Fix CI errors, address comments, update examples

DeepSpeech.py

@@ -876,11 +876,6 @@ def package_zip():
     with open(os.path.join(export_dir, 'info.json'), 'w') as f:
         json.dump({
             'name': FLAGS.export_language,
-            'parameters': {
-                'beamWidth': FLAGS.export_beam_width,
-                'lmAlpha': FLAGS.lm_alpha,
-                'lmBeta': FLAGS.lm_beta
-            }
         }, f)
 
     shutil.copy(FLAGS.scorer_path, export_dir)

native_client/java/libdeepspeech/src/androidTest/java/org/mozilla/deepspeech/libdeepspeech/test/BasicTest.java

@@ -33,8 +33,6 @@ public class BasicTest {
     public static final String scorerFile   = "/data/local/tmp/test/kenlm.scorer";
     public static final String wavFile      = "/data/local/tmp/test/LDC93S1.wav";
 
-    public static final int BEAM_WIDTH = 50;
-
     private char readLEChar(RandomAccessFile f) throws IOException {
         byte b1 = f.readByte();
         byte b2 = f.readByte();
@@ -117,7 +115,6 @@ public class BasicTest {
     @Test
     public void loadDeepSpeech_stt_noLM() {
         DeepSpeechModel m = new DeepSpeechModel(modelFile);
-        m.setBeamWidth(BEAM_WIDTH);
 
         String decoded = doSTT(m, false);
         assertEquals("she had your dark suit in greasy wash water all year", decoded);
@@ -127,7 +124,6 @@ public class BasicTest {
     @Test
     public void loadDeepSpeech_stt_withLM() {
         DeepSpeechModel m = new DeepSpeechModel(modelFile);
-        m.setBeamWidth(BEAM_WIDTH);
         m.enableExternalScorer(scorerFile);
 
         String decoded = doSTT(m, false);
@@ -138,7 +134,6 @@ public class BasicTest {
     @Test
     public void loadDeepSpeech_sttWithMetadata_noLM() {
         DeepSpeechModel m = new DeepSpeechModel(modelFile);
-        m.setBeamWidth(BEAM_WIDTH);
 
         String decoded = doSTT(m, true);
         assertEquals("she had your dark suit in greasy wash water all year", decoded);
@@ -148,7 +143,6 @@ public class BasicTest {
     @Test
     public void loadDeepSpeech_sttWithMetadata_withLM() {
         DeepSpeechModel m = new DeepSpeechModel(modelFile);
-        m.setBeamWidth(BEAM_WIDTH);
         m.enableExternalScorer(scorerFile);
 
         String decoded = doSTT(m, true);

native_client/java/libdeepspeech/src/main/java/org/mozilla/deepspeech/libdeepspeech/DeepSpeechModel.java

@@ -33,7 +33,7 @@ public class DeepSpeechModel {
     *
     * @return Beam width value used by the model.
     */
-    public int beamWidth() {
+    public long beamWidth() {
         return impl.GetModelBeamWidth(this._msp);
     }
 
@@ -45,7 +45,7 @@ public class DeepSpeechModel {
      *
      * @return Zero on success, non-zero on failure.
      */
-    public int setBeamWidth(int beamWidth) {
+    public int setBeamWidth(long beamWidth) {
         return impl.SetModelBeamWidth(this._msp, beamWidth);
     }
 

native_client/javascript/index.js

@@ -42,9 +42,8 @@ function Model(aModelPath) {
 }
 
 /**
- * Get beam width value used by the model. If {@link DS_SetModelBeamWidth}
+ * Get beam width value used by the model. If :js:func:Model.setBeamWidth was
- * was not called before, will return the default value loaded from the
+ * not called before, will return the default value loaded from the model file.
- * model file.
  *
  * @return {number} Beam width value used by the model.
  */
@@ -63,16 +62,6 @@ Model.prototype.setBeamWidth = function(aBeamWidth) {
     return binding.SetModelBeamWidth(this._impl, aBeamWidth);
 }
 
-/**
- * Return the sample rate expected by the model.
- *
- * @return {number} Sample rate.
- */
-Model.prototype.beamWidth = function() {
-    return binding.GetModelBeamWidth(this._impl);
-}
-
-
 /**
  * Return the sample rate expected by the model.
  *

native_client/python/__init__.py

@@ -45,9 +45,8 @@ class Model(object):
 
     def beamWidth(self):
         """
-        Get beam width value used by the model. If {@link DS_SetModelBeamWidth}
+        Get beam width value used by the model. If setModelBeamWidth was not
-        was not called before, will return the default value loaded from the
+        called before, will return the default value loaded from the model file.
-        model file.
 
         :return: Beam width value used by the model.
         :type: int

native_client/tflitemodelstate.cc

@@ -128,16 +128,16 @@ TFLiteModelState::init(const char* model_path)
   int metadata_sample_rate_idx      = get_output_tensor_by_name("metadata_sample_rate");
   int metadata_feature_win_len_idx  = get_output_tensor_by_name("metadata_feature_win_len");
   int metadata_feature_win_step_idx = get_output_tensor_by_name("metadata_feature_win_step");
-  int metadata_alphabet_idx = get_output_tensor_by_name("metadata_alphabet");
   int metadata_beam_width_idx = get_output_tensor_by_name("metadata_beam_width");
+  int metadata_alphabet_idx = get_output_tensor_by_name("metadata_alphabet");
 
