forked from OSchip/llvm-project
495 lines
17 KiB
C++
495 lines
17 KiB
C++
//===- AffineMap.cpp - MLIR Affine Map Classes ----------------------------===//
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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/IR/AffineMap.h"
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#include "AffineMapDetail.h"
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#include "mlir/IR/Attributes.h"
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#include "mlir/IR/StandardTypes.h"
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#include "mlir/Support/LogicalResult.h"
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#include "mlir/Support/MathExtras.h"
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#include "llvm/ADT/StringRef.h"
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#include "llvm/Support/raw_ostream.h"
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using namespace mlir;
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namespace {
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// AffineExprConstantFolder evaluates an affine expression using constant
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// operands passed in 'operandConsts'. Returns an IntegerAttr attribute
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// representing the constant value of the affine expression evaluated on
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// constant 'operandConsts', or nullptr if it can't be folded.
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class AffineExprConstantFolder {
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public:
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AffineExprConstantFolder(unsigned numDims, ArrayRef<Attribute> operandConsts)
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: numDims(numDims), operandConsts(operandConsts) {}
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/// Attempt to constant fold the specified affine expr, or return null on
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/// failure.
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IntegerAttr constantFold(AffineExpr expr) {
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if (auto result = constantFoldImpl(expr))
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return IntegerAttr::get(IndexType::get(expr.getContext()), *result);
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return nullptr;
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}
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private:
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Optional<int64_t> constantFoldImpl(AffineExpr expr) {
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switch (expr.getKind()) {
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case AffineExprKind::Add:
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return constantFoldBinExpr(
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expr, [](int64_t lhs, int64_t rhs) { return lhs + rhs; });
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case AffineExprKind::Mul:
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return constantFoldBinExpr(
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expr, [](int64_t lhs, int64_t rhs) { return lhs * rhs; });
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case AffineExprKind::Mod:
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return constantFoldBinExpr(
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expr, [](int64_t lhs, int64_t rhs) { return mod(lhs, rhs); });
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case AffineExprKind::FloorDiv:
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return constantFoldBinExpr(
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expr, [](int64_t lhs, int64_t rhs) { return floorDiv(lhs, rhs); });
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case AffineExprKind::CeilDiv:
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return constantFoldBinExpr(
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expr, [](int64_t lhs, int64_t rhs) { return ceilDiv(lhs, rhs); });
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case AffineExprKind::Constant:
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return expr.cast<AffineConstantExpr>().getValue();
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case AffineExprKind::DimId:
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if (auto attr = operandConsts[expr.cast<AffineDimExpr>().getPosition()]
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.dyn_cast_or_null<IntegerAttr>())
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return attr.getInt();
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return llvm::None;
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case AffineExprKind::SymbolId:
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if (auto attr = operandConsts[numDims +
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expr.cast<AffineSymbolExpr>().getPosition()]
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.dyn_cast_or_null<IntegerAttr>())
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return attr.getInt();
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return llvm::None;
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}
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llvm_unreachable("Unknown AffineExpr");
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}
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// TODO: Change these to operate on APInts too.
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Optional<int64_t> constantFoldBinExpr(AffineExpr expr,
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int64_t (*op)(int64_t, int64_t)) {
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auto binOpExpr = expr.cast<AffineBinaryOpExpr>();
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if (auto lhs = constantFoldImpl(binOpExpr.getLHS()))
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if (auto rhs = constantFoldImpl(binOpExpr.getRHS()))
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return op(*lhs, *rhs);
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return llvm::None;
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}
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// The number of dimension operands in AffineMap containing this expression.
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unsigned numDims;
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// The constant valued operands used to evaluate this AffineExpr.
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ArrayRef<Attribute> operandConsts;
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};
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} // end anonymous namespace
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/// Returns a single constant result affine map.
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AffineMap AffineMap::getConstantMap(int64_t val, MLIRContext *context) {
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return get(/*dimCount=*/0, /*symbolCount=*/0,
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{getAffineConstantExpr(val, context)});
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}
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/// Returns an identity affine map (d0, ..., dn) -> (dp, ..., dn) on the most
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/// minor dimensions.
