fix(tools): log formatting (#401)

- introduce numba
- move audio normalization functions to tools/audio
- remove IPython from tools/cmd

examples/cmd/run.py

@@ -11,27 +11,25 @@ load_dotenv("sha256.env")
 
 import wave
 import ChatTTS
-from IPython.display import Audio
 
+from tools.audio import unsafe_float_to_int16
 from tools.logger import get_logger
 
 logger = get_logger("Command")
 
 def save_wav_file(wav, index):
     wav_filename = f"output_audio_{index}.wav"
-    # Convert numpy array to bytes and write to WAV file
-    wav_bytes = (wav * 32768).astype('int16').tobytes()
     with wave.open(wav_filename, "wb") as wf:
         wf.setnchannels(1)  # Mono channel
         wf.setsampwidth(2)  # Sample width in bytes
         wf.setframerate(24000)  # Sample rate in Hz
-        wf.writeframes(wav_bytes)
+        wf.writeframes(unsafe_float_to_int16(wav))
     logger.info(f"Audio saved to {wav_filename}")
 
 def main():
     # Retrieve text from command line argument
     text_input = sys.argv[1] if len(sys.argv) > 1 else "<YOUR TEXT HERE>"
-    logger.info("Received text input: %s", text_input)
+    logger.info("Text input: %s", text_input)
 
     chat = ChatTTS.Chat(get_logger("ChatTTS"))
     logger.info("Initializing ChatTTS...")
@@ -41,17 +39,12 @@ def main():
         logger.error("Models load failed.")
         sys.exit(1)
 
-    texts = [text_input]
-    logger.info("Text prepared for inference: %s", texts)
-
-    wavs = chat.infer(texts, use_decoder=True)
+    wavs = chat.infer((text_input), use_decoder=True)
     logger.info("Inference completed. Audio generation successful.")
     # Save each generated wav file to a local file
     for index, wav in enumerate(wavs):
         save_wav_file(wav, index)
 
-    return Audio(wavs[0], rate=24_000, autoplay=True)
-
 if __name__ == "__main__":
     logger.info("Starting the TTS application...")
     main()

examples/web/funcs.py

@@ -4,6 +4,7 @@ import torch
 import gradio as gr
 import numpy as np
 
+from tools.audio import unsafe_float_to_int16
 from tools.logger import get_logger
 logger = get_logger(" WebUI ")
 
@@ -74,27 +75,7 @@ def generate_audio(text, temperature, top_P, top_K, audio_seed_input, text_seed_
 
     if stream:
         for gen in wav:
-            wavs = [np.array([[]])]
-            wavs[0] = np.hstack([wavs[0], np.array(gen[0])])
-            audio = wavs[0][0]
-            
-            # normalize
-            am = np.abs(audio).max() * 32768
-            if am > 32768:
-                am = 32768 * 32768 / am
-            np.multiply(audio, am, audio)
-            audio = audio.astype(np.int16)
-
-            yield 24000, audio
+            yield 24000, unsafe_float_to_int16(gen[0][0])
         return
 
-    audio_data = np.array(wav[0]).flatten()
-    # normalize
-    am = np.abs(audio_data).max() * 32768
-    if am > 32768:
-        am = 32768 * 32768 / am
-    np.multiply(audio_data, am, audio_data)
-    audio_data = audio_data.astype(np.int16)
-    sample_rate = 24000
-
-    yield sample_rate, audio_data
+    yield 24000, unsafe_float_to_int16(np.array(wav[0]).flatten())

requirements.txt

@@ -1,4 +1,5 @@
 numpy<2.0.0
+numba
 omegaconf>=2.3.0
 torch>=2.1.0
 tqdm

setup.py

@@ -4,6 +4,8 @@ setup(name='chattts',
       author='2noise',
       url='https://github.com/2noise/ChatTTS',
       install_requires=['omegaconf>=2.3.0',
+                        'numpy<2.0.0',
+                        'numba',
                 'torch>=2.1.0',
                 'tqdm',
                 'vector_quantize_pytorch',

tools/audio/__init__.py

@@ -0,0 +1 @@
+from .np import unsafe_float_to_int16

tools/audio/np.py

@@ -0,0 +1,14 @@
+import numpy as np
+from numba import jit
+
+@jit
+def unsafe_float_to_int16(audio: np.ndarray) -> np.ndarray:
+    """
+    This function will destroy audio, use only once.
+    """
+    am = np.abs(audio).max() * 32768
+    if am > 32768:
+        am = 32768 * 32768 / am
+    np.multiply(audio, am, audio)
+    audio16 = audio.astype(np.int16)
+    return audio16

tools/logger/log.py

@@ -2,6 +2,9 @@ import platform
 import logging
 from datetime import datetime, timezone
 
+logging.getLogger("numba").setLevel(logging.WARNING)
+logging.getLogger("httpx").setLevel(logging.WARNING)
+
 # from https://github.com/FloatTech/ZeroBot-Plugin/blob/c70766a989698452e60e5e48fb2f802a2444330d/console/console_windows.go#L89-L96
 colorCodePanic = "\x1b[1;31m"
 colorCodeFatal = "\x1b[1;31m"
@@ -41,7 +44,7 @@ class Formatter(logging.Formatter):
         logstr += log_level_msg_str.get(record.levelno, record.levelname)
         if self.color:
             logstr += colorReset
-        logstr += f"] {str(record.name)} | {str(record.msg)}"
+        logstr += f"] {str(record.name)} | {str(record.msg)%record.args}"
         return logstr
 
 def get_logger(name: str, lv = logging.INFO):