   std::vector<int> metadata_exec_plan;
   metadata_exec_plan.push_back(find_parent_node_ids(metadata_version_idx)[0]);
   metadata_exec_plan.push_back(find_parent_node_ids(metadata_sample_rate_idx)[0]);
   metadata_exec_plan.push_back(find_parent_node_ids(metadata_feature_win_len_idx)[0]);
   metadata_exec_plan.push_back(find_parent_node_ids(metadata_feature_win_step_idx)[0]);
-  metadata_exec_plan.push_back(find_parent_node_ids(metadata_alphabet_idx)[0]);
   metadata_exec_plan.push_back(find_parent_node_ids(metadata_beam_width_idx)[0]);
+  metadata_exec_plan.push_back(find_parent_node_ids(metadata_alphabet_idx)[0]);
 
   for (int i = 0; i < metadata_exec_plan.size(); ++i) {
     assert(metadata_exec_plan[i] > -1);
@@ -202,20 +202,20 @@ TFLiteModelState::init(const char* model_path)
   audio_win_len_  = sample_rate_ * (*win_len_ms / 1000.0);
   audio_win_step_ = sample_rate_ * (*win_step_ms / 1000.0);
 
+  int* const beam_width = interpreter_->typed_tensor<int>(metadata_beam_width_idx);
+  beam_width_ = (unsigned int)(*beam_width);
+
   tflite::StringRef serialized_alphabet = tflite::GetString(interpreter_->tensor(metadata_alphabet_idx), 0);
   err = alphabet_.deserialize(serialized_alphabet.str, serialized_alphabet.len);
   if (err != 0) {
     return DS_ERR_INVALID_ALPHABET;
   }
 
-  int* const beam_width = interpreter_->typed_tensor<int>(metadata_beam_width_idx);
-  beam_width_ = (unsigned int)(*beam_width);
-
   assert(sample_rate_ > 0);
   assert(audio_win_len_ > 0);
   assert(audio_win_step_ > 0);
-  assert(alphabet_.GetSize() > 0);
   assert(beam_width_ > 0);
+  assert(alphabet_.GetSize() > 0);
 
   TfLiteIntArray* dims_input_node = interpreter_->tensor(input_node_idx_)->dims;
 

native_client/tfmodelstate.cc

@@ -102,8 +102,8 @@ TFModelState::init(const char* model_path)
     "metadata_sample_rate",
     "metadata_feature_win_len",
     "metadata_feature_win_step",
-    "metadata_alphabet",
     "metadata_beam_width",
+    "metadata_alphabet",
   }, {}, &metadata_outputs);
   if (!status.ok()) {
     std::cout << "Unable to fetch metadata: " << status << std::endl;
@@ -115,21 +115,20 @@ TFModelState::init(const char* model_path)
   int win_step_ms = metadata_outputs[2].scalar<int>()();
   audio_win_len_ = sample_rate_ * (win_len_ms / 1000.0);
   audio_win_step_ = sample_rate_ * (win_step_ms / 1000.0);
+  int beam_width = metadata_outputs[3].scalar<int>()();
+  beam_width_ = (unsigned int)(beam_width);
 
-  string serialized_alphabet = metadata_outputs[3].scalar<string>()();
+  string serialized_alphabet = metadata_outputs[4].scalar<string>()();
   err = alphabet_.deserialize(serialized_alphabet.data(), serialized_alphabet.size());
   if (err != 0) {
     return DS_ERR_INVALID_ALPHABET;
   }
 
-  int beam_width = metadata_outputs[4].scalar<int>()();
-  beam_width_ = (unsigned int)(beam_width);
-
   assert(sample_rate_ > 0);
   assert(audio_win_len_ > 0);
   assert(audio_win_step_ > 0);
-  assert(alphabet_.GetSize() > 0);
   assert(beam_width_ > 0);
+  assert(alphabet_.GetSize() > 0);
 
   for (int i = 0; i < graph_def_.node_size(); ++i) {
     NodeDef node = graph_def_.node(i);

taskcluster/examples-base.tyml

@@ -30,11 +30,11 @@ then:
     image: ${build.docker_image}
 
     env:
-      DEEPSPEECH_MODEL: "https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.1/models.tar.gz"
+      DEEPSPEECH_MODEL: "https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.1/models_beam_width.tar.gz"
       DEEPSPEECH_AUDIO: "https://github.com/mozilla/DeepSpeech/releases/download/v0.4.1/audio-0.4.1.tar.gz"
       PIP_DEFAULT_TIMEOUT: "60"
       EXAMPLES_CLONE_URL: "https://github.com/mozilla/DeepSpeech-examples"
-      EXAMPLES_CHECKOUT_TARGET: "4b97ac41d03ca0d23fa92526433db72a90f47d4a"
+      EXAMPLES_CHECKOUT_TARGET: "embedded-beam-width"
 
     command:
       - "/bin/bash"

taskcluster/win-opt-base.tyml

@@ -44,7 +44,7 @@ payload:
     MSYS: 'winsymlinks:nativestrict'
     TENSORFLOW_BUILD_ARTIFACT: ${build.tensorflow}
     EXAMPLES_CLONE_URL: "https://github.com/mozilla/DeepSpeech-examples"
-    EXAMPLES_CHECKOUT_TARGET: "4b97ac41d03ca0d23fa92526433db72a90f47d4a"
+    EXAMPLES_CHECKOUT_TARGET: "embedded-beam-width"
 
   command:
     - >-

util/flags.py

@@ -111,7 +111,7 @@ def create_flags():
     f.DEFINE_string('export_language', '', 'language the model was trained on e.g. "en" or "English". Gets embedded into exported model.')
     f.DEFINE_boolean('export_zip', False, 'export a TFLite model and package with LM and info.json')
     f.DEFINE_string('export_name', 'output_graph', 'name for the export model')
-    f.DEFINE_string('export_beam_width', 500, 'default beam width to embed into exported graph')
+    f.DEFINE_integer('export_beam_width', 500, 'default beam width to embed into exported graph')
 
     # Reporting