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AffineMap AffineMap::getMinorIdentityMap(unsigned dims, unsigned results,
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MLIRContext *context) {
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assert(dims >= results && "Dimension mismatch");
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auto id = AffineMap::getMultiDimIdentityMap(dims, context);
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return AffineMap::get(dims, 0, id.getResults().take_back(results), context);
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}
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bool AffineMap::isMinorIdentity() const {
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return *this ==
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getMinorIdentityMap(getNumDims(), getNumResults(), getContext());
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}
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/// Returns an AffineMap representing a permutation.
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AffineMap AffineMap::getPermutationMap(ArrayRef<unsigned> permutation,
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MLIRContext *context) {
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assert(!permutation.empty() &&
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"Cannot create permutation map from empty permutation vector");
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SmallVector<AffineExpr, 4> affExprs;
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for (auto index : permutation)
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affExprs.push_back(getAffineDimExpr(index, context));
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auto m = std::max_element(permutation.begin(), permutation.end());
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auto permutationMap = AffineMap::get(*m + 1, 0, affExprs, context);
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assert(permutationMap.isPermutation() && "Invalid permutation vector");
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return permutationMap;
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}
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template <typename AffineExprContainer>
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static void getMaxDimAndSymbol(ArrayRef<AffineExprContainer> exprsList,
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int64_t &maxDim, int64_t &maxSym) {
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for (const auto &exprs : exprsList) {
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for (auto expr : exprs) {
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expr.walk([&maxDim, &maxSym](AffineExpr e) {
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if (auto d = e.dyn_cast<AffineDimExpr>())
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maxDim = std::max(maxDim, static_cast<int64_t>(d.getPosition()));
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if (auto s = e.dyn_cast<AffineSymbolExpr>())
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maxSym = std::max(maxSym, static_cast<int64_t>(s.getPosition()));
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});
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}
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}
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}
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template <typename AffineExprContainer>
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static SmallVector<AffineMap, 4>
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inferFromExprList(ArrayRef<AffineExprContainer> exprsList) {
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assert(!exprsList.empty());
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assert(!exprsList[0].empty());
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auto context = exprsList[0][0].getContext();
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int64_t maxDim = -1, maxSym = -1;
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getMaxDimAndSymbol(exprsList, maxDim, maxSym);
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SmallVector<AffineMap, 4> maps;
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maps.reserve(exprsList.size());
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for (const auto &exprs : exprsList)
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maps.push_back(AffineMap::get(/*dimCount=*/maxDim + 1,
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/*symbolCount=*/maxSym + 1, exprs, context));
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return maps;
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}
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SmallVector<AffineMap, 4>
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AffineMap::inferFromExprList(ArrayRef<ArrayRef<AffineExpr>> exprsList) {
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return ::inferFromExprList(exprsList);
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}
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SmallVector<AffineMap, 4>
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AffineMap::inferFromExprList(ArrayRef<SmallVector<AffineExpr, 4>> exprsList) {
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return ::inferFromExprList(exprsList);
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}
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AffineMap AffineMap::getMultiDimIdentityMap(unsigned numDims,
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MLIRContext *context) {
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SmallVector<AffineExpr, 4> dimExprs;
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dimExprs.reserve(numDims);
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for (unsigned i = 0; i < numDims; ++i)
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dimExprs.push_back(mlir::getAffineDimExpr(i, context));
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return get(/*dimCount=*/numDims, /*symbolCount=*/0, dimExprs, context);
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}
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MLIRContext *AffineMap::getContext() const { return map->context; }
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bool AffineMap::isIdentity() const {
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if (getNumDims() != getNumResults())
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return false;
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ArrayRef<AffineExpr> results = getResults();
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for (unsigned i = 0, numDims = getNumDims(); i < numDims; ++i) {
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auto expr = results[i].dyn_cast<AffineDimExpr>();
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if (!expr || expr.getPosition() != i)
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return false;
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}
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return true;
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}
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bool AffineMap::isEmpty() const {
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return getNumDims() == 0 && getNumSymbols() == 0 && getNumResults() == 0;
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}
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bool AffineMap::isSingleConstant() const {
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return getNumResults() == 1 && getResult(0).isa<AffineConstantExpr>();
