diff --git a/paddle/fluid/inference/tensorrt/op_teller.cc b/paddle/fluid/inference/tensorrt/op_teller.cc
index 040a3c9a22af85ecebcdef6862d098bd26cebbf4..957241cb3e89d6fe8c4ab9b083664abd1ca97ed4 100644
--- a/paddle/fluid/inference/tensorrt/op_teller.cc
+++ b/paddle/fluid/inference/tensorrt/op_teller.cc
@@ -303,9 +303,6 @@ bool OpTeller::Tell(const framework::ir::Node* node,
       desc.HasAttr("skip_quant"))
     return false;
 
-  // do not support Attribute with Variable(s) Type
-  if (HasUnsupportAttrVar(desc)) return false;
-
   for (auto& teller : tellers_) {
     std::unordered_set<std::string> act_op_list = {
         "relu",     "relu6", "sigmoid",
@@ -364,7 +361,30 @@ bool OpTeller::Tell(const framework::ir::Node* node,
       }
     }
 
+    if (op_type == "dropout") {
+      /*
+       * Some OpDescs Attribute support both constant value and dynamic
+       * runtime value (which is a Variable(s) type). But TensorRT maybe
+       * only support constant value Attribute, so we shall distinguish
+       * this case in time and return False in OpTeller.Tell().
+       * If Attribute is Variable(s), HasAttr() will return False
+       */
+      if (!desc.HasAttr("dropout_prob", /*with_attr_var=*/false)) {
+        VLOG(3)
+            << "Skip to convert into TRT while found Attribute('dropout_prob') "
+               "is Variable type in dropout.";
+        return false;
+      }
+    }
+
     if (op_type == "pool2d") {
+      // If Attribute is Variable(s), HasAttr() will return False
+      if (!desc.HasAttr("ksize", /*with_attr_var=*/false)) {
+        VLOG(3) << "Skip to convert into TRT while found Attribute('ksize') is "
+                   "Variable type in pool2d.";
+        return false;
+      }
+
       std::vector<int> paddings =
           PADDLE_GET_CONST(std::vector<int>, desc.GetAttr("paddings"));
       if (paddings.size() > 2) {
@@ -797,6 +817,12 @@ bool OpTeller::Tell(const framework::ir::Node* node,
     }
 
     if (op_type == "arg_max") {
+      if (!desc.HasAttr("axis", /*with_attr_var=*/false)) {
+        VLOG(3) << "Skip to convert into TRT while found Attribute('axis') is "
+                   "Variable type in arg_max.";
+        return false;
+      }
+
       int axis = desc.HasAttr("axis")
                      ? PADDLE_GET_CONST(int64_t, desc.GetAttr("axis"))
                      : -1;
@@ -1061,6 +1087,13 @@ bool OpTeller::Tell(const framework::ir::Node* node,
     }
 
     if (op_type == "squeeze2") {
+      // If Attribute is Variable(s), HasAttr() will return False
+      if (!desc.HasAttr("axes", /*with_attr_var=*/false)) {
+        VLOG(3) << "Skip to convert into TRT while found Attribute('axes') is "
+                   "Variable type in squeeze2.";
+        return false;
+      }
+
       std::vector<int> axes;
       if (desc.HasAttr("axes")) {
         axes = PADDLE_GET_CONST(std::vector<int>, desc.GetAttr("axes"));
@@ -2002,6 +2035,13 @@ bool OpTeller::Tell(const framework::ir::Node* node,
     }
 
     if (op_type == "reduce_sum" || op_type == "reduce_mean") {
+      if (!desc.HasAttr("dim", /*with_attr_var=*/false)) {
+        VLOG(3) << "Skip to convert into TRT while found Attribute('dim') is "
+                   "Variable type in "
+                << desc.Type();
+        return false;
+      }
+
       if (!(desc.HasAttr("keep_dim") && desc.HasAttr("dim") &&
             desc.HasAttr("reduce_all"))) {
         VLOG(3) << "the " << op_type
@@ -2265,34 +2305,6 @@ bool OpTeller::Tell(const framework::ir::Node* node,
   return false;
 }
 
-bool OpTeller::HasUnsupportAttrVar(const framework::OpDesc& desc) const {
-  const std::string op_type = desc.Type();
-  auto has_attr_var = [&](const std::string& attr_name) -> bool {
-    // If Attribute is Variable(s), HasAttr() will return False
-    return !desc.HasAttr(attr_name, /*with_attr_var=*/false);
-  };
-  std::unordered_map<std::string, std::vector<std::string>> attrs_info = {
-      {"dropout", {"dropout_prob"}},
-      {"pool2d", {"ksize"}},
-      {"arg_max", {"axis"}},
-      {"reduce_mean", {"dim"}},
-      {"reduce_sum", {"dim"}},
-      {"squeeze2", {"axes"}},
-  };
-
-  bool flag = false;
-  auto iter = attrs_info.find(op_type);
-  if (iter != attrs_info.end()) {
-    for (auto& attr_name : iter->second) {
-      if (has_attr_var(attr_name)) {
-        flag = true;
-        break;
-      }
-    }
-  }
-  return flag;
-}
-
 OpTeller::OpTeller() { tellers_.emplace_back(new SimpleOpTypeSetTeller); }
 }  // namespace tensorrt
 }  // namespace inference
diff --git a/paddle/fluid/inference/tensorrt/op_teller.h b/paddle/fluid/inference/tensorrt/op_teller.h
index d7d7d8b674001eabca2ffc974c92655300731dec..1a6ce092a18b43588f9db8372394155e596c73ab 100644
--- a/paddle/fluid/inference/tensorrt/op_teller.h
+++ b/paddle/fluid/inference/tensorrt/op_teller.h
@@ -73,14 +73,6 @@ class OpTeller {
  private:
   OpTeller();
 
-  /*
-   * Some OpDescs Attribute support both constant value and dynamic
-   * runtime value (which is a Variable(s) type). But TensorRT maybe
-   * only support constant value Attribute, so we shall distinguish
-   * this case in time and return False in OpTeller.Tell().
-   */
-  bool HasUnsupportAttrVar(const framework::OpDesc& desc) const;
-
  private:
   std::vector<std::unique_ptr<Teller>> tellers_;
 };