diff --git a/paddle/fluid/inference/tensorrt/plugin/pool_op_plugin.cu b/paddle/fluid/inference/tensorrt/plugin/pool_op_plugin.cu
index 21eb89d135efa654b0f0f894980f68393f7cadea..52959d8f90b6d1c587b4e25347e29030dcb6981f 100644
--- a/paddle/fluid/inference/tensorrt/plugin/pool_op_plugin.cu
+++ b/paddle/fluid/inference/tensorrt/plugin/pool_op_plugin.cu
@@ -321,16 +321,16 @@ int PoolPluginDynamic::enqueue(const nvinfer1::PluginTensorDesc *input_desc,
     paddings[1] = 0;
     output_shape[2] = 1;
     output_shape[3] = 1;
+    if (adaptive_) {
+      output_shape[2] = h;
+      output_shape[3] = w;
+    }
   } else {
     auto data_dim = CalcOutputSize(
         {h, w}, ceil_mode_, adaptive_, ksize_, strides_, paddings_);
     output_shape[2] = data_dim[0];
     output_shape[3] = data_dim[1];
   }
-  if (adaptive_) {
-    output_shape[2] = h;
-    output_shape[3] = w;
-  }
 
   if (pool_type_ == "max") {
     phi::funcs::MaxPool<float> pool_process;
diff --git a/paddle/phi/kernels/funcs/pooling.cu b/paddle/phi/kernels/funcs/pooling.cu
index 875fa92002a43680eda8441adb3a2c19fc96553b..a1bb927b73e07eab17ac6daed405c6e679855586 100644
--- a/paddle/phi/kernels/funcs/pooling.cu
+++ b/paddle/phi/kernels/funcs/pooling.cu
@@ -460,7 +460,6 @@ void Pool2dDirectCUDAFunctor<PoolProcess, T>::operator()(
   const int stride_width = strides[1];
   const int padding_height = paddings[0];
   const int padding_width = paddings[1];
-
   int nthreads = batch_size * output_channels * output_height * output_width;
   auto pool_divmods =
       FastDivModForPooling(input_channels, output_width, output_height);
@@ -491,6 +490,7 @@ void Pool2dDirectCUDAFunctor<PoolProcess, T>::operator()(
                                        pool_compute,
                                        exclusive,
                                        output);
+
   } else {
     int thread_num = 1024;
 #ifdef WITH_NV_JETSON