diff --git a/dnnlibrary/include/ModelBuilder.h b/dnnlibrary/include/ModelBuilder.h
index b4ddec5..d6b347e 100644
--- a/dnnlibrary/include/ModelBuilder.h
+++ b/dnnlibrary/include/ModelBuilder.h
@@ -43,10 +43,10 @@ class ModelBuilder {
     std::map<float, Index> float32_operand_map_;
     std::map<float, Index> float32_as_tensor_operand_map_;
     StrKeyMap<android::nn::wrapper::OperandType> operand_types_;
-    // tensor_inputs_ and tensor_outputs_ is to automatically determine the
+    // imm_blob_inputs_ and imm_blob_outputs_ is to automatically determine the
     // output of the model
-    std::set<std::string> tensor_inputs_;
-    std::set<std::string> tensor_outputs_;
+    std::set<std::string> imm_blob_inputs_;
+    std::set<std::string> imm_blob_outputs_;
 
     uint32_t int32_missing_index = UINT32_MAX;
     uint32_t float32_missing_index = UINT32_MAX;
diff --git a/generate_code.py b/generate_code.py
index 2f1fbe7..d6e1fef 100644
--- a/generate_code.py
+++ b/generate_code.py
@@ -75,7 +75,7 @@ def add_tensor_operand(operand):
     if operand['predefined'] == 'optional_bias':
         return add_optional_bias()
     if operand['cpp_type'] == 'str':
-        return '''tensor_inputs.insert({0});
+        return '''imm_blob_inputs_.insert({0});
 const auto {0}_idx = operand_indexes_.at({0});
 input_indexes.push_back({0}_idx);'''.format(operand['name'])
     elif operand['cpp_type'] == 'float':
@@ -86,7 +86,7 @@ def add_tensor_operand(operand):
 input_indexes.push_back({0}_idx);'''.format(operand['name'])
     elif operand['cpp_type'] == 'str_list':
         return '''for (const auto &x : {}) {{
-tensor_inputs_.insert(x);
+imm_blob_inputs_.insert(x);
 input_indexes.push_back(operand_indexes_.at(x));
 }}'''.format(operand['name'])
     else:
@@ -296,7 +296,7 @@ def generate_model_builder():
                 'AddOperation(ANEURALNETWORKS_{}, input_indexes, operand_type)[0];'.format(op['nnapi']))
         cogout(
             '''RegisterOperand(output, output_idx, operand_type);
-    tensor_outputs_.insert(output);
+    imm_blob_outputs_.insert(output);
     return output_idx;
     }
     '''