &b, Location loc) {
// Get the current seed value.
auto memref1DType = MemRefType::get({}, b.getI64Type());
Value globalVar =
b.create<memref::GetGlobalOp>(loc, memref1DType, getSeedGobalVarName());
Value currentSeed = b.create<memref::LoadOp>(loc, globalVar);
// The value of multiplier and incrementStep are referenced from
// https://en.wikipedia.org/wiki/Linear_congruential_generator for 2^64.
Value multiplier = b.create<arith::ConstantOp>(
loc, b.getI64IntegerAttr(6364136223846793005));
Value incrementStep = b.create<arith::ConstantOp>(
loc, b.getI64IntegerAttr(1442695040888963407));
// temp = multiplier * currentSeed + incrementStep
Value mul = b.create<arith::MulIOp>(loc, currentSeed, multiplier);
Value temp = b.create<arith::AddIOp>(loc, mul, incrementStep);
// temp mod 64 = temp & 63
Value cst127 = b.create<arith::ConstantOp>(loc, b.getI64IntegerAttr(127));
Value nextSeed = b.create<arith::AndIOp>(loc, temp, cst127);
b.create<memref::StoreOp>(loc, nextSeed, globalVar);
return nextSeed;
}
// The global seed is stored into a memref<i64> global variable as the only
// element.
namespace {
class InsertRngGlobals : public InsertRngGlobalsBase<InsertRngGlobals> {
void runOnOperation() override {
auto module = getOperation();
OpBuilder b(module.getBodyRegion());
createGlobalVariableForSeed(b, module);
SmallVector<Operation *> toErase;
module.walk([&](TorchConversion::GetNextSeedOp op) {
b.setInsertionPoint(op);
Value seed = lowerGetNextSeed(b, op.getLoc());
op.replaceAllUsesWith(seed);
toErase.push_back(op);
});
for (auto op : toErase)
op->erase();
}
};
} // namespace
std::unique_ptr<OperationPass<ModuleOp>>
mlir::torch::RefBackend::createInsertRngGlobalsPass() {
return std::make_unique<InsertRngGlobals>();
}
//===----------------------------------------------------------------------===//
// ExpandOpsForLLVM
//===----------------------------------------------------------------------===//
namespace {
class ExpandOpsForLLVM : public ExpandOpsForLLVMBase<ExpandOpsForLLVM> {
void runOnOperation() override {
auto func = getOperation();
auto *context = &getContext();
RewritePatternSet patterns(context);
populateExpandTanhPattern(patterns);
patterns.add<math::ErfPolynomialApproximation>(patterns.getContext());
ConversionTarget target(*context);
target.addLegalDialect<StandardOpsDialect>();
target.addLegalDialect<math::MathDialect>();
target.addLegalDialect<arith::ArithmeticDialect>();
target.addIllegalOp<math::TanhOp>();
target.addIllegalOp<math::ErfOp>();
if (failed(applyPartialConversion(func, target, std::move(patterns)))) {
return signalPassFailure();
}
}
};
} // namespace
std::unique_ptr<OperationPass<FuncOp>>
mlir::torch::RefBackend::createExpandOpsForLLVMPass() {
return std::make_unique<ExpandOpsForLLVM>();
}
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