// Copyright (c) 2019 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/op_teller.h" namespace paddle { namespace inference { namespace tensorrt { // Just tell by the op_types. struct SimpleOpTypeSetTeller : public Teller { SimpleOpTypeSetTeller() { #if IS_TRT_VERSION_GE(5130) teller_set.insert("relu6"); #endif } bool operator()(const std::string& op_type, const framework::OpDesc& desc) override { return teller_set.count(op_type); } private: std::unordered_set teller_set{{"mul", "conv2d", "pool2d", "relu", "softmax", "sigmoid", "depthwise_conv2d", "batch_norm", "concat", "tanh", "pad", "elementwise_add", "elementwise_mul", "dropout", "prelu", "conv2d_transpose", "leaky_relu", "fc", "shuffle_channel", "swish", "split"}}; }; bool OpTeller::Tell(const std::string& op_type, const framework::OpDesc& desc) { for (auto& teller : tellers_) { if (op_type == "pool2d" || op_type == "conv2d" || op_type == "depthwise_conv2d" || op_type == "conv2d_transpose") { std::vector paddings = boost::get>(desc.GetAttr("paddings")); if (paddings.size() > 2) return false; } if ((*teller)(op_type, desc)) return true; } return false; } OpTeller::OpTeller() { tellers_.emplace_back(new SimpleOpTypeSetTeller); } } // namespace tensorrt } // namespace inference } // namespace paddle