You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
154 lines
4.7 KiB
154 lines
4.7 KiB
# 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 jsonlines
|
|
import numpy as np
|
|
import paddle
|
|
import soundfile as sf
|
|
import yaml
|
|
from timer import timer
|
|
from yacs.config import CfgNode
|
|
|
|
from paddlespeech.t2s.datasets.data_table import DataTable
|
|
from paddlespeech.t2s.models.jets import JETS
|
|
from paddlespeech.t2s.utils import str2bool
|
|
|
|
|
|
def evaluate(args):
|
|
|
|
# construct dataset for evaluation
|
|
with jsonlines.open(args.test_metadata, 'r') as reader:
|
|
test_metadata = list(reader)
|
|
# 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)
|
|
|
|
fields = ["utt_id", "text"]
|
|
converters = {}
|
|
|
|
spk_num = None
|
|
if args.speaker_dict is not None:
|
|
print("multiple speaker jets!")
|
|
with open(args.speaker_dict, 'rt') as f:
|
|
spk_id = [line.strip().split() for line in f.readlines()]
|
|
spk_num = len(spk_id)
|
|
fields += ["spk_id"]
|
|
elif args.voice_cloning:
|
|
print("Evaluating voice cloning!")
|
|
fields += ["spk_emb"]
|
|
else:
|
|
print("single speaker jets!")
|
|
print("spk_num:", spk_num)
|
|
|
|
test_dataset = DataTable(
|
|
data=test_metadata,
|
|
fields=fields,
|
|
converters=converters, )
|
|
|
|
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
|
|
|
|
jets = JETS(idim=vocab_size, odim=odim, **config["model"])
|
|
jets.set_state_dict(paddle.load(args.ckpt)["main_params"])
|
|
jets.eval()
|
|
|
|
output_dir = Path(args.output_dir)
|
|
output_dir.mkdir(parents=True, exist_ok=True)
|
|
|
|
N = 0
|
|
T = 0
|
|
|
|
for datum in test_dataset:
|
|
utt_id = datum["utt_id"]
|
|
phone_ids = paddle.to_tensor(datum["text"])
|
|
with timer() as t:
|
|
with paddle.no_grad():
|
|
spk_emb = None
|
|
spk_id = None
|
|
# multi speaker
|
|
if args.voice_cloning and "spk_emb" in datum:
|
|
spk_emb = paddle.to_tensor(np.load(datum["spk_emb"]))
|
|
elif "spk_id" in datum:
|
|
spk_id = paddle.to_tensor(datum["spk_id"])
|
|
out = jets.inference(
|
|
text=phone_ids, sids=spk_id, spembs=spk_emb)
|
|
wav = out["wav"]
|
|
wav = wav.numpy()
|
|
N += wav.size
|
|
T += t.elapse
|
|
speed = wav.size / t.elapse
|
|
rtf = config.fs / speed
|
|
print(
|
|
f"{utt_id}, wave: {wav.size}, 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) }")
|
|
|
|
|
|
def parse_args():
|
|
# parse args and config
|
|
parser = argparse.ArgumentParser(description="Synthesize with JETS")
|
|
# model
|
|
parser.add_argument(
|
|
'--config', type=str, default=None, help='Config of JETS.')
|
|
parser.add_argument(
|
|
'--ckpt', type=str, default=None, help='Checkpoint file of JETS.')
|
|
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(
|
|
"--voice-cloning",
|
|
type=str2bool,
|
|
default=False,
|
|
help="whether training voice cloning model.")
|
|
# other
|
|
parser.add_argument(
|
|
"--ngpu", type=int, default=1, help="if ngpu == 0, use cpu.")
|
|
parser.add_argument("--test_metadata", type=str, help="test metadata.")
|
|
parser.add_argument("--output_dir", type=str, help="output dir.")
|
|
|
|
args = parser.parse_args()
|
|
return args
|
|
|
|
|
|
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()
|