Introduce memref bound checking.

Introduce analysis to check memref accesses (in MLFunctions) for out of bound
ones. It works as follows:

$ mlir-opt -memref-bound-check test/Transforms/memref-bound-check.mlir

/tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#2
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#2
      %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
           ^
/tmp/single.mlir:12:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1
      %y = load %B[%idy] : memref<128 x i32>
           ^
/tmp/single.mlir:12:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1
      %y = load %B[%idy] : memref<128 x i32>
           ^
#map0 = (d0, d1) -> (d0, d1)
#map1 = (d0, d1) -> (d0 * 128 - d1)
mlfunc @test() {
  %0 = alloc() : memref<9x9xi32>
  %1 = alloc() : memref<128xi32>
  for %i0 = -1 to 9 {
    for %i1 = -1 to 9 {
      %2 = affine_apply #map0(%i0, %i1)
      %3 = load %0[%2tensorflow/mlir#0, %2tensorflow/mlir#1] : memref<9x9xi32>
      %4 = affine_apply #map1(%i0, %i1)
      %5 = load %1[%4] : memref<128xi32>
    }
  }
  return
}

- Improves productivity while manually / semi-automatically developing MLIR for
  testing / prototyping; also provides an indirect way to catch errors in
  transformations.

- This pass is an easy way to test the underlying affine analysis
  machinery including low level routines.

Some code (in getMemoryRegion()) borrowed from @andydavis cl/218263256.

While on this:

- create mlir/Analysis/Passes.h; move Pass.h up from mlir/Transforms/ to mlir/

- fix a bug in AffineAnalysis.cpp::toAffineExpr

TODO: extend to non-constant loop bounds (straightforward). Will transparently
work for all accesses once floordiv, mod, ceildiv are supported in the
AffineMap -> FlatAffineConstraints conversion.
PiperOrigin-RevId: 219397961

1 files changed, 16 insertions, 0 deletions

diff --git a/mlir/lib/Analysis/AffineStructures.cpp b/mlir/lib/Analysis/AffineStructures.cpp
index de7c5db3e07..52c15bb9237 100644
--- a/mlir/lib/Analysis/AffineStructures.cpp
+++ b/mlir/lib/Analysis/AffineStructures.cpp
@@ -493,6 +493,22 @@ FlatAffineConstraints::FlatAffineConstraints(IntegerSet set)
   }
 }
 
+void FlatAffineConstraints::reset(unsigned numReservedInequalities,
+                                  unsigned numReservedEqualities,
+                                  unsigned newNumReservedCols,
+                                  unsigned newNumDims, unsigned newNumSymbols,
+                                  unsigned newNumLocals) {
+  assert(newNumReservedCols >= 1 && "minimum 1 column");
+  numReservedCols = newNumReservedCols;
+  numDims = newNumDims;
+  numSymbols = newNumSymbols;
+  numIds = numDims + numSymbols + newNumLocals;
+  equalities.clear();
+  inequalities.clear();
+  equalities.reserve(newNumReservedCols * numReservedEqualities);
+  inequalities.reserve(newNumReservedCols * numReservedInequalities);
+}
+
 /// Adds a dimensional identifier. The added column is initialized to
 /// zero.
 void FlatAffineConstraints::addDimId(unsigned pos) {