[mlir][tosa] Fix for incorrect cannonicalization of tosa.pad (#98356)

The current fold method for tosa.pad can produce invalid IR by replacing
the padded value with the tosa.pad is a noop. When the type of the input
value does not match the type of the tosa.pad, the canonicalizer detects
the change in types and asserts.

This change addresses the issue by avoiding folding when the input and
result types do not match.

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

@@ -859,7 +859,7 @@ OpFoldResult ReshapeOp::fold(FoldAdaptor adaptor) {
 
 OpFoldResult PadOp::fold(FoldAdaptor adaptor) {
   // If the pad is all zeros we can fold this operation away.
-  if (adaptor.getPadding()) {
+  if (adaptor.getPadding() && getInput1().getType() == getType()) {
     auto densePad = llvm::cast<DenseElementsAttr>(adaptor.getPadding());
     if (densePad.isSplat() && densePad.getSplatValue<APInt>().isZero()) {
       return getInput1();

mlir/test/Dialect/Tosa/canonicalize.mlir

@@ -217,6 +217,20 @@ func.func @pad_noop(%arg0: tensor<?x?xf32>) -> tensor<?x?xf32> {
 
 // -----
 
+// CHECK-LABEL: @pad_noop_type_mismatch_nofold
+func.func @pad_noop_type_mismatch_nofold(%arg0: tensor<10xf32>) -> tensor<?xf32> {
+  // CHECK: %[[PAD:.+]] = tosa.pad
+  // CHECK: return %[[PAD]]
+
+  %c0_i32 = arith.constant 0 : i32
+  %shape = tensor.from_elements %c0_i32, %c0_i32 : tensor<1x2xi32>
+
+  %0 = tosa.pad %arg0, %shape : (tensor<10xf32>, tensor<1x2xi32>) -> tensor<?xf32>
+  return %0 : tensor<?xf32>
+}
+
+// -----
+
 // CHECK-LABEL: @pad_determine_val_i32
 func.func @pad_determine_val_i32(%arg0: tensor<?x?xi32>, %arg1 : tensor<2x2xi32>) -> tensor<?x?xi32> {
   // CHECK: %[[ZERO:.+]] = "tosa.const"() <{value = dense<0> : tensor<i32>}