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}
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int64_t AffineMap::getSingleConstantResult() const {
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assert(isSingleConstant() && "map must have a single constant result");
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return getResult(0).cast<AffineConstantExpr>().getValue();
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}
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unsigned AffineMap::getNumDims() const {
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assert(map && "uninitialized map storage");
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return map->numDims;
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}
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unsigned AffineMap::getNumSymbols() const {
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assert(map && "uninitialized map storage");
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return map->numSymbols;
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}
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unsigned AffineMap::getNumResults() const {
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assert(map && "uninitialized map storage");
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return map->results.size();
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}
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unsigned AffineMap::getNumInputs() const {
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assert(map && "uninitialized map storage");
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return map->numDims + map->numSymbols;
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}
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ArrayRef<AffineExpr> AffineMap::getResults() const {
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assert(map && "uninitialized map storage");
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return map->results;
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}
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AffineExpr AffineMap::getResult(unsigned idx) const {
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assert(map && "uninitialized map storage");
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return map->results[idx];
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}
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/// Folds the results of the application of an affine map on the provided
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/// operands to a constant if possible. Returns false if the folding happens,
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/// true otherwise.
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LogicalResult
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AffineMap::constantFold(ArrayRef<Attribute> operandConstants,
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SmallVectorImpl<Attribute> &results) const {
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// Attempt partial folding.
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SmallVector<int64_t, 2> integers;
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partialConstantFold(operandConstants, &integers);
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// If all expressions folded to a constant, populate results with attributes
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// containing those constants.
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if (integers.empty())
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return failure();
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auto range = llvm::map_range(integers, [this](int64_t i) {
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return IntegerAttr::get(IndexType::get(getContext()), i);
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});
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results.append(range.begin(), range.end());
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return success();
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}
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AffineMap
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AffineMap::partialConstantFold(ArrayRef<Attribute> operandConstants,
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SmallVectorImpl<int64_t> *results) const {
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assert(getNumInputs() == operandConstants.size());
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// Fold each of the result expressions.
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AffineExprConstantFolder exprFolder(getNumDims(), operandConstants);
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SmallVector<AffineExpr, 4> exprs;
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exprs.reserve(getNumResults());
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for (auto expr : getResults()) {
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auto folded = exprFolder.constantFold(expr);
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// If did not fold to a constant, keep the original expression, and clear
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// the integer results vector.
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if (folded) {
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exprs.push_back(
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getAffineConstantExpr(folded.getInt(), folded.getContext()));
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if (results)
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results->push_back(folded.getInt());
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} else {
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exprs.push_back(expr);
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if (results) {
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results->clear();
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results = nullptr;
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}
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}
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}
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return get(getNumDims(), getNumSymbols(), exprs, getContext());
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}
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/// Walk all of the AffineExpr's in this mapping. Each node in an expression
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/// tree is visited in postorder.
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void AffineMap::walkExprs(std::function<void(AffineExpr)> callback) const {
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for (auto expr : getResults())
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expr.walk(callback);
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}
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/// This method substitutes any uses of dimensions and symbols (e.g.
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/// dim#0 with dimReplacements[0]) in subexpressions and returns the modified
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/// expression mapping. Because this can be used to eliminate dims and
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/// symbols, the client needs to specify the number of dims and symbols in
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/// the result. The returned map always has the same number of results.
