// See www.openfst.org for extensive documentation on this weighted
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// finite-state transducer library.
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//
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// Generates a random FST according to a class-specific transition model.
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#include <cstdlib>
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#include <cstring>
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#include <ctime>
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#include <memory>
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#include <string>
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#include <fst/flags.h>
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#include <fst/log.h>
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#include <fst/extensions/compress/randmod.h>
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#include <fst/fstlib.h>
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DEFINE_int32(seed, time(0), "Random seed");
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DEFINE_int32(states, 10, "# of states");
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DEFINE_int32(labels, 2, "# of labels");
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DEFINE_int32(classes, 1, "# of probability distributions");
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DEFINE_bool(transducer, false, "Output a transducer");
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DEFINE_bool(weights, false, "Output a weighted FST");
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int main(int argc, char **argv) {
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using fst::StdVectorFst;
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using fst::StdArc;
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using fst::TropicalWeight;
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using fst::WeightGenerate;
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string usage = "Generates a random FST.\n\n Usage: ";
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usage += argv[0];
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usage += "[out.fst]\n";
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std::set_new_handler(FailedNewHandler);
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SET_FLAGS(usage.c_str(), &argc, &argv, true);
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if (argc > 2) {
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ShowUsage();
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return 1;
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}
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string out_name = (argc > 1 && (strcmp(argv[1], "-") != 0)) ? argv[1] : "";
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srand(FLAGS_seed);
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int num_states = (rand() % FLAGS_states) + 1; // NOLINT
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int num_classes = (rand() % FLAGS_classes) + 1; // NOLINT
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int num_labels = (rand() % FLAGS_labels) + 1; // NOLINT
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StdVectorFst fst;
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using TropicalWeightGenerate = WeightGenerate<TropicalWeight>;
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std::unique_ptr<TropicalWeightGenerate> generate(FLAGS_weights ?
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new TropicalWeightGenerate(false) : nullptr);
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fst::RandMod<StdArc, TropicalWeightGenerate> rand_mod(num_states,
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num_classes, num_labels, FLAGS_transducer, generate.get());
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rand_mod.Generate(&fst);
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fst.Write(out_name);
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return 0;
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}
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