[mlir][Analysis][NFC] Make BoundType a top-level enum

[springerm]

Summary

BoundType is no longer a nested member of IntegerRelation but a top-level enum in the presburger namespace.

This allows BoundType to be predeclared in header files. Nested members cannot be predeclared.

Depends On: D146201

[springerm]

update

[springerm]

rebase

[springerm]

rebase

mlir/include/mlir/Analysis/FlatLinearValueConstraints.h

public:
   ///
   /// The bound can be added as open or closed by specifying isClosedBound. In
   /// case of a LB/UB, isClosedBound = false means the bound is added internally
   /// as a closed bound by +1/-1 respectively. In case of an EQ bound, it can
   /// only be added as a closed bound.
   ///
   /// Note: The dimensions/symbols of this FlatLinearConstraints must match the
   /// dimensions/symbols of the affine map.
-  LogicalResult addBound(BoundType type, unsigned pos, AffineMap boundMap,
-                         bool isClosedBound);
+  LogicalResult addBound(presburger::BoundType type, unsigned pos,
+                         AffineMap boundMap, bool isClosedBound);
 
   /// Adds a bound for the variable at the specified position with constraints
   /// being drawn from the specified bound map. In case of an EQ bound, the
   /// bound map is expected to have exactly one result. In case of a LB/UB, the
   /// bound map may have more than one result, for each of which an inequality
   /// is added.
   /// Note: The dimensions/symbols of this FlatLinearConstraints must match the
   /// dimensions/symbols of the affine map. By default the lower bound is closed
   /// and the upper bound is open.
-  LogicalResult addBound(BoundType type, unsigned pos, AffineMap boundMap);
+  LogicalResult addBound(presburger::BoundType type, unsigned pos,
+                         AffineMap boundMap);
 
   /// The `addBound` overload above hides the inherited overloads by default, so
   /// we explicitly introduce them here.
   using IntegerPolyhedron::addBound;
 
   /// Returns the constraint system as an integer set. Returns a null integer
   /// set if the system has no constraints, or if an integer set couldn't be
   /// constructed as a result of a local variable's explicit representation not
static bool classof(const IntegerRelation *cst) {
     return cst->getKind() >= Kind::FlatLinearValueConstraints &&
            cst->getKind() <= Kind::FlatAffineRelation;
   }
 
   /// Replaces the contents of this FlatLinearValueConstraints with `other`.
   void clearAndCopyFrom(const IntegerRelation &other) override;
 
   /// Adds a constant bound for the variable associated with the given Value.
-  void addBound(BoundType type, Value val, int64_t value);
+  void addBound(presburger::BoundType type, Value val, int64_t value);
   using FlatLinearConstraints::addBound;
 
   /// Returns the Value associated with the pos^th variable. Asserts if
   /// no Value variable was associated.
   inline Value getValue(unsigned pos) const {
     assert(pos < getNumDimAndSymbolVars() && "Invalid position");
     assert(hasValue(pos) && "variable's Value not set");
     return *values[pos];

mlir/include/mlir/Analysis/Presburger/IntegerRelation.h

 namespace presburger {
 
 class IntegerRelation;
 class IntegerPolyhedron;
 class PresburgerSet;
 class PresburgerRelation;
 struct SymbolicLexMin;
 
+/// The type of bound: equal, lower bound or upper bound.
+enum class BoundType { EQ, LB, UB };
+
 /// An IntegerRelation represents the set of points from a PresburgerSpace that
 /// satisfy a list of affine constraints. Affine constraints can be inequalities
 /// or equalities in the form:
 ///
 /// Inequality: c_0*x_0 + c_1*x_1 + .... + c_{n-1}*x_{n-1} + c_n >= 0
 /// Equality  : c_0*x_0 + c_1*x_1 + .... + c_{n-1}*x_{n-1} + c_n == 0
 ///
 /// where c_0, c_1, ..., c_n are integers and n is the total number of
public:
   /// If `repr` is not `nullptr`, the equality and pairs of inequality
   /// constraints identified by their position indices using which an explicit
   /// representation for each local variable can be computed are set in `repr`
   /// in the form of a `MaybeLocalRepr` struct. If no such inequality
   /// pair/equality can be found, the kind attribute in `MaybeLocalRepr` is set
   /// to None.
   DivisionRepr getLocalReprs(std::vector<MaybeLocalRepr> *repr = nullptr) const;
 
