diff --git a/paddle/fluid/inference/tensorrt/convert/shuffle_channel_op.cc b/paddle/fluid/inference/tensorrt/convert/shuffle_channel_op.cc
index 16264e82cf16a9bff45560bdfe74de666a0a2049..fa4c6f02bcd1e6e30fc35affd4cfbfb41b7efe0a 100644
--- a/paddle/fluid/inference/tensorrt/convert/shuffle_channel_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/shuffle_channel_op.cc
@@ -46,26 +46,23 @@ class ShuffleChannelOpConverter : public OpConverter {
 #if IS_TRT_VERSION_GE(8000)
     if (engine_->with_dynamic_shape()) {
       auto* input_shape_tensor = Shape(input);
+      auto* batch_shape_tensor = GetEleTensorOfShape(input_shape_tensor, 0);
       auto* channel_shape_tensor = GetEleTensorOfShape(input_shape_tensor, 1);
       auto* group_tensor =
           Add1DConstantLayer(group, output_name + "_group_tensor_");
       auto* new_channel_shape_tensor = Div(channel_shape_tensor, group_tensor);
-      std::vector<int32_t> shape_dim3{0, 2, 3};
-      auto* shape_dim3_tensor = Gather(input_shape_tensor, shape_dim3);
+      std::vector<int32_t> shape_dim2{2, 3};
+      auto* shape_dim2_tensor = Gather(input_shape_tensor, shape_dim2);
 
       std::vector<nvinfer1::ITensor*> itensors;
-      itensors.push_back(shape_dim3_tensor);
+      itensors.push_back(batch_shape_tensor);
       itensors.push_back(group_tensor);
       itensors.push_back(new_channel_shape_tensor);
+      itensors.push_back(shape_dim2_tensor);
       auto* reshape_tensor = Concat(itensors);
 
-      auto* reshape_layer =
-          TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *reshape_tensor);
-      nvinfer1::Permutation transpose_new_input{0, 3, 4, 1, 2};
-      reshape_layer->setSecondTranspose(transpose_new_input);
-
       auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *input);
-      layer->setInput(1, *(reshape_layer->getOutput(0)));
+      layer->setInput(1, *(reshape_tensor));
       nvinfer1::Permutation transpose_embed{0, 2, 1, 3, 4};
       layer->setSecondTranspose(transpose_embed);
       auto* output = layer->getOutput(0);