Originally, loop steps were implemented using `addi` and `constant` operations because `affine_apply` was not handled in the first implementation. The support for `affine_apply` has been added, use it to implement the update of the loop induction variable. This is more consistent with the lower and upper bounds of the loop that are also implemented as `affine_apply`, removes the dependence of the converted function on the StandardOps dialect and makes it clear from the CFG function that all operations on the loop induction variable are purely affine. PiperOrigin-RevId: 225165337
639 lines
27 KiB
C++
639 lines
27 KiB
C++
//===- ConvertToCFG.cpp - ML function to CFG function conversion ----------===//
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//
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// Copyright 2019 The MLIR Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// =============================================================================
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//
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// This file implements APIs to convert ML functions into CFG functions.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/IR/Builders.h"
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#include "mlir/IR/BuiltinOps.h"
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#include "mlir/IR/CFGFunction.h"
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#include "mlir/IR/MLFunction.h"
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#include "mlir/IR/MLIRContext.h"
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#include "mlir/IR/Module.h"
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#include "mlir/IR/StmtVisitor.h"
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#include "mlir/Pass.h"
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#include "mlir/StandardOps/StandardOps.h"
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#include "mlir/Support/Functional.h"
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#include "mlir/Transforms/Passes.h"
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#include "mlir/Transforms/Utils.h"
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#include "llvm/ADT/DenseSet.h"
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#include "llvm/Support/CommandLine.h"
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using namespace mlir;
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//===----------------------------------------------------------------------===//
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// ML function converter
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//===----------------------------------------------------------------------===//
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namespace {
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// Generates CFG function equivalent to the given ML function.
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class FunctionConverter : public StmtVisitor<FunctionConverter> {
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public:
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FunctionConverter(CFGFunction *cfgFunc)
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: cfgFunc(cfgFunc), builder(cfgFunc) {}
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CFGFunction *convert(MLFunction *mlFunc);
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void visitForStmt(ForStmt *forStmt);
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void visitIfStmt(IfStmt *ifStmt);
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void visitOperationStmt(OperationStmt *opStmt);
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private:
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CFGValue *getConstantIndexValue(int64_t value);
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void visitStmtBlock(StmtBlock *stmtBlock);
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CFGValue *buildMinMaxReductionSeq(
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Location loc, CmpIPredicate predicate,
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llvm::iterator_range<Operation::result_iterator> values);
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CFGFunction *cfgFunc;
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CFGFuncBuilder builder;
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// Mapping between original MLValues and lowered CFGValues.
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llvm::DenseMap<const MLValue *, CFGValue *> valueRemapping;
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};
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} // end anonymous namespace
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// Return a vector of OperationStmt's arguments as SSAValues. For each
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// statement operands, represented as MLValue, lookup its CFGValue conterpart in
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// the valueRemapping table.
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static llvm::SmallVector<SSAValue *, 4>
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operandsAs(Statement *opStmt,
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const llvm::DenseMap<const MLValue *, CFGValue *> &valueRemapping) {
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llvm::SmallVector<SSAValue *, 4> operands;
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for (const MLValue *operand : opStmt->getOperands()) {
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assert(valueRemapping.count(operand) != 0 && "operand is not defined");
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operands.push_back(valueRemapping.lookup(operand));
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}
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return operands;
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}
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// Convert an operation statement into an operation instruction.
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//
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// The operation description (name, number and types of operands or results)
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// remains the same but the values must be updated to be CFGValues. Update the
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// mapping MLValue->CFGValue as the conversion is performed. The operation
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// instruction is appended to current block (end of SESE region).
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void FunctionConverter::visitOperationStmt(OperationStmt *opStmt) {
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// Set up basic operation state (context, name, operands).
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OperationState state(cfgFunc->getContext(), opStmt->getLoc(),
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opStmt->getName());
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state.addOperands(operandsAs(opStmt, valueRemapping));
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// Set up operation return types. The corresponding SSAValues will become
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// available after the operation is created.