-  /// The type of bound: equal, lower bound or upper bound.
-  enum BoundType { EQ, LB, UB };
-
   /// Adds a constant bound for the specified variable.
   void addBound(BoundType type, unsigned pos, const MPInt &value);
   void addBound(BoundType type, unsigned pos, int64_t value) {
     addBound(type, pos, MPInt(value));
   }
 
   /// Adds a constant bound for the specified expression.
   void addBound(BoundType type, ArrayRef<MPInt> expr, const MPInt &value);

mlir/include/mlir/Dialect/Affine/Analysis/AffineStructures.h

public:
   /// the columns in the current one regarding numbers and values.
   void addAffineIfOpDomain(AffineIfOp ifOp);
 
   /// Adds a bound for the variable at the specified position with constraints
   /// being drawn from the specified bound map and operands. In case of an
   /// EQ bound, the  bound map is expected to have exactly one result. In case
   /// of a LB/UB, the bound map may have more than one result, for each of which
   /// an inequality is added.
-  LogicalResult addBound(BoundType type, unsigned pos, AffineMap boundMap,
-                         ValueRange operands);
+  LogicalResult addBound(presburger::BoundType type, unsigned pos,
+                         AffineMap boundMap, ValueRange operands);
   using FlatLinearValueConstraints::addBound;
 
   /// Add the specified values as a dim or symbol var depending on its nature,
   /// if it already doesn't exist in the system. `val` has to be either a
   /// terminal symbol or a loop IV, i.e., it cannot be the result affine.apply
   /// of any symbols or loop IVs. The variable is added to the end of the
   /// existing dims or symbols. Additional information on the variable is
   /// extracted from the IR and added to the constraint system.

mlir/lib/Analysis/FlatLinearValueConstraints.cpp

for (unsigned curEquality = 0, numEqualities = cst.getNumEqualities();
     // TODO: Handle AffineSymbolExpr as well. There is no reason to restrict it
     // to dims themselves.
     auto dimExpr = dividendExpr.dyn_cast<AffineDimExpr>();
     if (!dimExpr)
       continue;
 
     // Express `var_r` as `var_n % divisor` and store the expression in `memo`.
     if (quotientCount >= 1) {
-      auto ub = cst.getConstantBound64(FlatLinearConstraints::BoundType::UB,
-                                       dimExpr.getPosition());
+      auto ub = cst.getConstantBound64(BoundType::UB, dimExpr.getPosition());
       // If `var_n` has an upperbound that is less than the divisor, mod can be
       // eliminated altogether.
       if (ub && *ub < divisor)
         memo[pos] = dimExpr;
       else
         memo[pos] = dimExpr % divisor;
       // If a unique quotient `var_q` was seen, it can be expressed as
       // `var_n floordiv divisor`.

mlir/lib/Analysis/Presburger/PWMAFunction.cpp

for (unsigned level = 0; level < funcA.getNumOutputs(); ++level) {
 
     // TODO: Implement all comparison cases.
     switch (comp) {
     case OrderingKind::LT:
       // For less than, we add an upper bound of -1:
       //        outA - outB <= -1
       //        outA <= outB - 1
       //        outA < outB
-      levelSet.addBound(IntegerPolyhedron::BoundType::UB, subExpr, MPInt(-1));
+      levelSet.addBound(BoundType::UB, subExpr, MPInt(-1));
       break;
     case OrderingKind::GT:
       // For greater than, we add a lower bound of 1:
       //        outA - outB >= 1
       //        outA > outB + 1
       //        outA > outB
-      levelSet.addBound(IntegerPolyhedron::BoundType::LB, subExpr, MPInt(1));
+      levelSet.addBound(BoundType::LB, subExpr, MPInt(1));
       break;
     case OrderingKind::GE:
     case OrderingKind::LE:
     case OrderingKind::EQ:
     case OrderingKind::NE:
       assert(false && "Not implemented case");
     }
 

mlir/lib/Dialect/Affine/Analysis/AffineAnalysis.cpp

static void computeDirectionVector(
   // Eliminate all variables other than the direction variables just added.
   dependenceDomain->projectOut(numCommonLoops, numIdsToEliminate);
 
