Moved result limiting to ModelState instead of CTC decoder

native_client/ctcdecode/ctc_beam_search_decoder.cpp

@@ -157,7 +157,7 @@ DecoderState::next(const double *probs,
 }
 
 std::vector<Output>
-DecoderState::decode(size_t top_paths) const
+DecoderState::decode() const
 {
   std::vector<PathTrie*> prefixes_copy = prefixes_;
   std::unordered_map<const PathTrie*, float> scores;
@@ -167,7 +167,7 @@ DecoderState::decode(size_t top_paths) const
 
   // score the last word of each prefix that doesn't end with space
   if (ext_scorer_) {
-    for (size_t i = 0; i < top_paths && i < prefixes_copy.size(); ++i) {
+    for (size_t i = 0; i < beam_size_ && i < prefixes_copy.size(); ++i) {
       auto prefix = prefixes_copy[i];
       if (!ext_scorer_->is_scoring_boundary(prefix->parent, prefix->character)) {
         float score = 0.0;
@@ -181,13 +181,13 @@ DecoderState::decode(size_t top_paths) const
   }
 
   using namespace std::placeholders;
-  size_t num_prefixes = std::min(prefixes_copy.size(), top_paths);
+  size_t num_prefixes = std::min(prefixes_copy.size(), beam_size_);
   std::partial_sort(prefixes_copy.begin(),
                     prefixes_copy.begin() + num_prefixes,
                     prefixes_copy.end(),
                     std::bind(prefix_compare_external, _1, _2, scores));
 
-  size_t num_returned = std::min(num_prefixes, top_paths);
+  size_t num_returned = std::min(num_prefixes, beam_size_);
 
   std::vector<Output> outputs;
   outputs.reserve(num_returned);
@@ -218,7 +218,6 @@ std::vector<Output> ctc_beam_search_decoder(
     int class_dim,
     const Alphabet &alphabet,
     size_t beam_size,
-    size_t top_paths,
     double cutoff_prob,
     size_t cutoff_top_n,
     std::shared_ptr<Scorer> ext_scorer)
@@ -226,7 +225,7 @@ std::vector<Output> ctc_beam_search_decoder(
   DecoderState state;
   state.init(alphabet, beam_size, cutoff_prob, cutoff_top_n, ext_scorer);
   state.next(probs, time_dim, class_dim);
-  return state.decode(top_paths);
+  return state.decode();
 }
 
 std::vector<std::vector<Output>>
@@ -239,7 +238,6 @@ ctc_beam_search_decoder_batch(
     int seq_lengths_size,
     const Alphabet &alphabet,
     size_t beam_size,
-    size_t top_paths,
     size_t num_processes,
     double cutoff_prob,
     size_t cutoff_top_n,
@@ -259,7 +257,6 @@ ctc_beam_search_decoder_batch(
                                   class_dim,
                                   alphabet,
                                   beam_size,
-                                  top_paths,
                                   cutoff_prob,
                                   cutoff_top_n,
                                   ext_scorer));

native_client/deepspeech.cc

@@ -148,21 +148,7 @@ StreamingState::finishStreamWithMetadata(unsigned int num_results)
 {
   finalizeStream();
 
-  vector<Metadata*> metadata = model_->decode_metadata(decoder_state_, numResults);
+  return model_->decode_metadata(decoder_state_, num_results);
-
-  std::unique_ptr<Result> result(new Result());
-  result->num_transcriptions = metadata.size();
-
-  std::unique_ptr<Metadata[]> items(new Metadata[result->num_transcriptions]);
-
-  for (int i = 0; i < result->num_transcriptions; ++i) {
-      std::unique_ptr<Metadata> pointer(new Metadata(*metadata[i]));
-      items[i] = *pointer.release();
-  }
-
-  result->transcriptions = items.release();
-
-  return result.release();
 }
 
 void

native_client/modelstate.cc

@@ -32,22 +32,25 @@ ModelState::init(const char* model_path)
 char*
 ModelState::decode(const DecoderState& state) const
 {
-  vector<Output> out = state.decode(1);
+  vector<Output> out = state.decode();
   return strdup(alphabet_.LabelsToString(out[0].tokens).c_str());
 }
 
-vector<Metadata*>
+Result*
 ModelState::decode_metadata(const DecoderState& state, 
-                            size_t top_paths)
+                            size_t num_results)
 {
-  vector<Output> out = state.decode(top_paths);
+  vector<Output> out = state.decode();
 
-  vector<Metadata*> meta_out;
+  size_t max_results = std::min(num_results, out.size());
 
-  size_t max_results = std::min(top_paths, out.size());
+  std::unique_ptr<Result> result(new Result());
+  result->num_transcriptions = max_results;
+
+  std::unique_ptr<Metadata[]> transcripts(new Metadata[max_results]());
 
   for (int j = 0; j < max_results; ++j) {
-    std::unique_ptr<Metadata> metadata(new Metadata());
+    Metadata* metadata = &transcripts[j];
     metadata->num_items = out[j].tokens.size();
     metadata->confidence = out[j].confidence;
 
@@ -65,8 +68,9 @@ ModelState::decode_metadata(const DecoderState& state,
     }
 
     metadata->items = items.release();
-    meta_out.push_back(metadata.release());
   }
 
-  return meta_out;
+  result->transcriptions = transcripts.release();
+
+  return result.release();
 }

native_client/modelstate.h

@@ -66,14 +66,14 @@ struct ModelState {
    * @brief Return character-level metadata including letter timings.
    *
    * @param state Decoder state to use when decoding.
-   * @param top_paths Number of alternate results to return.   
+   * @param num_results Number of alternate results to return.   
    *
-   * @return Vector of Metadata structs containing MetadataItem structs for each character.
+   * @return A Result struct containing Metadata structs.
    * Each represents an alternate transcription, with the first ranked most probable.
-   * The user is responsible for freeing Metadata by calling DS_FreeMetadata() on each item.
+   * The user is responsible for freeing Result by calling DS_FreeResult().
    */
-  virtual std::vector<Metadata*> decode_metadata(const DecoderState& state, 
+  virtual Result* decode_metadata(const DecoderState& state, 
-                                                 size_t top_paths);
+                                                 size_t num_results);
 };
 
 #endif // MODELSTATE_H