Revert "Merge pull request #407 from Xilinx/matthias.fix_non_monotonic_slice_params"

This reverts commit 573742a, reversing
changes made to 1bf1742.

Author: josel-amd

mlir/include/mlir/IR/AffineExpr.h

@@ -110,11 +110,6 @@ class AffineExpr {
   /// floordiv, ceildiv, and mod is only allowed w.r.t constants.
   bool isPureAffine() const;
 
-  /// Returns true if this expression is monotonicically increasing with respect
-  /// to the AffineDimExprs, i.e. increasing the value of any AffineDimExpr will
-  /// never decrease the value of the result.
-  bool isMonotonicallyIncreasing() const;
-
   /// Returns the greatest known integral divisor of this affine expression. The
   /// result is always positive.
   int64_t getLargestKnownDivisor() const;

mlir/include/mlir/IR/AffineMap.h

@@ -382,10 +382,6 @@ class AffineMap {
   /// Returns true if the AffineMap represents a symbol-less permutation map.
   bool isPermutation() const;
 
-  // Returns true if every result is monotonically increasing.
-  // See AffineExpr::isMonotonicallyIncreasing().
-  bool isComponentWiseMonotonicallyIncreasing() const;
-
   /// Returns the map consisting of the `resultPos` subset.
   AffineMap getSubMap(ArrayRef<unsigned> resultPos) const;
 

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

@@ -612,6 +612,7 @@ SliceParameters computeSliceParameters(
 
     // Tiling creates a new slice at the proper index, the slice step is 1
     // (i.e. the op does not subsample, stepping occurs in the loop).
+    auto m = map.getSubMap({r});
     LLVM_DEBUG(llvm::dbgs() << "computeSliceParameters: submap: " << m << "\n");
     IRRewriter rewriter(builder);
     // The offset of the slice is map(lbs) - map(0).

mlir/lib/IR/AffineExpr.cpp

@@ -239,42 +239,6 @@ bool AffineExpr::isPureAffine() const {
   llvm_unreachable("Unknown AffineExpr");
 }
 
-static bool isNonNegativeConstant(AffineExpr expr) {
-  auto constant = dyn_cast<AffineConstantExpr>(expr);
-  return constant && constant.getValue() >= 0;
-}
-
-bool AffineExpr::isMonotonicallyIncreasing() const {
-  switch (getKind()) {
-  case AffineExprKind::SymbolId:
-  case AffineExprKind::DimId:
-  case AffineExprKind::Constant:
-    return true;
-  case AffineExprKind::Add: {
-    auto op = llvm::cast<AffineBinaryOpExpr>(*this);
-    return op.getLHS().isMonotonicallyIncreasing() &&
-           op.getRHS().isMonotonicallyIncreasing();
-  }
-  case AffineExprKind::Mul: {
-    // One operand must be a non-negative constant.
-    auto op = llvm::cast<AffineBinaryOpExpr>(*this);
-    return op.getLHS().isMonotonicallyIncreasing() &&
-           op.getRHS().isMonotonicallyIncreasing() &&
-           (isNonNegativeConstant(op.getLHS()) ||
-            isNonNegativeConstant(op.getRHS()));
-  }
-  case AffineExprKind::FloorDiv:
-  case AffineExprKind::CeilDiv: {
-    auto op = llvm::cast<AffineBinaryOpExpr>(*this);
-    return op.getLHS().isMonotonicallyIncreasing() &&
-           isNonNegativeConstant(op.getRHS());
-  }
-  case AffineExprKind::Mod:
-    return false;
-  }
-  llvm_unreachable("Unknown AffineExpr");
-}
-
 // Returns the greatest known integral divisor of this affine expression.
 int64_t AffineExpr::getLargestKnownDivisor() const {
   AffineBinaryOpExpr binExpr(nullptr);

mlir/lib/IR/AffineMap.cpp

@@ -651,11 +651,6 @@ bool AffineMap::isPermutation() const {
   return isProjectedPermutation();
 }
 
-bool AffineMap::isComponentWiseMonotonicallyIncreasing() const {
-  return all_of(getResults(),
-                [](auto expr) { return expr.isMonotonicallyIncreasing(); });
-}
-
 AffineMap AffineMap::getSubMap(ArrayRef<unsigned> resultPos) const {
   SmallVector<AffineExpr, 4> exprs;
   exprs.reserve(resultPos.size());

mlir/test/Dialect/Linalg/tile-tensors.mlir

@@ -167,35 +167,3 @@ module attributes {transform.with_named_sequence} {
     transform.yield
   }
 }
-
-// -----
-
-// CHECK-LABEL: func @non_monotonic_affine_expr
-//  CHECK-SAME:   %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?xf32>
-func.func @non_monotonic_affine_expr(%arg0 : tensor<?xf32>) -> tensor<?xf32> {
-  %c0 = arith.constant 0 : index
-  %0 = tensor.dim %arg0, %c0 : tensor<?xf32>
-  %empty = tensor.empty(%0) : tensor<?xf32>
-
-  // CHECK: scf.for
-  // CHECK: %[[SIZE:[a-zA-Z0-9_]+]] = tensor.dim %[[ARG0]],
-  // CHECK: tensor.extract_slice %[[ARG0]][0] [%[[SIZE]]] [1] : tensor<?xf32> to tensor<?xf32>
-  %generic = linalg.generic
-    {indexing_maps = [affine_map<(d0) -> (d0 mod 3)>,
-                      affine_map<(d0) -> (d0)>],
-     iterator_types = ["parallel"]}
-    ins(%arg0: tensor<?xf32>)
-    outs(%empty : tensor<?xf32>) {
-    ^bb0(%in : f32, %out: f32):
-      linalg.yield %in : f32
-    } -> tensor<?xf32>
-  return %generic : tensor<?xf32>
-}
-
-module attributes {transform.with_named_sequence} {
-  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
-    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
-    %1, %loop = transform.structured.tile_using_for %0 tile_sizes [100] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
-    transform.yield
-  }
-}