Apply Code Formatter Change

This commit is contained in:
Stardust-minus
2023-09-06 13:42:05 +00:00
committed by github-actions[bot]
parent d82ba3457a
commit eef212fd00
26 changed files with 2938 additions and 1453 deletions

View File

@@ -13,7 +13,8 @@ from scipy.io import wavfile
# Flask Init
app = Flask(__name__)
app.config['JSON_AS_ASCII'] = False
app.config["JSON_AS_ASCII"] = False
def get_text(text, language_str, hps):
norm_text, phone, tone, word2ph = clean_text(text, language_str)
@@ -30,84 +31,121 @@ def get_text(text, language_str, hps):
del word2ph
assert bert.shape[-1] == len(phone), phone
if language_str=='ZH':
if language_str == "ZH":
bert = bert
ja_bert = torch.zeros(768, len(phone))
elif language_str=="JA":
elif language_str == "JA":
ja_bert = bert
bert = torch.zeros(1024, len(phone))
else:
bert = torch.zeros(1024, len(phone))
ja_bert = torch.zeros(768, len(phone))
assert bert.shape[-1] == len(phone), (
bert.shape, len(phone), sum(word2ph), p1, p2, t1, t2, pold, pold2, word2ph, text, w2pho)
bert.shape,
len(phone),
sum(word2ph),
p1,
p2,
t1,
t2,
pold,
pold2,
word2ph,
text,
w2pho,
)
phone = torch.LongTensor(phone)
tone = torch.LongTensor(tone)
language = torch.LongTensor(language)
return bert, ja_bert, phone, tone, language
def infer(text, sdp_ratio, noise_scale, noise_scale_w, length_scale, sid, language):
bert, ja_bert, phones, tones, lang_ids = get_text(text, language, hps)
with torch.no_grad():
x_tst=phones.to(dev).unsqueeze(0)
tones=tones.to(dev).unsqueeze(0)
lang_ids=lang_ids.to(dev).unsqueeze(0)
x_tst = phones.to(dev).unsqueeze(0)
tones = tones.to(dev).unsqueeze(0)
lang_ids = lang_ids.to(dev).unsqueeze(0)
bert = bert.to(dev).unsqueeze(0)
ja_bert = ja_bert.to(device).unsqueeze(0)
x_tst_lengths = torch.LongTensor([phones.size(0)]).to(dev)
speakers = torch.LongTensor([hps.data.spk2id[sid]]).to(dev)
audio = net_g.infer(x_tst, x_tst_lengths, speakers, tones, lang_ids, bert, ja_bert, sdp_ratio=sdp_ratio
, noise_scale=noise_scale, noise_scale_w=noise_scale_w, length_scale=length_scale)[0][0,0].data.cpu().float().numpy()
audio = (
net_g.infer(
x_tst,
x_tst_lengths,
speakers,
tones,
lang_ids,
bert,
ja_bert,
sdp_ratio=sdp_ratio,
noise_scale=noise_scale,
noise_scale_w=noise_scale_w,
length_scale=length_scale,
)[0][0, 0]
.data.cpu()
.float()
.numpy()
)
return audio
def replace_punctuation(text, i=2):
punctuation = ",。?!"
for char in punctuation:
text = text.replace(char, char * i)
return text
def wav2(i, o, format):
inp = avopen(i, 'rb')
out = avopen(o, 'wb', format=format)
if format == "ogg": format = "libvorbis"
inp = avopen(i, "rb")
out = avopen(o, "wb", format=format)
if format == "ogg":
format = "libvorbis"
ostream = out.add_stream(format)
for frame in inp.decode(audio=0):
for p in ostream.encode(frame): out.mux(p)
for p in ostream.encode(frame):
out.mux(p)
for p in ostream.encode(None): out.mux(p)
for p in ostream.encode(None):
out.mux(p)
out.close()
inp.close()
# Load Generator
hps = utils.get_hparams_from_file("./configs/config.json")
dev='cuda'
dev = "cuda"
net_g = SynthesizerTrn(
len(symbols),
hps.data.filter_length // 2 + 1,
hps.train.segment_size // hps.data.hop_length,
n_speakers=hps.data.n_speakers,
**hps.model).to(dev)
**hps.model
).to(dev)
_ = net_g.eval()
_ = utils.load_checkpoint("logs/G_649000.pth", net_g, None,skip_optimizer=True)
_ = utils.load_checkpoint("logs/G_649000.pth", net_g, None, skip_optimizer=True)
@app.route("/")
def main():
try:
speaker = request.args.get('speaker')
text = request.args.get('text').replace("/n","")
speaker = request.args.get("speaker")
text = request.args.get("text").replace("/n", "")
sdp_ratio = float(request.args.get("sdp_ratio", 0.2))
noise = float(request.args.get("noise", 0.5))
noisew = float(request.args.get("noisew", 0.6))
length = float(request.args.get("length", 1.2))
language = request.args.get('language')
language = request.args.get("language")
if length >= 2:
return "Too big length"
if len(text) >=250:
if len(text) >= 250:
return "Too long text"
fmt = request.args.get("format", "wav")
if None in (speaker, text):
@@ -120,7 +158,15 @@ def main():
return "Invalid Parameter"
with torch.no_grad():
audio = infer(text, sdp_ratio=sdp_ratio, noise_scale=noise, noise_scale_w=noisew, length_scale=length, sid=speaker,language = language)
audio = infer(
text,
sdp_ratio=sdp_ratio,
noise_scale=noise,
noise_scale_w=noisew,
length_scale=length,
sid=speaker,
language=language,
)
with BytesIO() as wav:
wavfile.write(wav, hps.data.sampling_rate, audio)
@@ -131,6 +177,5 @@ def main():
with BytesIO() as ofp:
wav2(wav, ofp, fmt)
return Response(
ofp.getvalue(),
mimetype="audio/mpeg" if fmt == "mp3" else "audio/ogg"
ofp.getvalue(), mimetype="audio/mpeg" if fmt == "mp3" else "audio/ogg"
)