add Temporarily add code with bug

paddle/fluid/inference/tensorrt/convert/CMakeLists.txt

 # Add TRT tests
 nv_library(tensorrt_converter
-  SRCS mul_op.cc conv2d_op.cc fc_op.cc
+  SRCS mul_op.cc conv2d_op.cc fc_op.cc pool2d_op.cc
   DEPS tensorrt_engine mul_op)
 
 nv_test(test_op_converter SRCS test_op_converter.cc DEPS
@@ -13,3 +13,6 @@ nv_test(test_trt_fc_op SRCS test_fc_op.cc fc_op.cc
         DEPS ${FLUID_CORE_MODULES} tensorrt_engine mul_op SERIAL)
 nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc
         DEPS ${FLUID_CORE_MODULES} tensorrt_engine activation_op SERIAL)
+
+nv_test(test_trt_pool2d_op SRCS test_pool2d_op.cc pool2d_op.cc
+        DEPS ${FLUID_CORE_MODULES} tensorrt_engine pool_op SERIAL)

paddle/fluid/inference/tensorrt/convert/pool2d_op.cc

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
+
+namespace paddle {
+namespace inference {
+namespace tensorrt {
+
+/*
+ * Pool2dOp, IPoolingLayer in TRT. This Layer doesn't has weights.
+ */
+class Pool2dOpConverter : public OpConverter {
+ public:
+  void operator()(const framework::proto::OpDesc& op,
+                  const framework::Scope& scope, bool test_mode) override {
+    VLOG(4)
+        << "convert a fluid pool2d op to tensorrt pool2d layer without bias";
+    framework::OpDesc op_desc(op, nullptr);
+    // Declare inputs
+    auto* input1 = engine_->GetITensor(op_desc.Input("X")[0]);
+    std::string pool_type =
+        boost::get<std::string>(op_desc.GetAttr("pooling_type"));
+    std::vector<int> ksize =
+        boost::get<std::vector<int>>(op_desc.GetAttr("ksize"));
+    std::vector<int> strides =
+        boost::get<std::vector<int>>(op_desc.GetAttr("strides"));
+    std::vector<int> paddings =
+        boost::get<std::vector<int>>(op_desc.GetAttr("paddings"));
+
+    const nvinfer1::DimsHW nv_ksize(ksize[0], ksize[1]);
+    const nvinfer1::DimsHW nv_strides(strides[0], strides[1]);
+    const nvinfer1::DimsHW nv_paddings(paddings[0], paddings[1]);
+
+    nvinfer1::PoolingType pool_t = nvinfer1::PoolingType::kMAX;
+    if (pool_type == "max") {
+      pool_t = nvinfer1::PoolingType::kMAX;
+    } else if (pool_type == "avg") {
+      pool_t = nvinfer1::PoolingType::kAVERAGE;
+    } else {
+      PADDLE_THROW("TensorRT unsupported pooling type!");
+    }
+
+    auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Pooling,
+                                       *const_cast<nvinfer1::ITensor*>(input1),
+                                       pool_t, nv_ksize);
+    PADDLE_ENFORCE_NOT_NULL(layer, "pool layer could not be created.");
+    layer->setStride(nv_strides);
+    layer->setPadding(nv_paddings);
+
+    auto output_name = op_desc.Output("Out")[0];
+    engine_->SetITensor(output_name, layer->getOutput(0));
+    if (test_mode) {
+      engine_->DeclareOutput(output_name);
+    }
+  }
+};
+
+}  // namespace tensorrt
+}  // namespace inference
+}  // namespace paddle
+
+USE_OP(pool2d);
+REGISTER_TRT_OP_CONVERTER(pool2d, Pool2dOpConverter);

paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License. */
+#include <gtest/gtest.h>
+#include <fstream>
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
+
+namespace paddle {
+namespace inference {
+namespace tensorrt {
+
+TEST(Pool2dOpConverter, main) {
+  framework::Scope scope;
+  std::unordered_set<std::string> parameters;
+  TRTConvertValidation validator(10, parameters, scope, 1000);
+  validator.DeclInputVar("pool2d-X", nvinfer1::Dims4(10, 3, 2, 2));
+  validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims4(10, 3, 1, 1));
+
+  // Prepare Op description
+  framework::OpDesc desc;
+  desc.SetType("pool2d");
+  desc.SetInput("X", {"pool2d-X"});
+  desc.SetOutput("Out", {"pool2d-Out"});
+
+  std::vector<int> ksize({2, 2});
+  std::vector<int> strides({1, 1});
+  std::vector<int> paddings({0, 0});
+  std::string pooling_t = "max";
+
+  desc.SetAttr("pooling_type", pooling_t);
+  desc.SetAttr("ksize", ksize);
+  desc.SetAttr("strides", strides);
+  desc.SetAttr("paddings", paddings);
+  // std::string temp = "";
+  // (*desc.Proto()).SerializeToString(&temp);
+
+  // std::cout << temp << std::endl;
+  // std::ofstream f("__temp__", std::ios::out);
+  // f << temp;
+
+  LOG(INFO) << "set OP";
+  validator.SetOp(*desc.Proto());
+  LOG(INFO) << "execute";
+
+  validator.Execute(10);
+}
+
+}  // namespace tensorrt
+}  // namespace inference
+}  // namespace paddle
+
+USE_OP(pool2d);