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state.addTypes(
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functional::map([](SSAValue *result) { return result->getType(); },
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opStmt->getResults()));
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// Copy attributes.
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for (auto attr : opStmt->getAttrs()) {
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state.addAttribute(attr.first.strref(), attr.second);
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}
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auto opInst = builder.createOperation(state);
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// Make results of the operation accessible to the following operations
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// through remapping.
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assert(opInst->getNumResults() == opStmt->getNumResults());
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for (unsigned i = 0, n = opInst->getNumResults(); i < n; ++i) {
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valueRemapping.insert(
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std::make_pair(opStmt->getResult(i), opInst->getResult(i)));
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}
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}
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// Create a CFGValue for the given integer constant of index type.
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CFGValue *FunctionConverter::getConstantIndexValue(int64_t value) {
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auto op = builder.create<ConstantIndexOp>(builder.getUnknownLoc(), value);
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return cast<CFGValue>(op->getResult());
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}
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// Visit all statements in the given statement block.
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void FunctionConverter::visitStmtBlock(StmtBlock *stmtBlock) {
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for (auto &stmt : *stmtBlock)
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this->visit(&stmt);
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}
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// Given a range of values, emit the code that reduces them with "min" or "max"
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// depending on the provided comparison predicate. The predicate defines which
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// comparison to perform, "lt" for "min", "gt" for "max" and is used for the
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// `cmpi` operation followed by the `select` operation:
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//
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// %cond = cmpi "predicate" %v0, %v1
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// %result = select %cond, %v0, %v1
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//
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// Multiple values are scanned in a linear sequence. This creates a data
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// dependences that wouldn't exist in a tree reduction, but is easier to
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// recognize as a reduction by the subsequent passes.
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CFGValue *FunctionConverter::buildMinMaxReductionSeq(
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Location loc, CmpIPredicate predicate,
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llvm::iterator_range<Operation::result_iterator> values) {
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assert(!llvm::empty(values) && "empty min/max chain");
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auto valueIt = values.begin();
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CFGValue *value = cast<CFGValue>(*valueIt++);
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for (; valueIt != values.end(); ++valueIt) {
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auto cmpOp = builder.create<CmpIOp>(loc, predicate, value, *valueIt);
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auto selectOp =
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builder.create<SelectOp>(loc, cmpOp->getResult(), value, *valueIt);
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value = cast<CFGValue>(selectOp->getResult());
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}
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return value;
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}
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// Convert a "for" loop to a flow of basic blocks.
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//
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// Create an SESE region for the loop (including its body) and append it to the
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// end of the current region. The loop region consists of the initialization
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// block that sets up the initial value of the loop induction variable (%iv) and
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// computes the loop bounds that are loop-invariant in MLFunctions; the
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// condition block that checks the exit condition of the loop; the body SESE
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// region; and the end block that post-dominates the loop. The end block of the
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// loop becomes the new end of the current SESE region. The body of the loop is
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// constructed recursively after starting a new region (it may be, for example,
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// a nested loop). Induction variable modification is appended to the body SESE
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// region that always loops back to the condition block.
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//
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// +--------------------------------+
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// | <end of current SESE region> |
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// | <current insertion point> |
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// | br init |
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// +--------------------------------+
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// |
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// v
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// +--------------------------------+
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// | init: |
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// | <start of loop SESE region> |
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// | <compute initial %iv value> |
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// | br cond(%iv) |
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// +--------------------------------+
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// |
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// -------| |
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// | v v
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// | +--------------------------------+
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// | | cond(%iv): |
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// | | <compare %iv to upper bound> |
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// | | cond_br %r, body, end |
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// | +--------------------------------+
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// | | |
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// | | -------------|
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// | v |
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// | +--------------------------------+ |
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// | | body: | |
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// | | <body SESE region start> | |
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// | | <...> | |
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// | +--------------------------------+ |
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// | | |
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// | ... <SESE region of the body> |
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// | | |
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// | v |
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// | +--------------------------------+ |
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// | | body-end: | |
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// | | <body SESE region end> | |
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// | | %new_iv =<add step to %iv> | |
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// | | br cond(%new_iv) | |
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// | +--------------------------------+ |
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// | | |
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// |----------- |--------------------
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// v
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// +--------------------------------+
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// | end: |
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// | <end of loop SESE region> |
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// | <new insertion point> |
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// +--------------------------------+
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//
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void FunctionConverter::visitForStmt(ForStmt *forStmt) {
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// First, store the loop insertion location so that we can go back to it after
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// creating the new blocks (block creation updates the insertion point).