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AffineMap AffineMap::replaceDimsAndSymbols(ArrayRef<AffineExpr> dimReplacements,
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ArrayRef<AffineExpr> symReplacements,
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unsigned numResultDims,
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unsigned numResultSyms) const {
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SmallVector<AffineExpr, 8> results;
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results.reserve(getNumResults());
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for (auto expr : getResults())
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results.push_back(
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expr.replaceDimsAndSymbols(dimReplacements, symReplacements));
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return get(numResultDims, numResultSyms, results, getContext());
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}
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AffineMap AffineMap::compose(AffineMap map) {
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assert(getNumDims() == map.getNumResults() && "Number of results mismatch");
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// Prepare `map` by concatenating the symbols and rewriting its exprs.
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unsigned numDims = map.getNumDims();
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unsigned numSymbolsThisMap = getNumSymbols();
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unsigned numSymbols = numSymbolsThisMap + map.getNumSymbols();
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SmallVector<AffineExpr, 8> newDims(numDims);
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for (unsigned idx = 0; idx < numDims; ++idx) {
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newDims[idx] = getAffineDimExpr(idx, getContext());
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}
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SmallVector<AffineExpr, 8> newSymbols(numSymbols);
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for (unsigned idx = numSymbolsThisMap; idx < numSymbols; ++idx) {
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newSymbols[idx - numSymbolsThisMap] =
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getAffineSymbolExpr(idx, getContext());
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}
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auto newMap =
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map.replaceDimsAndSymbols(newDims, newSymbols, numDims, numSymbols);
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SmallVector<AffineExpr, 8> exprs;
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exprs.reserve(getResults().size());
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for (auto expr : getResults())
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exprs.push_back(expr.compose(newMap));
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return AffineMap::get(numDims, numSymbols, exprs, map.getContext());
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}
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SmallVector<int64_t, 4> AffineMap::compose(ArrayRef<int64_t> values) {
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assert(getNumSymbols() == 0 && "Expected symbol-less map");
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SmallVector<AffineExpr, 4> exprs;
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exprs.reserve(values.size());
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MLIRContext *ctx = getContext();
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for (auto v : values)
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exprs.push_back(getAffineConstantExpr(v, ctx));
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auto resMap = compose(AffineMap::get(0, 0, exprs, ctx));
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SmallVector<int64_t, 4> res;
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res.reserve(resMap.getNumResults());
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for (auto e : resMap.getResults())
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res.push_back(e.cast<AffineConstantExpr>().getValue());
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return res;
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}
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bool AffineMap::isProjectedPermutation() {
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if (getNumSymbols() > 0)
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return false;
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SmallVector<bool, 8> seen(getNumInputs(), false);
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for (auto expr : getResults()) {
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if (auto dim = expr.dyn_cast<AffineDimExpr>()) {
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if (seen[dim.getPosition()])
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return false;
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seen[dim.getPosition()] = true;
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continue;
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}
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return false;
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}
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return true;
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}
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bool AffineMap::isPermutation() {
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if (getNumDims() != getNumResults())
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return false;
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return isProjectedPermutation();
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}
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AffineMap AffineMap::getSubMap(ArrayRef<unsigned> resultPos) {
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SmallVector<AffineExpr, 4> exprs;
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exprs.reserve(resultPos.size());
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for (auto idx : resultPos)
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exprs.push_back(getResult(idx));
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return AffineMap::get(getNumDims(), getNumSymbols(), exprs, getContext());
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}
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AffineMap AffineMap::getMajorSubMap(unsigned numResults) {
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if (numResults == 0)
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return AffineMap();
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if (numResults > getNumResults())
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return *this;
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return getSubMap(llvm::to_vector<4>(llvm::seq<unsigned>(0, numResults)));
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}
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AffineMap AffineMap::getMinorSubMap(unsigned numResults) {
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if (numResults == 0)
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return AffineMap();
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if (numResults > getNumResults())
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return *this;
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return getSubMap(llvm::to_vector<4>(
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llvm::seq<unsigned>(getNumResults() - numResults, getNumResults())));
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}
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AffineMap mlir::simplifyAffineMap(AffineMap map) {
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SmallVector<AffineExpr, 8> exprs;
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for (auto e : map.getResults()) {
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exprs.push_back(
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simplifyAffineExpr(e, map.getNumDims(), map.getNumSymbols()));
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}
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return AffineMap::get(map.getNumDims(), map.getNumSymbols(), exprs,
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map.getContext());
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}
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AffineMap mlir::removeDuplicateExprs(AffineMap map) {
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auto results = map.getResults();
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SmallVector<AffineExpr, 4> uniqueExprs(results.begin(), results.end());
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uniqueExprs.erase(std::unique(uniqueExprs.begin(), uniqueExprs.end()),
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uniqueExprs.end());
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return AffineMap::get(map.getNumDims(), map.getNumSymbols(), uniqueExprs,
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map.getContext());
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}
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AffineMap mlir::inversePermutation(AffineMap map) {
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if (map.isEmpty())
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return map;
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assert(map.getNumSymbols() == 0 && "expected map without symbols");
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SmallVector<AffineExpr, 4> exprs(map.getNumDims());
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for (auto en : llvm::enumerate(map.getResults())) {
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auto expr = en.value();
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// Skip non-permutations.