   // Scan each common loop variable column and set direction vectors based
   // on eliminated constraint system.
   dependenceComponents->resize(numCommonLoops);
   for (unsigned j = 0; j < numCommonLoops; ++j) {
     (*dependenceComponents)[j].op = commonLoops[j].getOperation();
-    auto lbConst =
-        dependenceDomain->getConstantBound64(IntegerPolyhedron::LB, j);
+    auto lbConst = dependenceDomain->getConstantBound64(BoundType::LB, j);
     (*dependenceComponents)[j].lb =
         lbConst.value_or(std::numeric_limits<int64_t>::min());
-    auto ubConst =
-        dependenceDomain->getConstantBound64(IntegerPolyhedron::UB, j);
+    auto ubConst = dependenceDomain->getConstantBound64(BoundType::UB, j);
     (*dependenceComponents)[j].ub =
         ubConst.value_or(std::numeric_limits<int64_t>::max());
   }
 }
 
 LogicalResult MemRefAccess::getAccessRelation(FlatAffineRelation &rel) const {
   // Create set corresponding to domain of access.
   FlatAffineValueConstraints domain;

mlir/lib/Dialect/Affine/Analysis/Utils.cpp

ComputationSliceState::getAsConstraints(FlatAffineValueConstraints *cst) {
   // Add loop bound constraints for values which are loop IVs of the destination
   // of fusion and equality constraints for symbols which are constants.
   for (unsigned i = numDims, end = values.size(); i < end; ++i) {
     Value value = values[i];
     assert(cst->containsVar(value) && "value expected to be present");
     if (isValidSymbol(value)) {
       // Check if the symbol is a constant.
       if (auto cOp = value.getDefiningOp<arith::ConstantIndexOp>())
-        cst->addBound(FlatAffineValueConstraints::EQ, value, cOp.value());
+        cst->addBound(BoundType::EQ, value, cOp.value());
     } else if (auto loop = getForInductionVarOwner(value)) {
       if (failed(cst->addAffineForOpDomain(loop)))
         return failure();
     }
   }
 
   // Add slices bounds on 'ivs' using maps 'lbs'/'ubs' with 'lbOperands[0]'
   LogicalResult ret = cst->addSliceBounds(ivs, lbs, ubs, lbOperands[0]);
std::optional<int64_t> MemRefRegion::getConstantBoundingSizeAndShape(
 
   // Use a copy of the region constraints that has upper/lower bounds for each
   // memref dimension with static size added to guard against potential
   // over-approximation from projection or union bounding box. We may not add
   // this on the region itself since they might just be redundant constraints
   // that will need non-trivials means to eliminate.
   FlatAffineValueConstraints cstWithShapeBounds(cst);
   for (unsigned r = 0; r < rank; r++) {
-    cstWithShapeBounds.addBound(FlatAffineValueConstraints::LB, r, 0);
+    cstWithShapeBounds.addBound(BoundType::LB, r, 0);
     int64_t dimSize = memRefType.getDimSize(r);
     if (ShapedType::isDynamic(dimSize))
       continue;
-    cstWithShapeBounds.addBound(FlatAffineValueConstraints::UB, r, dimSize - 1);
+    cstWithShapeBounds.addBound(BoundType::UB, r, dimSize - 1);
   }
 
   // Find a constant upper bound on the extent of this memref region along each
   // dimension.
   int64_t numElements = 1;
   int64_t diffConstant;
   int64_t lbDivisor;
   for (unsigned d = 0; d < rank; d++) {
if (auto affineFor = getForInductionVarOwner(operand)) {
         return failure();
     } else if (auto parallelOp = getAffineParallelInductionVarOwner(operand)) {
       if (failed(cst.addAffineParallelOpDomain(parallelOp)))
         return failure();
     } else if (isValidSymbol(operand)) {
       // Check if the symbol is a constant.
       Value symbol = operand;
       if (auto constVal = getConstantIntValue(symbol))
-        cst.addBound(FlatAffineValueConstraints::EQ, symbol, constVal.value());
+        cst.addBound(BoundType::EQ, symbol, constVal.value());
     } else {
       LLVM_DEBUG(llvm::dbgs() << "unknown affine dimensional value");
       return failure();
     }
   }
 
   // Add lower/upper bounds on loop IVs using bounds from 'sliceState'.
   if (sliceState != nullptr) {
LogicalResult MemRefRegion::compute(Operation *op, unsigned loopDepth,
   assert(cst.getNumDimVars() == rank && "unexpected MemRefRegion format");
 
