[mlir][Intrange] Fix materializing ShapedType constant values

When materializing integer ranges of splat tensors or vector as
constants, they should use DenseElementsAttr of the shaped type, not
IntegerAttrs of the element types, since this can violate the invariants
of tensor/vector ops.

Author: jeffniu-openai

mlir/lib/Analysis/DataFlow/IntegerRangeAnalysis.cpp

@@ -26,6 +26,7 @@
 #include "mlir/Interfaces/ControlFlowInterfaces.h"
 #include "mlir/Interfaces/InferIntRangeInterface.h"
 #include "mlir/Interfaces/LoopLikeInterface.h"
+#include "mlir/Support/DebugStringHelper.h"
 #include "mlir/Support/LLVM.h"
 #include "llvm/ADT/STLExtras.h"
 #include "llvm/Support/Casting.h"
@@ -76,9 +77,17 @@ void IntegerValueRangeLattice::onUpdate(DataFlowSolver *solver) const {
   else
     dialect = value.getParentBlock()->getParentOp()->getDialect();
 
-  Type type = getElementTypeOrSelf(value);
-  solver->propagateIfChanged(
-      cv, cv->join(ConstantValue(IntegerAttr::get(type, *constant), dialect)));
+  Attribute cstAttr;
+  if (isa<IntegerType, IndexType>(value.getType())) {
+    cstAttr = IntegerAttr::get(value.getType(), *constant);
+  } else if (auto shapedTy = dyn_cast<ShapedType>(value.getType())) {
+    cstAttr = SplatElementsAttr::get(shapedTy, *constant);
+  } else {
+    llvm::report_fatal_error(
+        Twine("FIXME: Don't know how to create a constant for this type: ") +
+        mlir::debugString(value.getType()));
+  }
+  solver->propagateIfChanged(cv, cv->join(ConstantValue(cstAttr, dialect)));
 }
 
 LogicalResult IntegerRangeAnalysis::visitOperation(

mlir/lib/Dialect/Arith/Transforms/IntRangeOptimizations.cpp

@@ -8,6 +8,7 @@
 
 #include <utility>
 
+#include "mlir/Analysis/DataFlow/ConstantPropagationAnalysis.h"
 #include "mlir/Analysis/DataFlowFramework.h"
 #include "mlir/Dialect/Arith/Transforms/Passes.h"
 
@@ -485,6 +486,7 @@ struct IntRangeOptimizationsPass final
     MLIRContext *ctx = op->getContext();
     DataFlowSolver solver;
     solver.load<DeadCodeAnalysis>();
+    solver.load<SparseConstantPropagation>();
     solver.load<IntegerRangeAnalysis>();
     if (failed(solver.initializeAndRun(op)))
       return signalPassFailure();

mlir/test/Dialect/Arith/int-range-opts.mlir

@@ -132,3 +132,19 @@ func.func @wraps() -> i8 {
   %mod = arith.remsi %val, %c64 : i8
   return %mod : i8
 }
+
+// -----
+
+// CHECK-LABEL: @analysis_crash
+func.func @analysis_crash(%arg0: i32, %arg1: tensor<128xi1>) -> tensor<128xi64> {
+  %c0_i32 = arith.constant 0 : i32
+  %cst = arith.constant dense<-1> : tensor<128xi32>
+  %splat = tensor.splat %arg0 : tensor<128xi32>
+  %0 = scf.for %arg2 = %c0_i32 to %arg0 step %arg0 iter_args(%arg3 = %splat) -> (tensor<128xi32>)  : i32 {
+    scf.yield %arg3 : tensor<128xi32>
+  }
+  %1 = arith.select %arg1, %0#0, %cst : tensor<128xi1>, tensor<128xi32>
+  // Make sure the analysis doesn't crash when materializing the range as a tensor constant.
+  %2 = arith.extsi %1 : tensor<128xi32> to tensor<128xi64>
+  return %2 : tensor<128xi64>
+}