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86 lines
2.8 KiB
86 lines
2.8 KiB
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import os
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from pathlib import Path
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import numpy as np
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import paddle
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import soundfile as sf
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from paddlespeech.t2s.exps.waveflow.config import get_cfg_defaults
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from paddlespeech.t2s.models.waveflow import ConditionalWaveFlow
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from paddlespeech.t2s.utils import layer_tools
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def main(config, args):
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if args.ngpu == 0:
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paddle.set_device("cpu")
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elif args.ngpu > 0:
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paddle.set_device("gpu")
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else:
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print("ngpu should >= 0 !")
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model = ConditionalWaveFlow.from_pretrained(config, args.checkpoint_path)
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layer_tools.recursively_remove_weight_norm(model)
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model.eval()
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mel_dir = Path(args.input).expanduser()
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output_dir = Path(args.output).expanduser()
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output_dir.mkdir(parents=True, exist_ok=True)
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for file_path in mel_dir.glob("*.npy"):
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mel = np.load(str(file_path))
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with paddle.amp.auto_cast():
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audio = model.predict(mel)
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audio_path = output_dir / (os.path.splitext(file_path.name)[0] + ".wav")
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sf.write(audio_path, audio, config.data.sample_rate)
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print("[synthesize] {} -> {}".format(file_path, audio_path))
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if __name__ == "__main__":
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config = get_cfg_defaults()
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parser = argparse.ArgumentParser(
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description="generate mel spectrogram with TransformerTTS.")
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parser.add_argument(
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"--config",
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type=str,
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metavar="FILE",
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help="extra config to overwrite the default config")
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parser.add_argument(
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"--checkpoint_path", type=str, help="path of the checkpoint to load.")
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parser.add_argument(
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"--input",
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type=str,
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help="path of directory containing mel spectrogram (in .npy format)")
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parser.add_argument("--output", type=str, help="path to save outputs")
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parser.add_argument(
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"--ngpu", type=int, default=1, help="if ngpu=0, use cpu.")
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parser.add_argument(
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"--opts",
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nargs=argparse.REMAINDER,
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help="options to overwrite --config file and the default config, passing in KEY VALUE pairs"
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)
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args = parser.parse_args()
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if args.config:
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config.merge_from_file(args.config)
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if args.opts:
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config.merge_from_list(args.opts)
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config.freeze()
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print(config)
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print(args)
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main(config, args)
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