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BasicBlock *loopInsertionPoint = builder.getInsertionBlock();
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// Create blocks so that they appear in more human-readable order in the
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// output.
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BasicBlock *loopInitBlock = builder.createBlock();
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BasicBlock *loopConditionBlock = builder.createBlock();
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BasicBlock *loopBodyFirstBlock = builder.createBlock();
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// At the loop insertion location, branch immediately to the loop init block.
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builder.setInsertionPoint(loopInsertionPoint);
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builder.create<BranchOp>(builder.getUnknownLoc(), loopInitBlock);
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// The loop condition block has an argument for loop induction variable.
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// Create it upfront and make the loop induction variable -> basic block
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// argument remapping available to the following instructions. ForStatement
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// is-a MLValue corresponding to the loop induction variable.
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builder.setInsertionPoint(loopConditionBlock);
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CFGValue *iv = loopConditionBlock->addArgument(builder.getIndexType());
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valueRemapping.insert(std::make_pair(forStmt, iv));
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// Recursively construct loop body region.
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// Walking manually because we need custom logic before and after traversing
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// the list of children.
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builder.setInsertionPoint(loopBodyFirstBlock);
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visitStmtBlock(forStmt);
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// Builder point is currently at the last block of the loop body. Append the
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// induction variable stepping to this block and branch back to the exit
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// condition block. Construct an affine map f : (x -> x+step) and apply this
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// map to the induction variable.
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auto affStep = builder.getAffineConstantExpr(forStmt->getStep());
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auto affDim = builder.getAffineDimExpr(0);
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auto affStepMap = builder.getAffineMap(1, 0, {affDim + affStep}, {});
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auto stepOp =
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builder.create<AffineApplyOp>(forStmt->getLoc(), affStepMap, iv);
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CFGValue *nextIvValue = cast<CFGValue>(stepOp->getResult(0));
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builder.create<BranchOp>(builder.getUnknownLoc(), loopConditionBlock,
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nextIvValue);
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// Create post-loop block here so that it appears after all loop body blocks.
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BasicBlock *postLoopBlock = builder.createBlock();
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builder.setInsertionPoint(loopInitBlock);
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// Compute loop bounds using affine_apply after remapping its operands.
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auto remapOperands = [this](const SSAValue *value) -> SSAValue * {
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const MLValue *mlValue = dyn_cast<MLValue>(value);
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return valueRemapping.lookup(mlValue);
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};
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auto operands =
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functional::map(remapOperands, forStmt->getLowerBoundOperands());
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auto lbAffineApply = builder.create<AffineApplyOp>(
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forStmt->getLoc(), forStmt->getLowerBoundMap(), operands);
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CFGValue *lowerBound = buildMinMaxReductionSeq(
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forStmt->getLoc(), CmpIPredicate::SGT, lbAffineApply->getResults());
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operands = functional::map(remapOperands, forStmt->getUpperBoundOperands());
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auto ubAffineApply = builder.create<AffineApplyOp>(
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forStmt->getLoc(), forStmt->getUpperBoundMap(), operands);
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CFGValue *upperBound = buildMinMaxReductionSeq(
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forStmt->getLoc(), CmpIPredicate::SLT, ubAffineApply->getResults());
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builder.create<BranchOp>(builder.getUnknownLoc(), loopConditionBlock,
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lowerBound);
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builder.setInsertionPoint(loopConditionBlock);
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auto comparisonOp = builder.create<CmpIOp>(
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forStmt->getLoc(), CmpIPredicate::SLT, iv, upperBound);
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auto comparisonResult = cast<CFGValue>(comparisonOp->getResult());
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builder.create<CondBranchOp>(builder.getUnknownLoc(), comparisonResult,
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loopBodyFirstBlock, postLoopBlock);
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// Finally, make sure building can continue by setting the post-loop block
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// (end of loop SESE region) as the insertion point.