   // Add upper/lower bounds for each memref dimension with static size
   // to guard against potential over-approximation from projection.
   // TODO: Support dynamic memref dimensions.
   if (addMemRefDimBounds) {
     auto memRefType = memref.getType().cast<MemRefType>();
     for (unsigned r = 0; r < rank; r++) {
-      cst.addBound(FlatAffineValueConstraints::LB, /*pos=*/r, /*value=*/0);
+      cst.addBound(BoundType::LB, /*pos=*/r, /*value=*/0);
       if (memRefType.isDynamicDim(r))
         continue;
-      cst.addBound(FlatAffineValueConstraints::UB, /*pos=*/r,
-                   memRefType.getDimSize(r) - 1);
+      cst.addBound(BoundType::UB, /*pos=*/r, memRefType.getDimSize(r) - 1);
     }
   }
   cst.removeTrivialRedundancy();
 
   LLVM_DEBUG(llvm::dbgs() << "Memory region:\n");
   LLVM_DEBUG(cst.dump());
   return success();
 }
for (unsigned r = 0; r < rank; r++) {
     // feasible. If it is, there is at least one point out of bounds.
     SmallVector<int64_t, 4> ineq(rank + 1, 0);
     int64_t dimSize = loadOrStoreOp.getMemRefType().getDimSize(r);
     // TODO: handle dynamic dim sizes.
     if (dimSize == -1)
       continue;
 
     // Check for overflow: d_i >= memref dim size.
-    ucst.addBound(FlatAffineValueConstraints::LB, r, dimSize);
+    ucst.addBound(BoundType::LB, r, dimSize);
     outOfBounds = !ucst.isEmpty();
     if (outOfBounds && emitError) {
       loadOrStoreOp.emitOpError()
           << "memref out of upper bound access along dimension #" << (r + 1);
     }
 
     // Check for a negative index.
     FlatAffineValueConstraints lcst(*region.getConstraints());
     std::fill(ineq.begin(), ineq.end(), 0);
     // d_i <= -1;
-    lcst.addBound(FlatAffineValueConstraints::UB, r, -1);
+    lcst.addBound(BoundType::UB, r, -1);
     outOfBounds = !lcst.isEmpty();
     if (outOfBounds && emitError) {
       loadOrStoreOp.emitOpError()
           << "memref out of lower bound access along dimension #" << (r + 1);
     }
   }
   return failure(outOfBounds);
 }

 
 /// Bound an identifier `pos` in a given FlatAffineValueConstraints with
 /// constraints drawn from an affine map. Before adding the constraint, the
 /// dimensions/symbols of the affine map are aligned with `constraints`.
 /// `operands` are the SSA Value operands used with the affine map.
 /// Note: This function adds a new symbol column to the `constraints` for each
 /// dimension/symbol that exists in the affine map but not in `constraints`.
 static LogicalResult alignAndAddBound(FlatAffineValueConstraints &constraints,
-                                      IntegerPolyhedron::BoundType type,
-                                      unsigned pos, AffineMap map,
-                                      ValueRange operands) {
+                                      BoundType type, unsigned pos,
+                                      AffineMap map, ValueRange operands) {
   SmallVector<Value> dims, syms, newSyms;
   unpackOptionalValues(constraints.getMaybeValues(VarKind::SetDim), dims);
   unpackOptionalValues(constraints.getMaybeValues(VarKind::Symbol), syms);
 
   AffineMap alignedMap =
       alignAffineMapWithValues(map, operands, dims, syms, &newSyms);
   for (unsigned i = syms.size(); i < newSyms.size(); ++i)
     constraints.appendSymbolVar(newSyms[i]);
mlir::simplifyConstrainedMinMaxOp(Operation *op,
 
   // Add a few extra dimensions.
   unsigned dimOp = constraints.appendDimVar();      // `op`
   unsigned dimOpBound = constraints.appendDimVar(); // `op` lower/upper bound
   unsigned resultDimStart = constraints.appendDimVar(/*num=*/numResults);
 
