/* 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 #include #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/inference/tensorrt/convert/ut_helper.h" namespace paddle { namespace inference { namespace tensorrt { void test_pool2d(bool global_pooling) { framework::Scope scope; std::unordered_set parameters; TRTConvertValidation validator(5, parameters, scope, 1 << 15); // 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)); 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; desc.SetType("pool2d"); desc.SetInput("X", {"pool2d-X"}); desc.SetOutput("Out", {"pool2d-Out"}); std::vector ksize({2, 2}); std::vector strides({2, 2}); std::vector 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); desc.SetAttr("global_pooling", global_pooling); LOG(INFO) << "set OP"; validator.SetOp(*desc.Proto()); LOG(INFO) << "execute"; validator.Execute(3); } TEST(Pool2dOpConverter, normal) { test_pool2d(false); } TEST(Pool2dOpConverter, test_global_pooling) { test_pool2d(true); } } // namespace tensorrt } // namespace inference } // namespace paddle USE_OP(pool2d);