diff --git a/paddle/fluid/inference/tensorrt/op_teller.cc b/paddle/fluid/inference/tensorrt/op_teller.cc
index 9df3ec0445ad1c6c778f81a5e1489096c850c589..5ed79aa7ea4c38bccdf34b1420a549bcf983b1bd 100644
--- a/paddle/fluid/inference/tensorrt/op_teller.cc
+++ b/paddle/fluid/inference/tensorrt/op_teller.cc
@@ -143,19 +143,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
           BOOST_GET_CONST(std::vector<int>, desc.GetAttr("paddings"));
 
       if (paddings.size() > 2) return false;
-// strides > 1 is only supported by trt7.0 above
-#if !IS_TRT_VERSION_GE(7000)
-      if (desc.HasAttr("strides")) {
-        const std::vector<int> strides =
-            BOOST_GET_CONST(std::vector<int>, desc.GetAttr("strides"));
-        // there is no issue if strides.size() less than 2
-        if (strides.size() > 1) {
-          for (size_t i = 0; i < strides.size(); i++) {
-            if (strides[i] > 1) return false;
-          }
-        }
-      }
-#endif
     }
 
     if (op_type == "pool2d") {
@@ -239,15 +226,22 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
         return false;
       }
 
-// strides > 1 is only supported by trt7.0 above
+// strides > 1 and 'SAME' is only supported by trt7.0 above
 #if !IS_TRT_VERSION_GE(7000)
-      if (desc.HasAttr("strides")) {
-        const std::vector<int> strides =
-            BOOST_GET_CONST(std::vector<int>, desc.GetAttr("strides"));
-        // there is no issue if strides.size() less than 2
-        if (strides.size() > 1) {
-          for (size_t i = 0; i < strides.size(); i++) {
-            if (strides[i] > 1) return false;
+      if (op_type == "conv2d" || op_type == "conv2d_fusion" ||
+          op_type == "depthwise_conv2d") {
+        if (desc.HasAttr("padding_algorithm") && with_dynamic_shape) {
+          auto padding_algorithm =
+              BOOST_GET_CONST(std::string, desc.GetAttr("padding_algorithm"));
+          if (padding_algorithm == "SAME" && desc.HasAttr("strides")) {
+            const std::vector<int> strides =
+                BOOST_GET_CONST(std::vector<int>, desc.GetAttr("strides"));
+            // there is no issue if strides.size() less than 2
+            if (strides.size() > 1) {
+              for (size_t i = 0; i < strides.size(); i++) {
+                if (strides[i] > 1) return false;
+              }
+            }
           }
         }
       }
diff --git a/python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv_pass.py b/python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv_pass.py
index ec3955a9ae1441cdaa4efa5b0e87ff8b74a0b689..7f613c4765963da8e02d30aa7cf35553fc4d31fa 100644
--- a/python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv_pass.py
+++ b/python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv_pass.py
@@ -161,5 +161,70 @@ class TensorRTSubgraphPassDepthwiseConvTransposeTest(
         self.use_cudnn = False
 
 
+class DynamicShapeTensorRTSubgraphPassConvTest(InferencePassTest):
+    def setUp(self):
+        self.set_params()
+        with fluid.program_guard(self.main_program, self.startup_program):
+            data = fluid.data(
+                name="data", shape=[-1, 6, -1, -1], dtype="float32")
+            conv_out = fluid.layers.conv2d(
+                input=data,
+                num_filters=self.conv_num_filters,
+                filter_size=self.conv_filter_size,
+                groups=self.conv_groups,
+                padding=self.conv_padding,
+                bias_attr=False,
+                use_cudnn=self.use_cudnn,
+                stride=self.stride,
+                act=None)
+        self.feeds = {
+            "data": np.random.random([32, 6, 64, 64]).astype("float32"),
+        }
+        self.enable_trt = True
+        self.trt_parameters = DynamicShapeTensorRTSubgraphPassConvTest.TensorRTParam(
+            1 << 30, 32, 0, AnalysisConfig.Precision.Float32, False, False)
+        self.dynamic_shape_params = DynamicShapeTensorRTSubgraphPassConvTest.DynamicShapeParam(
+            {
+                "conv2d_0.tmp_0": [1, 6, 8, 8],
+                "data": [1, 6, 8, 8],
+                "depthwise_conv2d_0.tmp_0": [1, 6, 8, 8]
+            }, {
+                "conv2d_0.tmp_0": [32, 6, 64, 64],
+                "data": [32, 6, 64, 64],
+                "depthwise_conv2d_0.tmp_0": [32, 6, 64, 64]
+            }, {
+                "conv2d_0.tmp_0": [16, 6, 16, 16],
+                "data": [16, 6, 16, 16],
+                "depthwise_conv2d_0.tmp_0": [32, 6, 64, 64]
+            }, False)
+        self.fetch_list = [conv_out]
+
+    def set_params(self):
+        self.conv_num_filters = 6
+        self.conv_filter_size = 6
+        self.conv_groups = 6
+        self.conv_padding = 'SAME'
+        self.use_cudnn = True
+        self.stride = [2, 2]
+
+    def test_check_output(self):
+        if core.is_compiled_with_cuda():
+            use_gpu = True
+            self.check_output_with_option(use_gpu)
+            self.assertTrue(
+                PassVersionChecker.IsCompatible('tensorrt_subgraph_pass'))
+
+
+class DynamicShapeTensorRTSubgraphPassDepthwiseConvTransposeTest(
+        DynamicShapeTensorRTSubgraphPassConvTest):
+    def set_params(self):
+        self.conv_num_filters = 6
+        self.conv_filter_size = 6
+        self.conv_groups = 6
+        self.conv_padding = 'SAME'
+        self.use_cudnn = False
+        self.stride = [2, 2]
+
+
 if __name__ == "__main__":
     unittest.main()