Class Advisor

tensorflow/core/profiler/internal/advisor/tfprof_advisor.h:30–76

The Advisor runs a list of Checkers, each checks a specific area.

// The Advisor runs a list of Checkers, each checks a specific area.
class Advisor {
 public:
  Advisor(const TFStats* stats) : stats_(stats) {}

  static AdvisorOptionsProto DefaultOptions() {
    AdvisorOptionsProto options;
    std::vector<string> checkers(
        kCheckers, kCheckers + sizeof(kCheckers) / sizeof(*kCheckers));
    for (const string& checker : checkers) {
      (*options.mutable_checkers())[checker];
    }
    return options;
  }

  AdviceProto Advise(const AdvisorOptionsProto& options) {
    // Note: Release a checker's memory ASAP.
    AdviceProto ret = RunInternalCheckers(options, stats_);

    if (options.checkers().find(kCheckers[0]) != options.checkers().end()) {
      AcceleratorUtilizationChecker au_checker;
      (*ret.mutable_checkers())[kCheckers[0]].MergeFrom(
          au_checker.Run(options.checkers().at(kCheckers[0]), stats_));
    }
    if (options.checkers().find(kCheckers[1]) != options.checkers().end()) {
      OperationChecker op_checker;
      (*ret.mutable_checkers())[kCheckers[1]].MergeFrom(
          op_checker.Run(options.checkers().at(kCheckers[1]), stats_));
    }
    if (options.checkers().find(kCheckers[2]) != options.checkers().end()) {
      ExpensiveOperationChecker expensive_op_checker;
      (*ret.mutable_checkers())[kCheckers[2]].MergeFrom(
          expensive_op_checker.Run(options.checkers().at(kCheckers[2]),
                                   stats_));
    }
    for (const auto& checker : ret.checkers()) {
      fprintf(stdout, "\n%s:\n", checker.first.c_str());
      for (const string& r : checker.second.reports()) {
        fprintf(stdout, "%s\n", r.c_str());
      }
    }
    fflush(stdout);
    return ret;
  }

 private:
  const TFStats* stats_;
};

}  // namespace tfprof
}  // namespace tensorflow