   // Add an inequality for each result expr_i of map:
   // isMin: op <= expr_i, !isMin: op >= expr_i
-  auto boundType = isMin ? IntegerPolyhedron::UB : IntegerPolyhedron::LB;
+  auto boundType = isMin ? BoundType::UB : BoundType::LB;
   // Upper bounds are exclusive, so add 1. (`affine.min` ops are inclusive.)
   AffineMap mapLbUb = isMin ? addConstToResults(map, 1) : map;
   if (failed(
           alignAndAddBound(constraints, boundType, dimOp, mapLbUb, operands)))
     return failure();
 
   // Try to compute a lower/upper bound for op, expressed in terms of the other
   // `dims` and extra symbols.
   SmallVector<AffineMap> opLb(1), opUb(1);
   constraints.getSliceBounds(dimOp, 1, ctx, &opLb, &opUb);
   AffineMap sliceBound = isMin ? opUb[0] : opLb[0];
   // TODO: `getSliceBounds` may return multiple bounds at the moment. This is
   // a TODO of `getSliceBounds` and not handled here.
   if (!sliceBound || sliceBound.getNumResults() != 1)
     return failure(); // No or multiple bounds found.
   // Recover the inclusive UB in the case of an `affine.min`.
   AffineMap boundMap = isMin ? addConstToResults(sliceBound, -1) : sliceBound;
 
   // Add an equality: Set dimOpBound to computed bound.
   // Add back dimension for op. (Was removed by `getSliceBounds`.)
   AffineMap alignedBoundMap = boundMap.shiftDims(/*shift=*/1, /*offset=*/dimOp);
-  if (failed(constraints.addBound(IntegerPolyhedron::EQ, dimOpBound,
-                                  alignedBoundMap)))
+  if (failed(constraints.addBound(BoundType::EQ, dimOpBound, alignedBoundMap)))
     return failure();
 
   // If the constraint system is empty, there is an inconsistency. (E.g., this
   // can happen if loop lb > ub.)
   if (constraints.isEmpty())
     return failure();
 
   // In the case of `isMin` (`!isMin` is inversed):
   // Prove that each result of `map` has a lower bound that is equal to (or
   // greater than) the upper bound of `op` (`dimOpBound`). In that case, `op`
   // can be replaced with the bound. I.e., prove that for each result
   // expr_i (represented by dimension r_i):
   //
   // r_i >= opBound
   //
   // To prove this inequality, add its negation to the constraint set and prove
   // that the constraint set is empty.
   for (unsigned i = resultDimStart; i < resultDimStart + numResults; ++i) {
     FlatAffineValueConstraints newConstr(constraints);
 
     // Add an equality: r_i = expr_i
     // Note: These equalities could have been added earlier and used to express
     // minOp <= expr_i. However, then we run the risk that `getSliceBounds`
     // computes minOpUb in terms of r_i dims, which is not desired.
-    if (failed(alignAndAddBound(newConstr, IntegerPolyhedron::EQ, i,
+    if (failed(alignAndAddBound(newConstr, BoundType::EQ, i,
                                 map.getSubMap({i - resultDimStart}), operands)))
       return failure();
 
     // If `isMin`:  Add inequality: r_i < opBound
     //              equiv.: opBound - r_i - 1 >= 0
     // If `!isMin`: Add inequality: r_i > opBound
     //              equiv.: -opBound + r_i - 1 >= 0
     SmallVector<int64_t> ineq(newConstr.getNumCols(), 0);
mlir::simplifyConstrainedMinMaxOp(Operation *op,
   SmallVector<Value> newOperands;
   unpackOptionalValues(constraints.getMaybeValues(), newOperands);
   // If dims/symbols have known constant values, use those in order to simplify
   // the affine map further.
   for (int64_t i = 0, e = constraints.getNumDimAndSymbolVars(); i < e; ++i) {
     // Skip unused operands and operands that are already constants.
     if (!newOperands[i] || getConstantIntValue(newOperands[i]))
       continue;
-    if (auto bound = constraints.getConstantBound64(IntegerPolyhedron::EQ, i)) {
+    if (auto bound = constraints.getConstantBound64(BoundType::EQ, i)) {
       AffineExpr expr =
           i < newMap.getNumDims()
               ? builder.getAffineDimExpr(i)
               : builder.getAffineSymbolExpr(i - newMap.getNumDims());
       newMap = newMap.replace(expr, builder.getAffineConstantExpr(*bound),
                               newMap.getNumDims(), newMap.getNumSymbols());
     }
   }
   mlir::canonicalizeMapAndOperands(&newMap, &newOperands);
   return AffineValueMap(newMap, newOperands);
 }

