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Load a TensorFlow graph in C++
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| /* Copyright 2015 The TensorFlow 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 <cstdio> | |
| #include <functional> | |
| #include <string> | |
| #include <vector> | |
| #include "tensorflow/cc/ops/standard_ops.h" | |
| #include "tensorflow/core/framework/graph.pb.h" | |
| #include "tensorflow/core/framework/tensor.h" | |
| #include "tensorflow/core/graph/default_device.h" | |
| #include "tensorflow/core/graph/graph_def_builder.h" | |
| #include "tensorflow/core/lib/core/threadpool.h" | |
| #include "tensorflow/core/lib/strings/stringprintf.h" | |
| #include "tensorflow/core/platform/init_main.h" | |
| #include "tensorflow/core/platform/logging.h" | |
| #include "tensorflow/core/platform/types.h" | |
| #include "tensorflow/core/public/session.h" | |
| using tensorflow::string; | |
| using tensorflow::int32; | |
| namespace tensorflow | |
| { | |
| namespace example | |
| { | |
| /** | |
| Load the graph from checkpoint and graph definition files. | |
| Parameters: | |
| model_path path to the graph definition file | |
| checkpoint_name root checkpoint name. That is, if all | |
| checkpoint files are called | |
| "models/model_final.x", this should be | |
| "models/model_final". | |
| filename_tensor_name provided by the Python script. Probably | |
| something like "save/Const". Strip any ":0" | |
| off the end. | |
| restore_op_name provided by the Python script. Probably | |
| something like "save/restore_all". | |
| session a TensorFlow session | |
| scope a TensorFlow scope | |
| **/ | |
| void load(std::string model_path, std::string checkpoint_name, | |
| std::string filename_tensor_name, std::string restore_op_name, | |
| std::unique_ptr<Session> &session, tensorflow::Scope &scope) | |
| { | |
| // First create the graph specified in the graph def file | |
| GraphDef graph_def; | |
| auto load_graph_status = ReadTextProto(tensorflow::Env::Default(), model_path, | |
| &graph_def); | |
| if (!load_graph_status.ok()) | |
| { | |
| std::cout << load_graph_status.ToString() << std::endl; | |
| } | |
| auto session_status = session->Create(graph_def); | |
| if (!session_status.ok()) | |
| { | |
| std::cout << session_status.ToString() << std::endl; | |
| } | |
| // Now restore variable values using the Saver ops. | |
| std::vector<std::pair<std::string, Tensor>> input; | |
| Tensor filename_tensor = Tensor(DT_STRING, TensorShape({ 1 })); | |
| filename_tensor.vec<string>()(0) = checkpoint_name; | |
| input.emplace_back(filename_tensor_name, filename_tensor); | |
| TF_CHECK_OK(session->Run(input, {}, { restore_op_name }, {})); | |
| } | |
| } | |
| } | |
| int main() | |
| { | |
| tensorflow::SessionOptions options; | |
| std::unique_ptr<tensorflow::Session> session(NewSession(options)); | |
| tensorflow::Scope root = tensorflow::Scope::NewRootScope(); | |
| std::cout << "loading..." << std::flush; | |
| tensorflow::example::load("model/graph", "model/model_final", | |
| "save/Const", "save/restore_all", session, root); | |
| std::cout << "done." << std::endl; | |
| // Test input | |
| std::vector<std::pair<std::string, tensorflow::Tensor>> input; | |
| std::vector<tensorflow::Tensor> output; | |
| std::cout << "filling input tensor..." << std::flush; | |
| auto input_tensor = tensorflow::Tensor(tensorflow::DT_FLOAT, | |
| tensorflow::TensorShape({ 1, 72 })); | |
| auto flat = input_tensor.flat<float>(); | |
| for (int i = 0; i < 72; i++) | |
| { | |
| flat(i) = 0; | |
| } | |
| flat(71) = 1; | |
| std::cout << "done." << std::endl; | |
| input.emplace_back("input", input_tensor); | |
| std::cout << "running session..." << std::flush; | |
| TF_CHECK_OK(session->Run(input, { "output" }, {}, &output)); | |
| std::cout << "done." << std::endl; | |
| std::cout << "printing result..." << std::endl; | |
| std::cout << "[ "; | |
| for (int i = 0; i < 72; i++) | |
| { | |
| std::cout << output[0].flat<float>()(i) << " "; | |
| } | |
| std::cout << "]" << std::endl; | |
| return 0; | |
| } |
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Hi,
Could help me how I ready tensorflow for cpp? complier and heeder doesn't regnize that