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builder.setInsertionPoint(postLoopBlock);
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}
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// Convert an "if" statement into a flow of basic blocks.
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//
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// Create an SESE region for the if statement (including its "then" and optional
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// "else" statement blocks) and append it to the end of the current region. The
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// conditional region consists of a sequence of condition-checking blocks that
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// implement the short-circuit scheme, followed by a "then" SESE region and an
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// "else" SESE region, and the continuation block that post-dominates all blocks
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// of the "if" statement. The flow of blocks that correspond to the "then" and
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// "else" clauses are constructed recursively, enabling easy nesting of "if"
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// statements and if-then-else-if chains.
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//
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// +--------------------------------+
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// | <end of current SESE region> |
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// | <current insertion point> |
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// | %zero = constant 0 : index |
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// | %v = affine_apply #expr1(%ops) |
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// | %c = cmpi "sge" %v, %zero |
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// | cond_br %c, %next, %else |
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// +--------------------------------+
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// | |
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// | --------------|
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// v |
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// +--------------------------------+ |
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// | next: | |
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// | <repeat the check for expr2> | |
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// | cond_br %c, %next2, %else | |
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// +--------------------------------+ |
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// | | |
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// ... --------------|
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// | <Per-expression checks> |
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// v |
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// +--------------------------------+ |
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// | last: | |
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// | <repeat the check for exprN> | |
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// | cond_br %c, %then, %else | |
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// +--------------------------------+ |
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// | | |
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// | --------------|
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// v |
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// +--------------------------------+ |
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// | then: | |
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// | <then SESE region> | |
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// +--------------------------------+ |
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// | |
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// ... <SESE region of "then"> |
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// | |
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// v |
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// +--------------------------------+ |
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// | then_end: | |
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// | <then SESE region end> | |
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// | br continue | |
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// +--------------------------------+ |
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// | |
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// |---------- |-------------
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// | V
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// | +--------------------------------+
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// | | else: |
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// | | <else SESE region> |
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// | +--------------------------------+
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// | |
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// | ... <SESE region of "else">
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// | |
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// | v
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// | +--------------------------------+
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// | | else_end: |
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// | | <else SESE region> |
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// | | br continue |
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// | +--------------------------------+
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// | |
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// ------| |
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// v v
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// +--------------------------------+
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// | continue: |
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// | <end of "if" SESE region> |
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// | <new insertion point> |
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// +--------------------------------+
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//
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void FunctionConverter::visitIfStmt(IfStmt *ifStmt) {
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assert(ifStmt != nullptr);
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auto integerSet = ifStmt->getCondition().getIntegerSet();
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// Create basic blocks for the 'then' block and for the 'else' block.
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// Although 'else' block may be empty in absence of an 'else' clause, create
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// it anyway for the sake of consistency and output IR readability. Also
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// create extra blocks for condition checking to prepare for short-circuit
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// logic: conditions in the 'if' statement are conjunctive, so we can jump to
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// the false branch as soon as one condition fails. `cond_br` requires
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// another block as a target when the condition is true, and that block will
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// contain the next condition.