mlir/lib/Dialect/Affine/TransformOps/AffineTransformOps.cpp

SimplifyBoundedAffineOpsOp::apply(TransformResults &results,
   }
 
   // Build constraint set.
   FlatAffineValueConstraints cstr;
   for (const auto &it : llvm::zip(boundedValues, lbs, ubs)) {
     unsigned pos;
     if (!cstr.findVar(std::get<0>(it), &pos))
       pos = cstr.appendSymbolVar(std::get<0>(it));
-    cstr.addBound(FlatAffineValueConstraints::BoundType::LB, pos,
-                  std::get<1>(it));
+    cstr.addBound(presburger::BoundType::LB, pos, std::get<1>(it));
     // Note: addBound bounds are inclusive, but specified UB is exclusive.
-    cstr.addBound(FlatAffineValueConstraints::BoundType::UB, pos,
-                  std::get<2>(it) - 1);
+    cstr.addBound(presburger::BoundType::UB, pos, std::get<2>(it) - 1);
   }
 
   // Transform all targets.
   ArrayRef<Operation *> targets = state.getPayloadOps(getTarget());
   for (Operation *target : targets) {
     if (!isa<AffineMinOp, AffineMaxOp>(target)) {
       auto diag = emitDefiniteFailure()
                   << "target must be affine.min or affine.max";

mlir/lib/Dialect/Affine/Utils/LoopUtils.cpp

static bool getFullMemRefAsRegion(Operation *op, unsigned numParamLoopIVs,
   extractForInductionVars(ivs, &symbols);
   *regionCst = FlatAffineValueConstraints(rank, numParamLoopIVs, 0);
   regionCst->setValues(rank, rank + numParamLoopIVs, symbols);
 
   // Memref dim sizes provide the bounds.
   for (unsigned d = 0; d < rank; d++) {
     auto dimSize = memRefType.getDimSize(d);
     assert(dimSize > 0 && "filtered dynamic shapes above");
-    regionCst->addBound(IntegerPolyhedron::LB, d, 0);
-    regionCst->addBound(IntegerPolyhedron::UB, d, dimSize - 1);
+    regionCst->addBound(BoundType::LB, d, 0);
+    regionCst->addBound(BoundType::UB, d, dimSize - 1);
   }
   return true;
 }
 
 LogicalResult mlir::affineDataCopyGenerate(Block::iterator begin,
                                            Block::iterator end,
                                            const AffineCopyOptions &copyOptions,
                                            std::optional<Value> filterMemRef,

mlir/lib/Dialect/Affine/Utils/Utils.cpp

MemRefType mlir::normalizeMemRefType(MemRefType memrefType,
   // with the right shape and an identity layout map.
   ArrayRef<int64_t> shape = memrefType.getShape();
   // FlatAffineValueConstraint may later on use symbolicOperands.
   FlatAffineValueConstraints fac(rank, numSymbolicOperands);
   SmallVector<unsigned, 4> memrefTypeDynDims;
   for (unsigned d = 0; d < rank; ++d) {
     // Use constraint system only in static dimensions.
     if (shape[d] > 0) {
-      fac.addBound(IntegerPolyhedron::LB, d, 0);
-      fac.addBound(IntegerPolyhedron::UB, d, shape[d] - 1);
+      fac.addBound(BoundType::LB, d, 0);
+      fac.addBound(BoundType::UB, d, shape[d] - 1);
     } else {
       memrefTypeDynDims.emplace_back(d);
     }
   }
   // We compose this map with the original index (logical) space to derive
   // the upper bounds for the new index space.
   unsigned newRank = layoutMap.getNumResults();
   if (failed(fac.composeMatchingMap(layoutMap)))
     return memrefType;
   // TODO: Handle semi-affine maps.
   // Project out the old data dimensions.
   fac.projectOut(newRank, fac.getNumVars() - newRank - fac.getNumLocalVars());
   SmallVector<int64_t, 4> newShape(newRank);
   MLIRContext *context = memrefType.getContext();
   for (unsigned d = 0; d < newRank; ++d) {
     // Check if this dimension is dynamic.
     bool isDynDim =
         isNormalizedMemRefDynamicDim(d, layoutMap, memrefTypeDynDims, context);
     if (isDynDim) {
       newShape[d] = ShapedType::kDynamic;
     } else {
       // The lower bound for the shape is always zero.
-      std::optional<int64_t> ubConst =
-          fac.getConstantBound64(IntegerPolyhedron::UB, d);
+      std::optional<int64_t> ubConst = fac.getConstantBound64(BoundType::UB, d);
       // For a static memref and an affine map with no symbols, this is
       // always bounded. However, when we have symbols, we may not be able to
       // obtain a constant upper bound. Also, mapping to a negative space is
       // invalid for normalization.
       if (!ubConst.has_value() || *ubConst < 0) {
         LLVM_DEBUG(llvm::dbgs()
                    << "can't normalize map due to unknown/invalid upper bound");
         return memrefType;

