add verifier for pad input rank

Author: sayeddla

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

@@ -682,6 +682,10 @@ LogicalResult tosa::PadOp::inferReturnTypeComponents(
 
 LogicalResult PadOp::verify() {
   ShapedType inputType = llvm::cast<ShapedType>(getInput1().getType());
+  if (inputType.hasRank() && inputType.getRank() == 0) {
+    return emitOpError() << "input tensor rank must not be 0";
+  }
+
   ShapedType paddingType = llvm::cast<ShapedType>(getPadding().getType());
   if (paddingType.hasRank()) {
     if (paddingType.getRank() != 2) {

mlir/test/Dialect/Tosa/invalid.mlir

@@ -171,6 +171,22 @@ func.func @test_pad_negative_padding(%arg0: tensor<13x21xf32>) -> tensor<?x?xf32
 
 // -----
 
+func.func @test_pad_incorrect_input(%arg0: f32, %arg1: i32) -> f32 {
+  // expected-error@+1 {{'tosa.pad' op operand #0 must be ranked tensor of number values, but got 'f32'}}
+  %1 = "tosa.pad"(%arg0, %arg1) : (f32, i32) -> f32
+  return %1 : f32
+}
+
+// -----
+
+func.func @test_pad_zero_rank_input(%arg0: tensor<f32>, %arg1: tensor<i32>) -> tensor<f32> {
+  // expected-error@+1 {{'tosa.pad' op input tensor rank must not be 0}}
+  %1 = "tosa.pad"(%arg0, %arg1) : (tensor<f32>, tensor<i32>) -> tensor<f32>
+  return %1 : tensor<f32>
+}
+
+// -----
+
 func.func @test_transpose_non_const(%arg0: tensor<13x21x3xf32>, %arg1: tensor<3xi32>) -> tensor<3x13x21xf32> {
   // expected-error@+1 {{'tosa.transpose' op perms of transpose is not constant}}
   %0 = "tosa.transpose"(%arg0, %arg1) : (tensor<13x21x3xf32>, tensor<3xi32>) -> tensor<3x13x21xf32>