Add function docs and comments to demo_server.py and demo_client.py.

demo_client.py

@@ -11,6 +11,7 @@ enable_trigger_record = True
 
 
 def on_press(key):
+    """On-press keyboard callback function."""
     global is_recording, enable_trigger_record
     if key == keyboard.Key.space:
         if (not is_recording) and enable_trigger_record:
@@ -20,6 +21,7 @@ def on_press(key):
 
 
 def on_release(key):
+    """On-release keyboard callback function."""
     global is_recording, enable_trigger_record
     if key == keyboard.Key.esc:
         return False
@@ -32,6 +34,7 @@ data_list = []
 
 
 def callback(in_data, frame_count, time_info, status):
+    """Audio recorder's stream callback function."""
     global data_list, is_recording, enable_trigger_record
     if is_recording:
         data_list.append(in_data)
@@ -53,6 +56,7 @@ def callback(in_data, frame_count, time_info, status):
 
 
 def main():
+    # prepare audio recorder
     p = pyaudio.PyAudio()
     stream = p.open(
         format=pyaudio.paInt32,
@@ -62,10 +66,12 @@ def main():
         stream_callback=callback)
     stream.start_stream()
 
+    # prepare keyboard listener
     with keyboard.Listener(
             on_press=on_press, on_release=on_release) as listener:
         listener.join()
 
+    # close up
     stream.stop_stream()
     stream.close()
     p.terminate()

demo_server.py

@@ -112,6 +112,8 @@ args = parser.parse_args()
 
 
 class AsrTCPServer(SocketServer.TCPServer):
+    """The ASR TCP Server."""
+
     def __init__(self,
                  server_address,
                  RequestHandlerClass,
@@ -125,8 +127,7 @@ class AsrTCPServer(SocketServer.TCPServer):
 
 
 class AsrRequestHandler(SocketServer.BaseRequestHandler):
-    """The ASR request handler.
+    """The ASR request handler."""
-    """
 
     def handle(self):
         # receive data through TCP socket
@@ -170,6 +171,7 @@ def warm_up_test(audio_process_handler,
                  manifest_path,
                  num_test_cases,
                  random_seed=0):
+    """Warming-up test."""
     manifest = read_manifest(manifest_path)
     rng = random.Random(random_seed)
     samples = rng.sample(manifest, num_test_cases)
@@ -183,12 +185,15 @@ def warm_up_test(audio_process_handler,
 
 
 def start_server():
+    """Start the ASR server"""
+    # prepare data generator
     data_generator = DataGenerator(
         vocab_filepath=args.vocab_filepath,
         mean_std_filepath=args.mean_std_filepath,
         augmentation_config='{}',
         specgram_type=args.specgram_type,
         num_threads=1)
+    # prepare ASR model
     ds2_model = DeepSpeech2Model(
         vocab_size=data_generator.vocab_size,
         num_conv_layers=args.num_conv_layers,
@@ -196,6 +201,7 @@ def start_server():
         rnn_layer_size=args.rnn_layer_size,
         pretrained_model_path=args.model_filepath)
 
+    # prepare ASR inference handler
     def file_to_transcript(filename):
         feature = data_generator.process_utterance(filename, "")
         result_transcript = ds2_model.infer_batch(
@@ -210,6 +216,7 @@ def start_server():
             num_processes=1)
         return result_transcript[0]
 
+    # warming up with utterrances sampled from Librispeech
     print('-----------------------------------------------------------')
     print('Warming up ...')
     warm_up_test(
@@ -218,12 +225,12 @@ def start_server():
         num_test_cases=3)
     print('-----------------------------------------------------------')
 
+    # start the server
     server = AsrTCPServer(
         server_address=(args.host_ip, args.host_port),
         RequestHandlerClass=AsrRequestHandler,
         speech_save_dir=args.speech_save_dir,
         audio_process_handler=file_to_transcript)
-
     print("ASR Server Started.")
     server.serve_forever()