mlir/lib/Dialect/Linalg/Utils/Utils.cpp

for (Operation *op : llvm::reverse(backwardSlice)) {
     if (!(llvm::all_of(op->getResults(), findOrCreateId) &&
           llvm::all_of(op->getOperands(), findOrCreateId)))
       return;
 
     // Add AffineApplyOps to the constraints.
     if (auto applyOp = dyn_cast<AffineApplyOp>(op)) {
       AffineMap map = constraints.computeAlignedMap(applyOp.getAffineMap(),
                                                     applyOp.getOperands());
-      if (failed(constraints.addBound(IntegerPolyhedron::EQ,
+      if (failed(constraints.addBound(BoundType::EQ,
                                       getPosition(applyOp.getResult()), map)))
         return;
       continue;
     }
     // Add AffineMinOps to the constraints.
     auto minOp = cast<AffineMinOp>(op);
     AffineMap map = constraints.computeAlignedMap(minOp.getAffineMap(),
                                                   minOp.getOperands());
-    if (failed(constraints.addBound(IntegerPolyhedron::UB,
+    if (failed(constraints.addBound(BoundType::UB,
                                     getPosition(minOp.getResult()), map,
                                     /*isClosedBound=*/true)))
       return;
   }
 
   // Obtain an upper bound for the affine index computation by projecting out
   // all temporary results and expressing the upper bound for `value` in terms
   // of the terminals of the index computation.
   unsigned pos = getPosition(value);
   if (constantRequired) {
-    auto ubConst = constraints.getConstantBound64(
-        FlatAffineValueConstraints::BoundType::UB, pos);
+    auto ubConst = constraints.getConstantBound64(BoundType::UB, pos);
     if (!ubConst)
       return;
 
     boundMap = AffineMap::getConstantMap(*ubConst, value.getContext());
     return;
   }
 
   SmallVector<AffineMap> lowerBounds(1), upperBounds(1);

mlir/lib/Dialect/SCF/Utils/AffineCanonicalizationUtils.cpp

LogicalResult scf::addLoopRangeConstraints(FlatAffineValueConstraints &cstr,
   auto ubv = ub.dyn_cast<Value>();
   unsigned symUb =
       ubv ? cstr.appendSymbolVar(ubv) : cstr.appendSymbolVar(/*num=*/1);
 
   // If loop lower/upper bounds are constant: Add EQ constraint.
   std::optional<int64_t> lbInt = getConstantIntValue(lb);
   std::optional<int64_t> ubInt = getConstantIntValue(ub);
   if (lbInt)
-    cstr.addBound(IntegerPolyhedron::EQ, symLb, *lbInt);
+    cstr.addBound(BoundType::EQ, symLb, *lbInt);
   if (ubInt)
-    cstr.addBound(IntegerPolyhedron::EQ, symUb, *ubInt);
+    cstr.addBound(BoundType::EQ, symUb, *ubInt);
 
   // Lower bound: iv >= lb (equiv.: iv - lb >= 0)
   SmallVector<int64_t> ineqLb(cstr.getNumCols(), 0);
   ineqLb[dimIv] = 1;
   ineqLb[symLb] = -1;
   cstr.addInequality(ineqLb);
 
   // Upper bound
AffineExpr exprUb =
         ubInt ? b.getAffineConstantExpr(*ubInt)
               : b.getAffineSymbolExpr(symUb - cstr.getNumDimVars());
     ivUb = exprLb + 1 + (*stepInt * ((exprUb - exprLb - 1).floorDiv(*stepInt)));
   }
   auto map = AffineMap::get(
       /*dimCount=*/cstr.getNumDimVars(),
       /*symbolCount=*/cstr.getNumSymbolVars(), /*result=*/ivUb);
 
