fixup! [USMP] Adding support for U4 usecase

Change-Id: I78f03d36b12b4a5e8eae8d11701f51019489defc

Author: manupak

src/relay/backend/aot_executor_codegen.cc

@@ -1112,32 +1112,20 @@ class AOTExecutorCodegen : public MixedModeVisitor {
     auto tir_main_func = CreateMainFunc(mod_name, lowered_main_func->params.size());
     // Extract additional information around main TIR PrimFunc arguments
     Array<String> devices = ListDevices();
-    Array<tir::Var> inputs =
-        Array<tir::Var>(tir_main_func->params.begin(), tir_main_func->params.begin() +
-                                                           tir_main_func->params.size() -
-                                                           return_sid_.size() - devices.size());
+    const auto main_func_params_end_iterator =
+        tir_main_func->params.begin() + tir_main_func->params.size();
+    const auto outputs_begin_iterator =
+        main_func_params_end_iterator - return_sid_.size() - devices.size();
+    Array<tir::Var> inputs = Array<tir::Var>(tir_main_func->params.begin(), outputs_begin_iterator);
     Array<TensorType> input_tensor_types;
     for (auto i : inputs) {
       input_tensor_types.push_back(io_tensor_types_[i]);
     }
-
+    Array<tir::Var> outputs =
+        Array<tir::Var>(outputs_begin_iterator, main_func_params_end_iterator - devices.size());
     std::vector<String> output_var_names;
-    if (auto opt = func->GetAttr<Array<String>>("output_tensor_names")) {
-      Array<String> output_tensor_names = opt.value();
-      for (size_t i = 0; i < output_tensor_names.size(); ++i) {
-        output_var_names.push_back(output_tensor_names[i]);
-      }
-    }
-
-    // If output names have not been specified then generate default output names
-    if (output_var_names.size() == 0) {
-      if (return_sid_.size() == 1) {
-        output_var_names.push_back(String("output"));
-      } else {
-        for (size_t i = 0; i < return_sid_.size(); ++i) {
-          output_var_names.push_back(String("output" + std::to_string(i)));
-        }
-      }
+    for (const tir::Var& output : outputs) {
+      output_var_names.push_back(output->name_hint);
     }
 
     Array<TensorType> output_tensor_types{final_aot_allocator.GetReturnTtypes()};