diff --git a/paddle/fluid/inference/tensorrt/op_teller.cc b/paddle/fluid/inference/tensorrt/op_teller.cc
index 6f413dd0042dc202c2a9119a9ee171a3ca4efad1..b23611c144f6925b2a4ea95293d50b073497e89d 100644
--- a/paddle/fluid/inference/tensorrt/op_teller.cc
+++ b/paddle/fluid/inference/tensorrt/op_teller.cc
@@ -354,6 +354,22 @@ bool OpTeller::Tell(const framework::ir::Node* node,
         }
       }
 #endif
+      // In fact, this should include all conv, not only conv2d
+      if (op_type == "conv2d") {
+        auto* block = desc.Block();
+        if (block == nullptr) {
+          VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
+                     "Developers need to check whether block_desc is passed in "
+                     "the pass.";
+          return false;
+        }
+        auto* filter_var_desc = block->FindVar(desc.Input("Filter")[0]);
+        if (!filter_var_desc->Persistable()) {
+          VLOG(3) << "Trt not support filter is  a intermediate tensor in "
+                     "conv2d op.";
+          return false;
+        }
+      }
     }
 
     if (op_type == "deformable_conv") {
@@ -912,6 +928,19 @@ bool OpTeller::Tell(const framework::ir::Node* node,
           return false;
         }
       }
+      auto* block = desc.Block();
+      if (block == nullptr) {
+        VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
+                   "Developers need to check whether block_desc is passed in "
+                   "the pass.";
+        return false;
+      }
+      auto* x_var_desc = block->FindVar(desc.Input("X")[0]);
+      auto dtype = x_var_desc->GetDataType();
+      // At present, forbid int64_t into trt.
+      if (dtype == 3) {
+        return false;
+      }
     }
 
     if (op_type == "unsqueeze2") {
@@ -931,6 +960,19 @@ bool OpTeller::Tell(const framework::ir::Node* node,
           return false;
         }
       }
+      auto* block = desc.Block();
+      if (block == nullptr) {
+        VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
+                   "Developers need to check whether block_desc is passed in "
+                   "the pass.";
+        return false;
+      }
+      auto* x_var_desc = block->FindVar(desc.Input("X")[0]);
+      auto dtype = x_var_desc->GetDataType();
+      // At present, forbid int64_t into trt.
+      if (dtype == 3) {
+        return false;
+      }
     }
 
     if (op_type == "batch_norm") {
@@ -1073,6 +1115,11 @@ bool OpTeller::Tell(const framework::ir::Node* node,
       auto x_var_name = desc.Input("X")[0];
       auto* x_var_desc = block->FindVar(x_var_name);
       const auto x_shape = x_var_desc->GetShape();
+      auto dtype = x_var_desc->GetDataType();
+      // At present, only support float32 or float16 into trt.
+      if (!(dtype == 5 || dtype == 4)) {
+        return false;
+      }
       if (!with_dynamic_shape && x_shape.size() == 1) {
         VLOG(3) << "Scale op does not support 1-dimensional input in tensorrt";
         return false;
@@ -1163,6 +1210,20 @@ bool OpTeller::Tell(const framework::ir::Node* node,
           return false;
         }
       }
+
+      auto* block = desc.Block();
+      if (block == nullptr) {
+        VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
+                   "Developers need to check whether block_desc is passed in "
+                   "the pass.";
+        return false;
+      }
+      auto* x_var_desc = block->FindVar(desc.Input("Input")[0]);
+      auto dtype = x_var_desc->GetDataType();
+      // At present, forbid int64_t into trt.
+      if (dtype == 3) {
+        return false;
+      }
     }
 
     if (op_type == "elementwise_add" || op_type == "elementwise_mul" ||