TensorFlow/test/testHelloWorld.cc

0001 /*
0002  * HelloWorld test of the TensorFlow interface.
0003  * For more info, see https://gitlab.cern.ch/mrieger/CMSSW-DNN.
0004  *
0005  * Author: Marcel Rieger
0006  */
0007
0008 #include <stdexcept>
0009 #include <cppunit/extensions/HelperMacros.h>
0010
0011 #include "tensorflow/cc/saved_model/loader.h"
0012 #include "tensorflow/cc/saved_model/tag_constants.h"
0013 #include "PhysicsTools/TensorFlow/interface/TensorFlow.h"
0014
0015 #include "testBase.h"
0016
0017 class testHelloWorld : public testBase {
0018   CPPUNIT_TEST_SUITE(testHelloWorld);
0019   CPPUNIT_TEST(test);
0020   CPPUNIT_TEST_SUITE_END();
0021
0022 public:
0023   std::string pyScript() const override;
0024   void test() override;
0025 };
0026
0027 CPPUNIT_TEST_SUITE_REGISTRATION(testHelloWorld);
0028
0029 std::string testHelloWorld::pyScript() const { return "creategraph.py"; }
0030
0031 void testHelloWorld::test() {
0032   std::string modelDir = dataPath_ + "/simplegraph";
0033   // Testing CPU
0034   std::cout << "Testing CPU backend" << std::endl;
0035   tensorflow::Backend backend = tensorflow::Backend::cpu;
0036
0037   // object to load and run the graph / session
0038   tensorflow::Status status;
0039   tensorflow::Options options{backend};
0040   tensorflow::RunOptions runOptions;
0041   tensorflow::SavedModelBundle bundle;
0042
0043   // load everything
0044   status = tensorflow::LoadSavedModel(options.getSessionOptions(), runOptions, modelDir, {"serve"}, &bundle);
0045   if (!status.ok()) {
0046     std::cout << status.ToString() << std::endl;
0047     return;
0048   }
0049
0050   // fetch the session
0051   tensorflow::Session* session = bundle.session.release();
0052
0053   // prepare inputs
0054   tensorflow::Tensor input(tensorflow::DT_FLOAT, {1, 10});
0055   float* d = input.flat<float>().data();
0056   for (size_t i = 0; i < 10; i++, d++) {
0057     *d = float(i);
0058   }
0059   tensorflow::Tensor scale(tensorflow::DT_FLOAT, {});
0060   scale.scalar<float>()() = 1.0;
0061
0062   // prepare outputs
0063   std::vector<tensorflow::Tensor> outputs;
0064
0065   // session run
0066   status = session->Run({{"input", input}, {"scale", scale}}, {"output"}, {}, &outputs);
0067   if (!status.ok()) {
0068     std::cout << status.ToString() << std::endl;
0069     return;
0070   }
0071
0072   // log the output tensor
0073   std::cout << outputs[0].DebugString() << std::endl;
0074
0075   // close the session
0076   status = session->Close();
0077   if (!status.ok()) {
0078     std::cerr << "error while closing session" << std::endl;
0079   }
0080   delete session;
0081 }