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if (auto d = expr.dyn_cast<AffineDimExpr>()) {
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if (exprs[d.getPosition()])
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continue;
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exprs[d.getPosition()] = getAffineDimExpr(en.index(), d.getContext());
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}
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}
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SmallVector<AffineExpr, 4> seenExprs;
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seenExprs.reserve(map.getNumDims());
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for (auto expr : exprs)
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if (expr)
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seenExprs.push_back(expr);
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if (seenExprs.size() != map.getNumInputs())
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return AffineMap();
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return AffineMap::get(map.getNumResults(), 0, seenExprs, map.getContext());
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}
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AffineMap mlir::concatAffineMaps(ArrayRef<AffineMap> maps) {
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unsigned numResults = 0, numDims = 0, numSymbols = 0;
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for (auto m : maps)
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numResults += m.getNumResults();
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SmallVector<AffineExpr, 8> results;
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results.reserve(numResults);
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for (auto m : maps) {
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for (auto res : m.getResults())
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results.push_back(res.shiftSymbols(m.getNumSymbols(), numSymbols));
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numSymbols += m.getNumSymbols();
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numDims = std::max(m.getNumDims(), numDims);
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}
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return AffineMap::get(numDims, numSymbols, results,
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maps.front().getContext());
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}
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//===----------------------------------------------------------------------===//
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// MutableAffineMap.
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//===----------------------------------------------------------------------===//
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MutableAffineMap::MutableAffineMap(AffineMap map)
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: numDims(map.getNumDims()), numSymbols(map.getNumSymbols()),
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context(map.getContext()) {
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for (auto result : map.getResults())
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results.push_back(result);
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}
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void MutableAffineMap::reset(AffineMap map) {
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results.clear();
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numDims = map.getNumDims();
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numSymbols = map.getNumSymbols();
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context = map.getContext();
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for (auto result : map.getResults())
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results.push_back(result);
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}
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|
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bool MutableAffineMap::isMultipleOf(unsigned idx, int64_t factor) const {
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|
if (results[idx].isMultipleOf(factor))
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|
return true;
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|
|
|
// TODO: use simplifyAffineExpr and FlatAffineConstraints to
|
|
// complete this (for a more powerful analysis).
|
|
return false;
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|
}
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|
|
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// Simplifies the result affine expressions of this map. The expressions have to
|
|
// be pure for the simplification implemented.
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|
void MutableAffineMap::simplify() {
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|
// Simplify each of the results if possible.
|
|
// TODO: functional-style map
|
|
for (unsigned i = 0, e = getNumResults(); i < e; i++) {
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|
results[i] = simplifyAffineExpr(getResult(i), numDims, numSymbols);
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|
}
|
|
}
|
|
|
|
AffineMap MutableAffineMap::getAffineMap() const {
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|
return AffineMap::get(numDims, numSymbols, results, context);
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}
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