diff --git a/paddle/fluid/inference/tensorrt/convert/skip_layernorm.cc b/paddle/fluid/inference/tensorrt/convert/skip_layernorm.cc
index cf95a4d9b55e0e..b4484c7ad14c37 100644
--- a/paddle/fluid/inference/tensorrt/convert/skip_layernorm.cc
+++ b/paddle/fluid/inference/tensorrt/convert/skip_layernorm.cc
@@ -26,12 +26,29 @@ class SkipLayerNormOpConverter : public OpConverter {
   void operator()(const framework::proto::OpDesc& op,
                   const framework::Scope& scope,
                   bool test_mode) override {
-#if IS_TRT_VERSION_GE(6000)
     VLOG(4) << "convert fused skip layernorm op to tensorrt layer";
     framework::OpDesc op_desc(op, nullptr);
     // Declare inputs
     auto* input1 = engine_->GetITensor(op_desc.Input("X")[0]);
     auto* input2 = engine_->GetITensor(op_desc.Input("Y")[0]);
+
+    // We should expand input1 to input2's nbDims
+    if (input1->getDimensions().nbDims < input2->getDimensions().nbDims) {
+      nvinfer1::Dims reshape_input1_dim;
+      reshape_input1_dim.nbDims = input2->getDimensions().nbDims;
+      for (int i = 0; i < reshape_input1_dim.nbDims; i++) {
+        if (i < input1->getDimensions().nbDims) {
+          reshape_input1_dim.d[i] = 0;
+        } else {
+          reshape_input1_dim.d[i] = 1;
+        }
+      }
+      auto* reshape_input1_layer =
+          TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *input1);
+      reshape_input1_layer->setReshapeDimensions(reshape_input1_dim);
+      input1 = reshape_input1_layer->getOutput(0);
+    }
+
     std::vector<nvinfer1::ITensor*> inputs;
     inputs.push_back(input1);
     inputs.push_back(input2);
@@ -74,10 +91,10 @@ class SkipLayerNormOpConverter : public OpConverter {
              bias_weight.values,
              GetPluginFieldType(bias_weight.type),
              static_cast<int32_t>(bias_weight.count)},
-            { "gamma",
-              scale_weight.values,
-              GetPluginFieldType(scale_weight.type),
-              static_cast<int32_t>(scale_weight.count) }};
+            {"gamma",
+             scale_weight.values,
+             GetPluginFieldType(scale_weight.type),
+             static_cast<int32_t>(scale_weight.count)}};
         nvinfer1::PluginFieldCollection* pluginPtr =
             static_cast<nvinfer1::PluginFieldCollection*>(
                 malloc(sizeof(*pluginPtr) +
@@ -178,11 +195,6 @@ class SkipLayerNormOpConverter : public OpConverter {
 
     auto output_name = op_desc.Output("Out")[0];
     RreplenishLayerAndOutput(layer, "skip_layernorm", {output_name}, test_mode);
-#else
-    PADDLE_THROW(platform::errors::Fatal(
-        "You are running the TRT Dynamic Shape mode, need to confirm that "
-        "your TRT version is no less than 6.0"));
-#endif
   }
 };