diff --git a/paddle/fluid/inference/tensorrt/convert/pool2d_op.cc b/paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
index 11cad95361867476c6f775af778015da37f1cfb1..73f1b28ddf73403862e55d102a259d7b6cf67b1f 100644
--- a/paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
@@ -33,6 +33,7 @@ class Pool2dOpConverter : public OpConverter {
     PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1);
     auto* input1 = engine_->GetITensor(op_desc.Input("X")[0]);
 
+    bool global_pooling = boost::get<bool>(op_desc.GetAttr("global_pooling"));
     std::string pool_type =
         boost::get<std::string>(op_desc.GetAttr("pooling_type"));
     std::vector<int> ksize =
@@ -42,7 +43,13 @@ class Pool2dOpConverter : public OpConverter {
     std::vector<int> paddings =
         boost::get<std::vector<int>>(op_desc.GetAttr("paddings"));
 
-    const nvinfer1::DimsHW nv_ksize(ksize[0], ksize[1]);
+    nvinfer1::DimsHW nv_ksize(ksize[0], ksize[1]);
+    if (global_pooling == true) {
+      nvinfer1::Dims input_shape = input1->getDimensions();
+      int nbDims = input_shape.nbDims;
+      nv_ksize.d[0] = input_shape.d[nbDims - 2];
+      nv_ksize.d[1] = input_shape.d[nbDims - 1];
+    }
     const nvinfer1::DimsHW nv_strides(strides[0], strides[1]);
     const nvinfer1::DimsHW nv_paddings(paddings[0], paddings[1]);
 
diff --git a/paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc b/paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
index c5dddbc8cd37b9fb1ba39382af2da5ad045f3af2..aedd6b62df040eeee4e48f628128511cd8bf4439 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
@@ -20,7 +20,7 @@ namespace paddle {
 namespace inference {
 namespace tensorrt {
 
-TEST(Pool2dOpConverter, main) {
+void test_pool2d(bool global_pooling) {
   framework::Scope scope;
   std::unordered_set<std::string> parameters;
   TRTConvertValidation validator(5, parameters, scope, 1 << 15);
@@ -28,7 +28,10 @@ TEST(Pool2dOpConverter, main) {
   // The ITensor's Dims should not contain the batch size.
   // So, the ITensor's Dims of input and output should be C * H * W.
   validator.DeclInputVar("pool2d-X", nvinfer1::Dims3(3, 4, 4));
-  validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 2, 2));
+  if (global_pooling)
+    validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 1, 1));
+  else
+    validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 2, 2));
 
   // Prepare Op description
   framework::OpDesc desc;
@@ -45,6 +48,7 @@ TEST(Pool2dOpConverter, main) {
   desc.SetAttr("ksize", ksize);
   desc.SetAttr("strides", strides);
   desc.SetAttr("paddings", paddings);
+  desc.SetAttr("global_pooling", global_pooling);
 
   LOG(INFO) << "set OP";
   validator.SetOp(*desc.Proto());
@@ -53,6 +57,10 @@ TEST(Pool2dOpConverter, main) {
   validator.Execute(3);
 }
 
+TEST(Pool2dOpConverter, normal) { test_pool2d(false); }
+
+TEST(Pool2dOpConverter, test_global_pooling) { test_pool2d(true); }
+
 }  // namespace tensorrt
 }  // namespace inference
 }  // namespace paddle