-  return cstr.addBound(IntegerPolyhedron::UB, dimIv, map);
+  return cstr.addBound(BoundType::UB, dimIv, map);
 }
 
 /// Canonicalize min/max operations in the context of for loops with a known
 /// range. Call `canonicalizeMinMaxOp` and add the following constraints to
 /// the constraint system (along with the missing dimensions):
 ///
 /// * iv >= lb
 /// * iv < lb + step * ((ub - lb - 1) floorDiv step) + 1

 /// parameters, see comment of `canonicalizeMinMaxOpInLoop`.
 LogicalResult scf::rewritePeeledMinMaxOp(RewriterBase &rewriter, Operation *op,
                                          Value iv, Value ub, Value step,
                                          bool insideLoop) {
   FlatAffineValueConstraints constraints;
   constraints.appendDimVar({iv});
   constraints.appendSymbolVar({ub, step});
   if (auto constUb = getConstantIntValue(ub))
-    constraints.addBound(IntegerPolyhedron::EQ, 1, *constUb);
+    constraints.addBound(BoundType::EQ, 1, *constUb);
   if (auto constStep = getConstantIntValue(step))
-    constraints.addBound(IntegerPolyhedron::EQ, 2, *constStep);
+    constraints.addBound(BoundType::EQ, 2, *constStep);
 
   // Add loop peeling invariant. This is the main piece of knowledge that
   // enables AffineMinOp simplification.
   if (insideLoop) {
     // ub - iv >= step (equiv.: -iv + ub - step + 0 >= 0)
     // Intuitively: Inside the peeled loop, every iteration is a "full"
     // iteration, i.e., step divides the iteration space `ub - lb` evenly.
     constraints.addInequality({-1, 1, -1, 0});

mlir/unittests/Analysis/Presburger/IntegerPolyhedronTest.cpp

TEST(IntegerPolyhedronTest, removeRedundantConstraintsTest) {
   for (unsigned i = 0; i < 3; ++i) {
     // Ensure that the removed constraint was the redundant constraint [3].
     EXPECT_NE(poly5.getInequality(i), ArrayRef<MPInt>(redundantConstraint));
   }
 }
 
 TEST(IntegerPolyhedronTest, addConstantUpperBound) {
   IntegerPolyhedron poly(PresburgerSpace::getSetSpace(2));
-  poly.addBound(IntegerPolyhedron::UB, 0, 1);
+  poly.addBound(BoundType::UB, 0, 1);
   EXPECT_EQ(poly.atIneq(0, 0), -1);
   EXPECT_EQ(poly.atIneq(0, 1), 0);
   EXPECT_EQ(poly.atIneq(0, 2), 1);
 
-  poly.addBound(IntegerPolyhedron::UB, {1, 2, 3}, 1);
+  poly.addBound(BoundType::UB, {1, 2, 3}, 1);
   EXPECT_EQ(poly.atIneq(1, 0), -1);
   EXPECT_EQ(poly.atIneq(1, 1), -2);
   EXPECT_EQ(poly.atIneq(1, 2), -2);
 }
 
 TEST(IntegerPolyhedronTest, addConstantLowerBound) {
   IntegerPolyhedron poly(PresburgerSpace::getSetSpace(2));
-  poly.addBound(IntegerPolyhedron::LB, 0, 1);
+  poly.addBound(BoundType::LB, 0, 1);
   EXPECT_EQ(poly.atIneq(0, 0), 1);
   EXPECT_EQ(poly.atIneq(0, 1), 0);
   EXPECT_EQ(poly.atIneq(0, 2), -1);
 
-  poly.addBound(IntegerPolyhedron::LB, {1, 2, 3}, 1);
+  poly.addBound(BoundType::LB, {1, 2, 3}, 1);
   EXPECT_EQ(poly.atIneq(1, 0), 1);
   EXPECT_EQ(poly.atIneq(1, 1), 2);
   EXPECT_EQ(poly.atIneq(1, 2), 2);
 }
 
 /// Check if the expected division representation of local variables matches the
 /// computed representation. The expected division representation is given as
 /// a vector of expressions set in `expectedDividends` and the corressponding