diff --git a/paddle/fluid/inference/tensorrt/plugin/layer_norm_op_plugin.cu b/paddle/fluid/inference/tensorrt/plugin/layer_norm_op_plugin.cu
index 9b0fa45c337733028367bfb1b155b769a5702029..48b9d3229c38c0599124134af221b0dcc41d6d1b 100644
--- a/paddle/fluid/inference/tensorrt/plugin/layer_norm_op_plugin.cu
+++ b/paddle/fluid/inference/tensorrt/plugin/layer_norm_op_plugin.cu
@@ -177,9 +177,20 @@ int LayerNormPluginDynamic::enqueue(
   }
   // in dynamic shape
   // the batch num should be involved in mean/variance shape
-  mean_shape_[0] *= input_dims.d[0];
-  variance_shape_[0] *= input_dims.d[0];
-
+  PADDLE_ENFORCE_EQ(1,
+                    mean_shape_.size(),
+                    platform::errors::InvalidArgument(
+                        "Size of mean_shape vector should be equal to 1,"
+                        "but got Size of mean_shape vector:%d",
+                        mean_shape_.size()));
+  PADDLE_ENFORCE_EQ(1,
+                    variance_shape_.size(),
+                    platform::errors::InvalidArgument(
+                        "Size of variance_shape vector should be equal to 1,"
+                        "but got Size of mean_shape vector:%d",
+                        mean_shape_.size()));
+  int64_t batched_mean_shape = mean_shape_[0] * input_dims.d[0];
+  int64_t batched_variance_shape = variance_shape_[0] * input_dims.d[0];
   const auto input_ddim = phi::make_ddim(input_shape);
   auto matrix_dim = phi::flatten_to_2d(input_ddim, begin_norm_axis);
   int feature_size = static_cast<int>(matrix_dim[1]);
@@ -206,8 +217,8 @@ int LayerNormPluginDynamic::enqueue(
     float *output = static_cast<float *>(outputs[0]);
     scale_t.Resize(phi::make_ddim({feature_size}));
     bias_t.Resize(phi::make_ddim({feature_size}));
-    mean_t.Resize(phi::make_ddim(mean_shape_));
-    variance_t.Resize(phi::make_ddim(variance_shape_));
+    mean_t.Resize(phi::make_ddim({batched_mean_shape}));
+    variance_t.Resize(phi::make_ddim({batched_variance_shape}));
 
     float *scale_d =
         scale_t.mutable_data<float>(platform::CUDAPlace(device_id));