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BasicBlock *ifInsertionBlock = builder.getInsertionBlock();
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SmallVector<BasicBlock *, 4> ifConditionExtraBlocks;
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unsigned numConstraints = integerSet.getNumConstraints();
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ifConditionExtraBlocks.reserve(numConstraints - 1);
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for (unsigned i = 0, e = numConstraints - 1; i < e; ++i) {
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ifConditionExtraBlocks.push_back(builder.createBlock());
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}
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BasicBlock *thenBlock = builder.createBlock();
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BasicBlock *elseBlock = builder.createBlock();
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builder.setInsertionPoint(ifInsertionBlock);
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// Implement short-circuit logic. For each affine expression in the 'if'
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// condition, convert it into an affine map and call `affine_apply` to obtain
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// the resulting value. Perform the equality or the greater-than-or-equality
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// test between this value and zero depending on the equality flag of the
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// condition. If the test fails, jump immediately to the false branch, which
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// may be the else block if it is present or the continuation block otherwise.
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// If the test succeeds, jump to the next block testing testing the next
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// conjunct of the condition in the similar way. When all conjuncts have been
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// handled, jump to the 'then' block instead.
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SSAValue *zeroConstant = getConstantIndexValue(0);
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ifConditionExtraBlocks.push_back(thenBlock);
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for (auto tuple :
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llvm::zip(integerSet.getConstraints(), integerSet.getEqFlags(),
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ifConditionExtraBlocks)) {
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AffineExpr constraintExpr = std::get<0>(tuple);
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bool isEquality = std::get<1>(tuple);
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BasicBlock *nextBlock = std::get<2>(tuple);
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// Build and apply an affine map.
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auto affineMap =
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builder.getAffineMap(integerSet.getNumDims(),
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integerSet.getNumSymbols(), constraintExpr, {});
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auto affineApplyOp = builder.create<AffineApplyOp>(
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ifStmt->getLoc(), affineMap, operandsAs(ifStmt, valueRemapping));
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SSAValue *affResult = affineApplyOp->getResult(0);
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// Compare the result of the apply and branch.
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auto comparisonOp = builder.create<CmpIOp>(
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ifStmt->getLoc(), isEquality ? CmpIPredicate::EQ : CmpIPredicate::SGE,
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affResult, zeroConstant);
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builder.create<CondBranchOp>(ifStmt->getLoc(), comparisonOp->getResult(),
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nextBlock, elseBlock);
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builder.setInsertionPoint(nextBlock);
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}
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ifConditionExtraBlocks.pop_back();
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// Recursively traverse the 'then' block.
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builder.setInsertionPoint(thenBlock);
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visitStmtBlock(ifStmt->getThen());
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BasicBlock *lastThenBlock = builder.getInsertionBlock();
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// Recursively traverse the 'else' block if present.
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builder.setInsertionPoint(elseBlock);
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if (ifStmt->hasElse())
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visitStmtBlock(ifStmt->getElse());
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BasicBlock *lastElseBlock = builder.getInsertionBlock();
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// Create the continuation block here so that it appears lexically after the
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// 'then' and 'else' blocks, branch from end of 'then' and 'else' SESE regions
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// to the continuation block.
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BasicBlock *continuationBlock = builder.createBlock();
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builder.setInsertionPoint(lastThenBlock);
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builder.create<BranchOp>(ifStmt->getLoc(), continuationBlock);
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builder.setInsertionPoint(lastElseBlock);
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builder.create<BranchOp>(ifStmt->getLoc(), continuationBlock);
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// Make sure building can continue by setting up the continuation block as the
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// insertion point.
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builder.setInsertionPoint(continuationBlock);
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|
}
|
|
|
|
// Entry point of the function convertor.
|
|
//
|
|
// Conversion is performed by recursively visiting statements of an MLFunction.
|
|
// It reasons in terms of single-entry single-exit (SESE) regions that are not
|
|
// materialized in the code. Instead, the pointer to the last block of the
|
|
// region is maintained throughout the conversion as the insertion point of the
|
|
// IR builder since we never change the first block after its creation. "Block"
|
|
// statements such as loops and branches create new SESE regions for their
|
|
// bodies, and surround them with additional basic blocks for the control flow.
