Merge pull request #74 from cms-ml/tf_aot_docs

TF AOT documentation.

content/inference/code/tensorflow_aot/tensorflow_aot_buildfile.xml

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+<use name="FWCore/Framework" />
+<use name="FWCore/PluginManager" />
+<use name="FWCore/ParameterSet" />
+
+<use name="PhysicsTools/TensorFlowAOT" />
+<use name="tfaot-model-test"/>
+
+<flags EDM_PLUGIN="1" />

content/inference/code/tensorflow_aot/tensorflow_aot_cfg.py

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+# coding: utf-8
+
+import os
+
+import FWCore.ParameterSet.Config as cms
+from FWCore.ParameterSet.VarParsing import VarParsing
+
+
+# get the data/ directory
+thisdir = os.path.dirname(os.path.abspath(__file__))
+datadir = os.path.join(os.path.dirname(thisdir), "data")
+
+# setup minimal options
+options = VarParsing("python")
+options.setDefault("inputFiles", "root://xrootd-cms.infn.it//store/mc/RunIISummer20UL18MiniAODv2/GluGluToHHTo2G2Tau_node_cHHH1_TuneCP5_13TeV-powheg-pythia8/MINIAODSIM/106X_upgrade2018_realistic_v16_L1v1-v2/40000/871B714B-0AA3-3342-B56C-6DC0E634593A.root")  # noqa
+options.parseArguments()
+
+# define the process to run
+process = cms.Process("TEST")
+
+# minimal configuration
+process.load("FWCore.MessageService.MessageLogger_cfi")
+process.MessageLogger.cerr.FwkReport.reportEvery = 1
+process.maxEvents = cms.untracked.PSet(
+    input=cms.untracked.int32(10),
+)
+process.source = cms.Source(
+    "PoolSource",
+    fileNames=cms.untracked.vstring(options.inputFiles),
+)
+
+# process options
+process.options = cms.untracked.PSet(
+    allowUnscheduled=cms.untracked.bool(True),
+    wantSummary=cms.untracked.bool(True),
+)
+
+# setup MyPlugin by loading the auto-generated cfi (see MyPlugin.fillDescriptions)
+process.load("MySubsystem.MyModule.myPlugin_cfi")
+# register three batch rules
+# - add 1+1+1 for batch size 3
+# - add 4+1 for batch size 5
+# - add 4+4 for batch size 6, using a padding of 2 for the second call
+process.myPlugin.batchRules = cms.vstring(["3:1,1,1", "5:4,1", "6:4,4"])
+
+# define what to run in the path
+process.p = cms.Path(process.myPlugin)

content/inference/code/tensorflow_aot/tensorflow_aot_plugin.cpp

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+/*
+ * Example plugin to demonstrate the inference with TensorFlow AOT.
+ */
+
+#include <memory>
+
+#include "FWCore/Framework/interface/Event.h"
+#include "FWCore/Framework/interface/Frameworkfwd.h"
+#include "FWCore/Framework/interface/MakerMacros.h"
+#include "FWCore/Framework/interface/stream/EDAnalyzer.h"
+#include "FWCore/ParameterSet/interface/ParameterSet.h"
+#include "PhysicsTools/TensorFlowAOT/interface/Model.h"
+
+// include the header of the compiled model
+#include "tfaot-model-test/model.h"
+
+class MyPlugin : public edm::stream::EDAnalyzer<> {
+public:
+  explicit MyPlugin(const edm::ParameterSet&);
+  ~MyPlugin(){};
+
+  static void fillDescriptions(edm::ConfigurationDescriptions&);
+
+private:
+  void beginJob(){};
+  void analyze(const edm::Event&, const edm::EventSetup&);
+  void endJob(){};
+
+  std::vector<std::string> batchRuleStrings_;
+
+  // aot model
+  tfaot::Model<tfaot_model::test> model_;
+};
+
+void MyPlugin::fillDescriptions(edm::ConfigurationDescriptions& descriptions) {
+  // defining this function will lead to a *_cfi file being generated when compiling
+  edm::ParameterSetDescription desc;
+  desc.add<std::vector<std::string>>("batchRules");
+  descriptions.addWithDefaultLabel(desc);
+}
+
+MyPlugin::MyPlugin(const edm::ParameterSet& config)
+    : batchRuleStrings_(config.getParameter<std::vector<std::string>>("batchRules")) {
+  // register batch rules
+  for (const auto& rule : batchRuleStrings_) {
+    model_.setBatchRule(rule);
+  }
+}
+
+void MyPlugin::analyze(const edm::Event& event, const edm::EventSetup& setup) {
+  // define input for a batch size of 1
+  // (just a single float input, with shape 1x4)
+  tfaot::FloatArrays input = { {0, 1, 2, 3} };
+
+  // define output
+  // (just a single float output, which will shape 1x2)
+  tfaot::FloatArrays output;
+
+  // evaluate the model
+  // the template arguments of run() correspond to the types of the outputs
+  // that are "tied" the "1" denote the batch size of 1
+  std::tie(output) = model_.run<tfaot::FloatArrays>(1, input);
+
+  // print output
+  std::cout << "output[0]: " << output[0][0] << ", " << output[0][1] << std::endl;
+  // -> "output[0]: 0.648093, 0.351907"
+}
+
+DEFINE_FWK_MODULE(MyPlugin);