TensorFlow/test/testGraphLoadingCUDA.cc

0001 /*
0002  * Tests for loading graphs via the converted protobuf files.
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 "PhysicsTools/TensorFlow/interface/TensorFlow.h"
0012
0013 #include "testBaseCUDA.h"
0014
0015 class testGraphLoadingCUDA : public testBaseCUDA {
0016   CPPUNIT_TEST_SUITE(testGraphLoadingCUDA);
0017   CPPUNIT_TEST(test);
0018   CPPUNIT_TEST_SUITE_END();
0019
0020 public:
0021   std::string pyScript() const override;
0022   void test() override;
0023 };
0024
0025 CPPUNIT_TEST_SUITE_REGISTRATION(testGraphLoadingCUDA);
0026
0027 std::string testGraphLoadingCUDA::pyScript() const { return "createconstantgraph.py"; }
0028
0029 void testGraphLoadingCUDA::test() {
0030   if (!cms::cudatest::testDevices())
0031     return;
0032
0033   std::vector<edm::ParameterSet> psets;
0034   edm::ServiceToken serviceToken = edm::ServiceRegistry::createSet(psets);
0035   edm::ServiceRegistry::Operate operate(serviceToken);
0036
0037   // Setup the CUDA Service
0038   edmplugin::PluginManager::configure(edmplugin::standard::config());
0039
0040   std::string const config = R"_(import FWCore.ParameterSet.Config as cms
0041 process = cms.Process('Test')
0042 process.add_(cms.Service('ResourceInformationService'))
0043 process.add_(cms.Service('CUDAService'))
0044 )_";
0045   std::unique_ptr<edm::ParameterSet> params;
0046   edm::makeParameterSets(config, params);
0047   edm::ServiceToken tempToken(edm::ServiceRegistry::createServicesFromConfig(std::move(params)));
0048   edm::ServiceRegistry::Operate operate2(tempToken);
0049   edm::Service<CUDAInterface> cuda;
0050   std::cout << "CUDA service enabled: " << cuda->enabled() << std::endl;
0051
0052   std::cout << "Testing CUDA backend" << std::endl;
0053   tensorflow::Backend backend = tensorflow::Backend::cuda;
0054
0055   // load the graph
0056   std::string pbFile = dataPath_ + "/constantgraph.pb";
0057   tensorflow::Options options{backend};
0058   tensorflow::GraphDef* graphDef = tensorflow::loadGraphDef(pbFile);
0059   CPPUNIT_ASSERT(graphDef != nullptr);
0060
0061   // create a new session and add the graphDef
0062   tensorflow::Session* session = tensorflow::createSession(graphDef, options);
0063   CPPUNIT_ASSERT(session != nullptr);
0064
0065   // check for exception
0066   CPPUNIT_ASSERT_THROW(tensorflow::createSession(nullptr, options), cms::Exception);
0067
0068   // example evaluation
0069   tensorflow::Tensor input(tensorflow::DT_FLOAT, {1, 10});
0070   float* d = input.flat<float>().data();
0071   for (size_t i = 0; i < 10; i++, d++) {
0072     *d = float(i);
0073   }
0074   tensorflow::Tensor scale(tensorflow::DT_FLOAT, {});
0075   scale.scalar<float>()() = 1.0;
0076
0077   std::vector<tensorflow::Tensor> outputs;
0078   tensorflow::Status status = session->Run({{"input", input}, {"scale", scale}}, {"output"}, {}, &outputs);
0079   if (!status.ok()) {
0080     std::cout << status.ToString() << std::endl;
0081     CPPUNIT_ASSERT(false);
0082   }
0083
0084   // check the output
0085   CPPUNIT_ASSERT(outputs.size() == 1);
0086   std::cout << outputs[0].DebugString() << std::endl;
0087   CPPUNIT_ASSERT(outputs[0].matrix<float>()(0, 0) == 46.);
0088
0089   // run again using the convenience helper
0090   outputs.clear();
0091   tensorflow::run(session, {{"input", input}, {"scale", scale}}, {"output"}, &outputs);
0092   CPPUNIT_ASSERT(outputs.size() == 1);
0093   std::cout << outputs[0].DebugString() << std::endl;
0094   CPPUNIT_ASSERT(outputs[0].matrix<float>()(0, 0) == 46.);
0095
0096   // check for exception
0097   CPPUNIT_ASSERT_THROW(tensorflow::run(session, {{"foo", input}}, {"output"}, &outputs), cms::Exception);
0098
0099   // cleanup
0100   CPPUNIT_ASSERT(tensorflow::closeSession(session));
0101   CPPUNIT_ASSERT(session == nullptr);
0102   delete graphDef;
0103 }