|
|
// Individual operations are simply appended to the end of the last basic block
|
|
// of the current region. The SESE invariant allows us to easily handle nested
|
|
// structures of arbitrary complexity.
|
|
//
|
|
// During the conversion, we maintain a mapping between the MLValues present in
|
|
// the original function and their CFGValue images in the function under
|
|
// construction. When an MLValue is used, it gets replaced with the
|
|
// corresponding CFGValue that has been defined previously. The value flow
|
|
// starts with function arguments converted to basic block arguments.
|
|
CFGFunction *FunctionConverter::convert(MLFunction *mlFunc) {
|
|
auto outerBlock = builder.createBlock();
|
|
|
|
// CFGFunctions do not have explicit arguments but use the arguments to the
|
|
// first basic block instead. Create those from the MLFunction arguments and
|
|
// set up the value remapping.
|
|
outerBlock->addArguments(mlFunc->getType().getInputs());
|
|
assert(mlFunc->getNumArguments() == outerBlock->getNumArguments());
|
|
for (unsigned i = 0, n = mlFunc->getNumArguments(); i < n; ++i) {
|
|
const MLValue *mlArgument = mlFunc->getArgument(i);
|
|
CFGValue *cfgArgument = outerBlock->getArgument(i);
|
|
valueRemapping.insert(std::make_pair(mlArgument, cfgArgument));
|
|
}
|
|
|
|
// Convert statements in order.
|
|
for (auto &stmt : *mlFunc) {
|
|
visit(&stmt);
|
|
}
|
|
|
|
return cfgFunc;
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Module converter
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
namespace {
|
|
// ModuleConverter class does CFG conversion for the whole module.
|
|
class ModuleConverter : public ModulePass {
|
|
public:
|
|
explicit ModuleConverter() : ModulePass(&ModuleConverter::passID) {}
|
|
|
|
PassResult runOnModule(Module *m) override;
|
|
|
|
static char passID;
|
|
|
|
private:
|
|
// Generates CFG functions for all ML functions in the module.
|
|
void convertMLFunctions();
|
|
// Generates CFG function for the given ML function.
|
|
CFGFunction *convert(MLFunction *mlFunc);
|
|
// Replaces all ML function references in the module
|
|
// with references to the generated CFG functions.
|
|
void replaceReferences();
|
|
// Replaces function references in the given function.
|
|
void replaceReferences(CFGFunction *cfgFunc);
|
|
// Replaces MLFunctions with their CFG counterparts in the module.
|
|
void replaceFunctions();
|
|
|
|
// Map from ML functions to generated CFG functions.
|
|
llvm::DenseMap<MLFunction *, CFGFunction *> generatedFuncs;
|
|
Module *module = nullptr;
|
|
};
|
|
} // end anonymous namespace
|
|
|
|
char ModuleConverter::passID = 0;
|
|
|
|
// Iterates over all functions in the module generating CFG functions
|
|
// equivalent to ML functions and replacing references to ML functions
|
|
// with references to the generated ML functions. The names of the converted
|
|
// functions match those of the original functions to avoid breaking any
|
|
// external references to the current module. Therefore, converted functions
|
|
// are added to the module at the end of the pass, after removing the original
|
|
// functions to avoid name clashes. Conversion procedure has access to the
|
|
// module as member of ModuleConverter and must not rely on the converted
|
|
// function to belong to the module.
|
|
PassResult ModuleConverter::runOnModule(Module *m) {
|
|
module = m;
|
|
convertMLFunctions();
|
|
replaceReferences();
|
|
replaceFunctions();
|
|
|
|
return success();
|
|
}
|
|
|
|
void ModuleConverter::convertMLFunctions() {
|
|
for (Function &fn : *module) {
|
|
if (auto *mlFunc = dyn_cast<MLFunction>(&fn))
|
|
generatedFuncs[mlFunc] = convert(mlFunc);
|
|
}
|
|
}
|
|
|
|
// Creates CFG function equivalent to the given ML function.
