Applied extra settings to TTS generation
Pulled some extra settings from the models configuration file to help keep generated speech closer to the sample wav.
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erew123 authored and GitHub committed
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commit
ee3f5cb853
1 file changed
+54
-12
+54
-12
@@ -35,6 +35,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
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with open(this_dir / "languages.json", encoding="utf8") as f:
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languages = json.load(f)
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##############################################################
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#### LOAD PARAMS FROM CONFIG.JSON - REQUIRED FOR BRANDING ####
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##############################################################
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@@ -44,12 +45,13 @@ def load_config(file_path):
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configfile_data = json.load(configfile_path)
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return configfile_data
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# Define the path to the config.json file
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configfile_path = this_dir / "config.json"
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# Load config.json and assign it to a different variable (config_data)
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params = load_config(configfile_path)
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# check someone hasnt enabled lowvram on a system thats not cuda enabled
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# check someone hasnt enabled lowvram on a system thats not cuda enabled
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params["low_vram"] = "false" if not torch.cuda.is_available() else params["low_vram"]
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# Define the path to the JSON file
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@@ -98,10 +100,14 @@ try:
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deepspeed_installed = True
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print(f"[{params['branding']}Startup] DeepSpeed \033[93mDetected\033[0m")
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print(f"[{params['branding']}Startup] Activate DeepSpeed in {params['branding']} settings")
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print(
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f"[{params['branding']}Startup] Activate DeepSpeed in {params['branding']} settings"
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)
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except ImportError:
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deepspeed_installed = False
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print(f"[{params['branding']}Startup] DeepSpeed \033[93mNot Detected\033[0m. See https://github.com/microsoft/DeepSpeed")
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print(
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f"[{params['branding']}Startup] DeepSpeed \033[93mNot Detected\033[0m. See https://github.com/microsoft/DeepSpeed"
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)
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@asynccontextmanager
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@@ -159,7 +165,6 @@ async def setup():
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Path(f'{params["output_folder_wav"]}').mkdir(parents=True, exist_ok=True)
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# MODEL LOADER For "API TTS"
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async def api_load_model():
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global model
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@@ -255,6 +260,7 @@ async def handle_tts_method_change(tts_method):
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# Load the correct model based on the updated params
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await setup()
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# MODEL WEBSERVER- API Swap Between Models
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@app.route("/api/reload", methods=["POST"])
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async def reload(request: Request):
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@@ -266,6 +272,7 @@ async def reload(request: Request):
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content=json.dumps({"status": "model-success"}), media_type="application/json"
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)
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##################
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#### LOW VRAM ####
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##################
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@@ -283,6 +290,7 @@ async def switch_device():
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device = "cuda"
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model.to(device)
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@app.post("/api/lowvramsetting")
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async def set_low_vram(request: Request, new_low_vram_value: bool):
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global device
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@@ -313,7 +321,9 @@ async def set_low_vram(request: Request, new_low_vram_value: bool):
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await setup()
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else:
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# Handle the case where CUDA is not available
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print(f"[{params['branding']}Model] \033[91mError:\033[0m Nvidia CUDA is not available on this system. Unable to use LowVRAM mode.")
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print(
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f"[{params['branding']}Model] \033[91mError:\033[0m Nvidia CUDA is not available on this system. Unable to use LowVRAM mode."
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)
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params["low_vram"] = False
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else:
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await unload_model(model)
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@@ -328,12 +338,15 @@ async def set_low_vram(request: Request, new_low_vram_value: bool):
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await setup()
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else:
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# Handle the case where CUDA is not available
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print(f"[{params['branding']}Model] \033[91mError:\033[0m Nvidia CUDA is not available on this system. Unable to use LowVRAM mode.")
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print(
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f"[{params['branding']}Model] \033[91mError:\033[0m Nvidia CUDA is not available on this system. Unable to use LowVRAM mode."
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)
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params["low_vram"] = False
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return Response(content=json.dumps({"status": "lowvram-success"}))
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except Exception as e:
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return Response(content=json.dumps({"status": "error", "message": str(e)}))
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###################
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#### DeepSpeed ####
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###################
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@@ -399,6 +412,7 @@ async def deepspeed(request: Request, new_deepspeed_value: bool):
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except Exception as e:
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return Response(content=json.dumps({"status": "error", "message": str(e)}))
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########################
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#### TTS GENERATION ####
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########################
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@@ -412,21 +426,42 @@ async def generate_audio(text, voice, language, output_file):
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if params["tts_method_xtts_local"]:
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print(f"[{params['branding']}TTSGen] {text}")
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gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(
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audio_path=[f"{this_dir}/voices/{voice}"]
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audio_path=[f"{this_dir}/voices/{voice}"],
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gpt_cond_len=model.config.gpt_cond_len,
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max_ref_length=model.config.max_ref_len,
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sound_norm_refs=model.config.sound_norm_refs,
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)
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out = model.inference(
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text,
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language,
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gpt_cond_latent=gpt_cond_latent,
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speaker_embedding=speaker_embedding,
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temperature=0.7,
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temperature=model.config.temperature,
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length_penalty=model.config.length_penalty,
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repetition_penalty=model.config.repetition_penalty,
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top_k=model.config.top_k,
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top_p=model.config.top_p,
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enable_text_splitting=True,
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)
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torchaudio.save(output_file, torch.tensor(out["wav"]).unsqueeze(0), 24000)
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# API TTS and API LOCAL Methods
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elif params["tts_method_api_tts"] or params["tts_method_api_local"]:
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# API LOCAL Methods
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elif params["tts_method_api_local"]:
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# Set the correct output path (different from the if statement)
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print(f"[{params['branding']}TTSGen] Using API TTS/Local Method")
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print(f"[{params['branding']}TTSGen] Using API Local")
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model.tts_to_file(
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text=text,
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file_path=output_file,
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speaker_wav=[f"{this_dir}/voices/{voice}"],
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language=language,
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temperature=model.config.temperature,
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length_penalty=model.config.length_penalty,
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repetition_penalty=model.config.repetition_penalty,
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top_k=model.config.top_k,
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top_p=model.config.top_p,
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)
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# API TTS
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elif params["tts_method_api_tts"]:
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print(f"[{params['branding']}TTSGen] Using API TTS")
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model.tts_to_file(
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text=text,
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file_path=output_file,
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@@ -469,9 +504,14 @@ async def generate(request: Request):
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###################################################
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# List files in the "voices" directory
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def list_files(directory):
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files = [f for f in os.listdir(directory) if os.path.isfile(os.path.join(directory, f)) and f.endswith('.wav')]
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files = [
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f
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for f in os.listdir(directory)
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if os.path.isfile(os.path.join(directory, f)) and f.endswith(".wav")
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]
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return files
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#############################
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#### JSON CONFIG UPDATER ####
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#############################
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@@ -479,6 +519,7 @@ def list_files(directory):
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# Create an instance of Jinja2Templates for rendering HTML templates
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templates = Jinja2Templates(directory=this_dir / "templates")
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# Create a dependency to get the current JSON data
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def get_json_data():
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with open(this_dir / "config.json", "r") as json_file:
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@@ -501,6 +542,7 @@ async def get_settings(request: Request):
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},
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)
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@app.post("/update-settings")
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async def update_settings(
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request: Request,
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