TensorFlow/test/testThreadPoolsCUDA.cc

0001 /*
0002  * Tests for running inference using custom thread pools.
0003  * For more info, see https://gitlab.cern.ch/mrieger/CMSSW-DNN.
0004  *
0005  * Author: Marcel Rieger
0006  */
0007
0008 #include <cppunit/extensions/HelperMacros.h>
0009 #include <stdexcept>
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   tensorflow::Options options{backend};
0055
0056   // initialize the TBB threadpool
0057   int nThreads = 4;
0058   tensorflow::TBBThreadPool::instance(nThreads);
0059   options.setThreading(nThreads);
0060
0061   // load the graph
0062   std::string pbFile = dataPath_ + "/constantgraph.pb";
0063   tensorflow::GraphDef* graphDef = tensorflow::loadGraphDef(pbFile);
0064   CPPUNIT_ASSERT(graphDef != nullptr);
0065
0066   // create a new session and add the graphDef
0067   tensorflow::Session* session = tensorflow::createSession(graphDef, options);
0068   CPPUNIT_ASSERT(session != nullptr);
0069
0070   // prepare inputs
0071   tensorflow::Tensor input(tensorflow::DT_FLOAT, {1, 10});
0072   float* d = input.flat<float>().data();
0073   for (size_t i = 0; i < 10; i++, d++) {
0074     *d = float(i);
0075   }
0076   tensorflow::Tensor scale(tensorflow::DT_FLOAT, {});
0077   scale.scalar<float>()() = 1.0;
0078
0079   // "no_threads" pool
0080   std::vector<tensorflow::Tensor> outputs;
0081   tensorflow::run(session, {{"input", input}, {"scale", scale}}, {"output"}, &outputs, "no_threads");
0082   CPPUNIT_ASSERT(outputs.size() == 1);
0083   std::cout << outputs[0].DebugString() << std::endl;
0084   CPPUNIT_ASSERT(outputs[0].matrix<float>()(0, 0) == 46.);
0085
0086   // "tbb" pool
0087   outputs.clear();
0088   tensorflow::run(session, {{"input", input}, {"scale", scale}}, {"output"}, &outputs, "tbb");
0089   CPPUNIT_ASSERT(outputs.size() == 1);
0090   std::cout << outputs[0].DebugString() << std::endl;
0091   CPPUNIT_ASSERT(outputs[0].matrix<float>()(0, 0) == 46.);
0092
0093   // tensorflow defaut pool using a new session
0094   tensorflow::Session* session2 = tensorflow::createSession(graphDef, options);
0095   CPPUNIT_ASSERT(session != nullptr);
0096   outputs.clear();
0097   tensorflow::run(session2, {{"input", input}, {"scale", scale}}, {"output"}, &outputs, "tensorflow");
0098   CPPUNIT_ASSERT(outputs.size() == 1);
0099   std::cout << outputs[0].DebugString() << std::endl;
0100   CPPUNIT_ASSERT(outputs[0].matrix<float>()(0, 0) == 46.);
0101
0102   // force an exception
0103   CPPUNIT_ASSERT_THROW(
0104       tensorflow::run(session, {{"input", input}, {"scale", scale}}, {"output"}, &outputs, "not_existing"),
0105       cms::Exception);
0106
0107   // cleanup
0108   CPPUNIT_ASSERT(tensorflow::closeSession(session));
0109   CPPUNIT_ASSERT(tensorflow::closeSession(session2));
0110   delete graphDef;
0111 }