[mlir][Transforms] Add missing check in applyPermutation

The applyPermutation() utility should make sure
that the permutation numbers are within the size
of the input array. Otherwise it will cause a
cryptic array out of bound assertion later.

mlir/include/mlir/Dialect/Utils/IndexingUtils.h

@@ -202,6 +202,9 @@ SmallVector<T> applyPermutation(ArrayRef<T> input,
                                 ArrayRef<int64_t> permutation) {
   assert(input.size() == permutation.size() &&
          "expected input rank to equal permutation rank");
+  assert(
+      llvm::all_of(permutation, [&](size_t s) { return s < input.size(); }) &&
+      "permutation must be within input bounds");
   auto permutationRange = llvm::map_range(
       llvm::seq<unsigned>(0, input.size()),
       [&](int64_t idx) -> T { return input[permutation[idx]]; });

mlir/lib/Dialect/Tosa/IR/TosaOps.cpp

@@ -1116,6 +1116,12 @@ LogicalResult tosa::TransposeOp::verify() {
            "Unexpectedly found permutation tensor without rank");
     if (!isPermutationVector(constantPerms))
       return emitOpError() << "expected valid permutation tensor";
+
+    if (inputType.hasRank() && !llvm::all_of(constantPerms, [&](int64_t s) {
+          return s < inputType.getRank();
+        })) {
+      return emitOpError() << "permutation must be within input bounds";
+    }
   }
   return success();
 }

mlir/test/Dialect/Tosa/invalid.mlir

@@ -413,3 +413,38 @@ func.func @test_tile_invalid_multiples() {
   %1 = tosa.tile %0 {multiples = array<i64>} : (tensor<4x31x31xf32>) -> tensor<4x31x31xf32>
   return
 }
+
+// -----
+
+// CHECK-LABEL: @test_invalid_constant_permutation
+func.func @test_invalid_constant_permutation() {
+  // expected-error@+3 {{permutation must be within input bounds}}
+	%0 = tensor.empty() : tensor<3x4x5xi32>
+	%1 = arith.constant dense<[3, 0, 1]> : tensor<3xi32>
+	%2 = tosa.transpose %0, %1 : (tensor<3x4x5xi32>, tensor<3xi32>) -> tensor<3x4x5xi32>
+	return 
+}
+
+// -----
+
+// CHECK-LABEL: test_rank_size_constant_permutation
+func.func @test_rank_size_constant_permutation() {
+  // expected-error@+4 {{permutation must be within input bounds}}
+  %0 = arith.constant 6 : index
+  %1 = arith.constant dense<[0, 2]> : tensor<2xi32>
+  %2 = tensor.empty(%0) : tensor<?x27xi64>
+  %3 = tosa.transpose %2, %1 : (tensor<?x27xi64>, tensor<2xi32>) -> tensor<?x27xi64>
+  return
+}
+
+// -----
+
+// CHECK-LABEL: test_large_constant_permutation
+func.func @test_large_constant_permutation() {
+  // expected-error@+4 {{permutation must be within input bounds}}
+  %0 = arith.constant 6 : index
+  %1 = arith.constant dense<[1185677355, 332462212]> : tensor<2xi32>
+  %2 = tensor.empty(%0) : tensor<?x27xi64>
+  %3 = tosa.transpose %2, %1 : (tensor<?x27xi64>, tensor<2xi32>) -> tensor<?x27xi64>
+  return
+}

mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir

@@ -1373,30 +1373,4 @@ func.func @test_tosa_use_def_chain(%arg0: tensor<1x32x32x3xf32>, %arg1: tensor<1
   // CHECK: (tensor<1x32x32x16xf32>) -> tensor<1x16x16x16xf32>
   %1 = tosa.max_pool2d %0 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x32x32x16xf32>) -> tensor<?x16x16x16xf32>
   return %1 : tensor<?x16x16x16xf32>
-}
-
-// -----
-
-// CHECK-LABEL: test_rank_size_constant_permutation
-func.func @test_rank_size_constant_permutation() {
-  %c6 = arith.constant 6 : index
-  %cst_26 = arith.constant dense<[0, 2]> : tensor<2xi32>
-  %14 = tensor.empty(%c6) : tensor<?x27xi64>
-  // Fail to infer the shape but not crash.
-  // CHECK: (tensor<?x27xi64>, tensor<2xi32>) -> tensor<?x27xi64>
-  %72 = tosa.transpose %14, %cst_26 : (tensor<?x27xi64>, tensor<2xi32>) -> tensor<?x27xi64>
-  return
-}
-
-// -----
-
-// CHECK-LABEL: test_large_constant_permutation
-func.func @test_large_constant_permutation() {
-  %c6 = arith.constant 6 : index
-  %cst_26 = arith.constant dense<[1185677355, 332462212]> : tensor<2xi32>
-  %14 = tensor.empty(%c6) : tensor<?x27xi64>
-  // Fail to infer the shape but not crash.
-  // CHECK: (tensor<?x27xi64>, tensor<2xi32>) -> tensor<?x27xi64>
-  %72 = tosa.transpose %14, %cst_26 : (tensor<?x27xi64>, tensor<2xi32>) -> tensor<?x27xi64>
-  return
-}
+}