mrq/ai-voice-cloning
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Websocket server, override args parameters for model settings (squashed)

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favor existing arguments from parameters (kwargs) over global (args)

added parameter to specify the autoregressive_model (tho it still loads the default model first, and then loads the target model, which seems to be because TTS loading just loads whatever is set in the settings first)
removed load_tts() call, the cli tool now relys on generate() to load the tts system, which is less fail prone imho

Revert "added parameter to specify the autoregressive_model (tho it still loads the default model first, and then loads the target model, which seems to be because TTS loading just loads whatever is set in the settings first)"

This reverts commit d1dbe3e464.

Revert "added parameter to specify the autoregressive_model (tho it still loads the default model first, and then loads the target model, which seems to be because TTS loading just loads whatever is set in the settings first)"

This reverts commit d1dbe3e464.

Revert "favor existing arguments from parameters (kwargs) over global (args)"

This reverts commit 89102347a9.

args are now updated in the websocket server

remove unused import
This commit is contained in:
ben_mkiv 2023-08-22 23:09:42 +02:00
parent 5d73d9e71c
commit d16ba3a06d
1 changed files with 16 additions and 1 deletions
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17
src/api/websocket_server.py
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@ -4,7 +4,7 @@ from threading import Thread
from websockets.server import serve
from utils import generate, get_autoregressive_models, get_voice_list
from utils import generate, get_autoregressive_models, get_voice_list, args
# this is a not so nice workaround to set values to None if their string value is "None"
@ -19,6 +19,21 @@ def replaceNoneStringWithNone(message):
async def _handle_generate(websocket, message):
global args
# update args parameters which control the model settings
if message.get('autoregressive_model'):
args.autoregressive_model = message['autoregressive_model']
if message.get('diffusion_model'):
args.diffusion_model = message['diffusion_model']
if message.get('tokenizer_json'):
args.tokenizer_json = message['tokenizer_json']
if message.get('sample_batch_size'):
args.sample_batch_size = message['sample_batch_size']
message['result'] = generate(**message)
await websocket.send(json.dumps(replaceNoneStringWithNone(message)))