Merge branch 'dev' of https://github.com/mozilla/TTS into dev

server/server.py

@@ -18,9 +18,9 @@ def create_argparser():
     parser.add_argument('--wavernn_file', type=str, default=None, help='path to WaveRNN checkpoint file.')
     parser.add_argument('--wavernn_config', type=str, default=None, help='path to WaveRNN config file.')
     parser.add_argument('--is_wavernn_batched', type=convert_boolean, default=False, help='true to use batched WaveRNN.')
-    parser.add_argument('--pwgan_lib_path', type=str, help='path to ParallelWaveGAN project folder to be imported. If this is not passed, model uses Griffin-Lim for synthesis.')
-    parser.add_argument('--pwgan_file', type=str, help='path to ParallelWaveGAN checkpoint file.')
-    parser.add_argument('--pwgan_config', type=str, help='path to ParallelWaveGAN config file.')
+    parser.add_argument('--pwgan_lib_path', type=str, default=None, help='path to ParallelWaveGAN project folder to be imported. If this is not passed, model uses Griffin-Lim for synthesis.')
+    parser.add_argument('--pwgan_file', type=str, default=None, help='path to ParallelWaveGAN checkpoint file.')
+    parser.add_argument('--pwgan_config', type=str, default=None, help='path to ParallelWaveGAN config file.')
     parser.add_argument('--port', type=int, default=5002, help='port to listen on.')
     parser.add_argument('--use_cuda', type=convert_boolean, default=False, help='true to use CUDA.')
     parser.add_argument('--debug', type=convert_boolean, default=False, help='true to enable Flask debug mode.')
@@ -29,28 +29,35 @@ def create_argparser():
 
 synthesizer = None
 
-embedded_model_folder = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'model')
-checkpoint_file = os.path.join(embedded_model_folder, 'checkpoint.pth.tar')
-config_file = os.path.join(embedded_model_folder, 'config.json')
+embedded_models_folder = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'model')
 
-# Default options with embedded model files
-if os.path.isfile(checkpoint_file):
-    default_tts_checkpoint = checkpoint_file
-else:
-    default_tts_checkpoint = None
+embedded_tts_folder = os.path.join(embedded_models_folder, 'tts')
+tts_checkpoint_file = os.path.join(embedded_tts_folder, 'checkpoint.pth.tar')
+tts_config_file = os.path.join(embedded_tts_folder, 'config.json')
 
-if os.path.isfile(config_file):
-    default_tts_config = config_file
-else:
-    default_tts_config = None
+embedded_wavernn_folder = os.path.join(embedded_models_folder, 'wavernn')
+wavernn_checkpoint_file = os.path.join(embedded_wavernn_folder, 'checkpoint.pth.tar')
+wavernn_config_file = os.path.join(embedded_wavernn_folder, 'config.json')
+
+embedded_pwgan_folder = os.path.join(embedded_models_folder, 'pwgan')
+pwgan_checkpoint_file = os.path.join(embedded_pwgan_folder, 'checkpoint.pkl')
+pwgan_config_file = os.path.join(embedded_pwgan_folder, 'config.yml')
 
 args = create_argparser().parse_args()
 
-# If these were not specified in the CLI args, use default values
-if not args.tts_checkpoint:
-    args.tts_checkpoint = default_tts_checkpoint
-if not args.tts_config:
-    args.tts_config = default_tts_config
+# If these were not specified in the CLI args, use default values with embedded model files
+if not args.tts_checkpoint and os.path.isfile(tts_checkpoint_file):
+    args.tts_checkpoint = tts_checkpoint_file
+if not args.tts_config and os.path.isfile(tts_config_file):
+    args.tts_config = tts_config_file
+if not args.wavernn_file and os.path.isfile(wavernn_checkpoint_file):
+    args.wavernn_file = wavernn_checkpoint_file
+if not args.wavernn_config and os.path.isfile(wavernn_config_file):
+    args.wavernn_config = wavernn_config_file
+if not args.pwgan_file and os.path.isfile(pwgan_checkpoint_file):
+    args.pwgan_file = pwgan_checkpoint_file
+if not args.pwgan_config and os.path.isfile(pwgan_config_file):
+    args.pwgan_config = pwgan_config_file
 
 synthesizer = Synthesizer(args)
 

server/synthesizer.py

@@ -121,8 +121,9 @@ class Synthesizer(object):
         wav = np.array(wav)
         self.ap.save_wav(wav, path)
 
