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on
CPU Upgrade
Running
on
CPU Upgrade
import os | |
import requests | |
from subprocess import Popen, PIPE | |
import time | |
import threading | |
import gradio as gr | |
def run_xvaserver(): | |
try: | |
import logging | |
# start the process without waiting for a response | |
logging.info('loginfo: Running xVAServer subprocess...') | |
print('Running xVAServer subprocess...') | |
xvaserver = Popen(['python', 'server.py'], stdout=PIPE, stderr=PIPE, universal_newlines=True) | |
except: | |
import logging | |
logging.error(f'Could not run xVASynth.') | |
sys.exit(0) | |
# Read and print stdout and stderr of the subprocess | |
while True: | |
output = xvaserver.stdout.readline() | |
if output == '' and xvaserver.poll() is not None: | |
break | |
if output: | |
print(output.strip()) | |
error = xvaserver.stderr.readline() | |
if error == '' and xvaserver.poll() is not None: | |
break | |
if error: | |
print(error.strip(), file=sys.stderr) | |
# Wait for the process to exit | |
xvaserver.wait() | |
def load_model(): | |
model_type = 'xVAPitch' | |
language = 'en' | |
data = { | |
'outputs': None, | |
'version': '3.0', | |
'model': 'ccby/ccby_nvidia_hifi_6670_M', | |
'modelType': model_type, | |
'base_lang': language, | |
'pluginsContext': '{}', | |
} | |
requests.post('http://0.0.0.0:8008/loadModel', json=data) | |
return | |
def predict(input, pacing): | |
model_type = 'xVAPitch' | |
line = 'Test' | |
pace = pacing if pacing else 1.0 | |
save_path = 'test.wav' | |
language = 'en' | |
base_speaker_emb = [] | |
use_sr = 0 | |
use_cleanup = 0 | |
data = { | |
'modelType': model_type, | |
'sequence': line, | |
'pace': pace, | |
'outfile': save_path, | |
'vocoder': 'n/a', | |
'base_lang': language, | |
'base_emb': base_speaker_emb, | |
'useSR': use_sr, | |
'useCleanup': use_cleanup, | |
} | |
requests.post('http://0.0.0.0:8008/synthesize', json=data) | |
return 22100, os.open(save_path, "rb") | |
input_textbox = gr.Textbox( | |
label="Input Text", | |
lines=1, | |
autofocus=True | |
) | |
slider = gr.Slider(0.0, 2.0, value=1.0, step=0.1, label="Pacing") | |
gradio_app = gr.Interface( | |
predict, | |
[ | |
input_textbox, | |
slider | |
], | |
outputs= "audio", | |
title="xVASynth", | |
) | |
if __name__ == "__main__": | |
# Run the web server in a separate thread | |
web_server_thread = threading.Thread(target=run_xvaserver) | |
web_server_thread.start() | |
gradio_app.launch() | |
# Wait for the web server thread to finish (shouldn't be reached in normal execution) | |
web_server_thread.join() | |