|
|
CFGFunction *ModuleConverter::convert(MLFunction *mlFunc) {
|
|
// Use the same name as for ML function; do not add the converted function to
|
|
// the module yet to avoid collision.
|
|
auto name = mlFunc->getName().str();
|
|
auto *cfgFunc = new CFGFunction(mlFunc->getLoc(), name, mlFunc->getType(),
|
|
mlFunc->getAttrs());
|
|
|
|
// Generates the body of the CFG function.
|
|
return FunctionConverter(cfgFunc).convert(mlFunc);
|
|
}
|
|
|
|
// Replace references to MLFunctions with the references to the converted
|
|
// CFGFunctions. Since this all MLFunctions are converted at this point, it is
|
|
// unnecessary to replace references in the MLFunctions that are going to be
|
|
// removed anyway. However, it is necessary to replace the references in the
|
|
// converted CFGFunctions that have not been added to the module yet.
|
|
void ModuleConverter::replaceReferences() {
|
|
// Build the remapping between function attributes pointing to ML functions
|
|
// and the newly created function attributes pointing to the converted CFG
|
|
// functions.
|
|
llvm::DenseMap<Attribute, FunctionAttr> remappingTable;
|
|
for (const Function &fn : *module) {
|
|
const auto *mlFunc = dyn_cast<MLFunction>(&fn);
|
|
if (!mlFunc)
|
|
continue;
|
|
CFGFunction *convertedFunc = generatedFuncs.lookup(mlFunc);
|
|
assert(convertedFunc && "ML function was not converted");
|
|
|
|
MLIRContext *context = module->getContext();
|
|
auto mlFuncAttr = FunctionAttr::get(mlFunc, context);
|
|
auto cfgFuncAttr = FunctionAttr::get(convertedFunc, module->getContext());
|
|
remappingTable.insert({mlFuncAttr, cfgFuncAttr});
|
|
}
|
|
|
|
// Remap in existing functions.
|
|
remapFunctionAttrs(*module, remappingTable);
|
|
|
|
// Remap in generated functions.
|
|
for (auto pair : generatedFuncs) {
|
|
remapFunctionAttrs(*pair.second, remappingTable);
|
|
}
|
|
}
|
|
|
|
// Replace the value of a function attribute named "name" attached to the
|
|
// operation "op" and containing an MLFunction-typed value with the result of
|
|
// converting "func" to a CFGFunction.
|
|
static inline void replaceMLFunctionAttr(
|
|
Operation &op, Identifier name, const Function *func,
|
|
const llvm::DenseMap<MLFunction *, CFGFunction *> &generatedFuncs) {
|
|
const auto *mlFunc = dyn_cast<MLFunction>(func);
|
|
if (!mlFunc)
|
|
return;
|
|
|
|
Builder b(op.getContext());
|
|
auto cfgFunc = generatedFuncs.lookup(mlFunc);
|
|
op.setAttr(name, b.getFunctionAttr(cfgFunc));
|
|
}
|
|
|
|
// The CFG and ML functions have the same name. First, erase the MLFunction.
|
|
// Then insert the CFGFunction at the same place.
|
|
void ModuleConverter::replaceFunctions() {
|
|
for (auto pair : generatedFuncs) {
|
|
auto &functions = module->getFunctions();
|
|
auto it = functions.erase(pair.first);
|
|
functions.insert(it, pair.second);
|
|
}
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Entry point method
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// Replaces all ML functions in the module with equivalent CFG functions.
|
|
/// Function references are appropriately patched to refer to the newly
|
|
/// generated CFG functions. Converted functions have the same names as the
|
|
/// original functions to preserve module linking.
|
|
ModulePass *mlir::createConvertToCFGPass() { return new ModuleConverter(); }
|
|
|
|
static PassRegistration<ModuleConverter>
|
|
pass("convert-to-cfg",
|
|
"Convert all ML functions in the module to CFG ones");
|