-    def split_into_sentences(self, text):
-        text = " " + text + "  "
+    @staticmethod
+    def split_into_sentences(text):
+        text = " " + text + "  <stop>"
         text = text.replace("\n", " ")
         text = re.sub(prefixes, "\\1<prd>", text)
         text = re.sub(websites, "<prd>\\1", text)
@@ -149,15 +150,13 @@ class Synthesizer(object):
         text = text.replace("<prd>", ".")
         sentences = text.split("<stop>")
         sentences = sentences[:-1]
-        sentences = [s.strip() for s in sentences]
+        sentences = list(filter(None, [s.strip() for s in sentences])) # remove empty sentences
         return sentences
 
     def tts(self, text):
         wavs = []
         sens = self.split_into_sentences(text)
         print(sens)
-        if not sens:
-            sens = [text+'.']
         for sen in sens:
             # preprocess the given text
             inputs = text_to_seqvec(sen, self.tts_config, self.use_cuda)
@@ -168,9 +167,16 @@ class Synthesizer(object):
             postnet_output, decoder_output, _ = parse_outputs(
                 postnet_output, decoder_output, alignments)
 
+            if self.pwgan:
+                vocoder_input = torch.FloatTensor(postnet_output.T).unsqueeze(0)
+                if self.use_cuda:
+                    vocoder_input.cuda()
+                wav = self.pwgan.inference(vocoder_input, hop_size=self.ap.hop_length)
             if self.wavernn:
-                postnet_output = postnet_output[0].data.cpu().numpy()
-                wav = self.wavernn.generate(torch.FloatTensor(postnet_output.T).unsqueeze(0).cuda(), batched=self.config.is_wavernn_batched, target=11000, overlap=550)
+                vocoder_input = torch.FloatTensor(postnet_output.T).unsqueeze(0)
+                if self.use_cuda:
+                    vocoder_input.cuda()
+                wav = self.wavernn.generate(vocoder_input, batched=self.config.is_wavernn_batched, target=11000, overlap=550)
             else:
                 wav = inv_spectrogram(postnet_output, self.ap, self.tts_config)
             # trim silence

setup.py

@@ -61,10 +61,11 @@ package_data = ['server/templates/*']
 if 'bdist_wheel' in unknown_args and args.checkpoint and args.model_config:
     print('Embedding model in wheel file...')
     model_dir = os.path.join('server', 'model')
-    os.makedirs(model_dir, exist_ok=True)
-    embedded_checkpoint_path = os.path.join(model_dir, 'checkpoint.pth.tar')
+    tts_dir = os.path.join(model_dir, 'tts')
+    os.makedirs(tts_dir, exist_ok=True)
+    embedded_checkpoint_path = os.path.join(tts_dir, 'checkpoint.pth.tar')
     shutil.copy(args.checkpoint, embedded_checkpoint_path)
-    embedded_config_path = os.path.join(model_dir, 'config.json')
+    embedded_config_path = os.path.join(tts_dir, 'config.json')
     shutil.copy(args.model_config, embedded_config_path)
     package_data.extend([embedded_checkpoint_path, embedded_config_path])
 

tests/test_server_package.sh

@@ -11,7 +11,7 @@ source /tmp/venv/bin/activate
 pip install --quiet --upgrade pip setuptools wheel
 
 rm -f dist/*.whl
-python setup.py bdist_wheel --checkpoint tests/outputs/checkpoint_10.pth.tar --model_config tests/outputs/dummy_model_config.json
+python setup.py --quiet bdist_wheel --checkpoint tests/outputs/checkpoint_10.pth.tar --model_config tests/outputs/dummy_model_config.json
 pip install --quiet dist/TTS*.whl
 
 python -m TTS.server.server &