# 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 get_frontend from paddlespeech.t2s.exps.syn_utils import get_sentences from paddlespeech.t2s.models.vits import VITS from paddlespeech.t2s.utils import str2bool 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) 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 vits = VITS(idim=vocab_size, odim=odim, **config["model"]) vits.set_state_dict(paddle.load(args.ckpt)["main_params"]) vits.eval() 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] out = vits.inference(text=part_phone_ids) wav = out["wav"] 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) }") 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.") # 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") 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()