# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
from pathlib import Path
import paddle
import soundfile as sf
import yaml
from timer import timer
from yacs.config import CfgNode
from paddlespeech.t2s.exps.syn_utils import am_to_static
from paddlespeech.t2s.exps.syn_utils import get_frontend
from paddlespeech.t2s.exps.syn_utils import get_sentences
from paddlespeech.t2s.models.vits import VITS
from paddlespeech.t2s.models.vits import VITSInference
from paddlespeech.t2s.utils import str2bool
[docs]def evaluate(args):
# Init body.
with open(args.config) as f:
config = CfgNode(yaml.safe_load(f))
print("========Args========")
print(yaml.safe_dump(vars(args)))
print("========Config========")
print(config)
sentences = get_sentences(text_file=args.text, lang=args.lang)
# frontend
frontend = get_frontend(lang=args.lang, phones_dict=args.phones_dict)
# acoustic model
am_name = args.am[:args.am.rindex('_')]
am_dataset = args.am[args.am.rindex('_') + 1:]
spk_num = None
if args.speaker_dict is not None:
print("multiple speaker vits!")
with open(args.speaker_dict, 'rt') as f:
spk_id = [line.strip().split() for line in f.readlines()]
spk_num = len(spk_id)
else:
print("single speaker vits!")
print("spk_num:", spk_num)
with open(args.phones_dict, "r") as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)
odim = config.n_fft // 2 + 1
config["model"]["generator_params"]["spks"] = spk_num
vits = VITS(idim=vocab_size, odim=odim, **config["model"])
vits.set_state_dict(paddle.load(args.ckpt)["main_params"])
vits.eval()
vits_inference = VITSInference(vits)
# whether dygraph to static
if args.inference_dir:
vits_inference = am_to_static(
am_inference=vits_inference,
am=args.am,
inference_dir=args.inference_dir,
speaker_dict=args.speaker_dict)
output_dir = Path(args.output_dir)
output_dir.mkdir(parents=True, exist_ok=True)
merge_sentences = False
add_blank = args.add_blank
N = 0
T = 0
for utt_id, sentence in sentences:
with timer() as t:
if args.lang == 'zh':
input_ids = frontend.get_input_ids(
sentence,
merge_sentences=merge_sentences,
add_blank=add_blank)
phone_ids = input_ids["phone_ids"]
elif args.lang == 'en':
input_ids = frontend.get_input_ids(
sentence, merge_sentences=merge_sentences)
phone_ids = input_ids["phone_ids"]
else:
print("lang should in {'zh', 'en'}!")
with paddle.no_grad():
flags = 0
for i in range(len(phone_ids)):
part_phone_ids = phone_ids[i]
spk_id = None
if am_dataset in {"aishell3",
"vctk"} and spk_num is not None:
spk_id = paddle.to_tensor(args.spk_id)
wav = vits_inference(part_phone_ids, spk_id)
else:
wav = vits_inference(part_phone_ids)
if flags == 0:
wav_all = wav
flags = 1
else:
wav_all = paddle.concat([wav_all, wav])
wav = wav_all.numpy()
N += wav.size
T += t.elapse
speed = wav.size / t.elapse
rtf = config.fs / speed
print(
f"{utt_id}, wave: {wav.shape}, time: {t.elapse}s, Hz: {speed}, RTF: {rtf}."
)
sf.write(str(output_dir / (utt_id + ".wav")), wav, samplerate=config.fs)
print(f"{utt_id} done!")
print(f"generation speed: {N / T}Hz, RTF: {config.fs / (N / T) }")
[docs]def parse_args():
# parse args and config
parser = argparse.ArgumentParser(description="Synthesize with VITS")
# model
parser.add_argument(
'--config', type=str, default=None, help='Config of VITS.')
parser.add_argument(
'--ckpt', type=str, default=None, help='Checkpoint file of VITS.')
parser.add_argument(
"--phones_dict", type=str, default=None, help="phone vocabulary file.")
parser.add_argument(
"--speaker_dict", type=str, default=None, help="speaker id map file.")
parser.add_argument(
'--spk_id',
type=int,
default=0,
help='spk id for multi speaker acoustic model')
# other
parser.add_argument(
'--lang',
type=str,
default='zh',
help='Choose model language. zh or en')
parser.add_argument(
"--inference_dir",
type=str,
default=None,
help="dir to save inference models")
parser.add_argument(
"--ngpu", type=int, default=1, help="if ngpu == 0, use cpu.")
parser.add_argument(
"--text",
type=str,
help="text to synthesize, a 'utt_id sentence' pair per line.")
parser.add_argument("--output_dir", type=str, help="output dir.")
parser.add_argument(
"--add-blank",
type=str2bool,
default=True,
help="whether to add blank between phones")
parser.add_argument(
'--am',
type=str,
default='vits_csmsc',
help='Choose acoustic model type of tts task.')
args = parser.parse_args()
return args
[docs]def main():
args = parse_args()
if args.ngpu == 0:
paddle.set_device("cpu")
elif args.ngpu > 0:
paddle.set_device("gpu")
else:
print("ngpu should >= 0 !")
evaluate(args)
if __name__ == "__main__":
main()