65 lines
2.6 KiB
Python
65 lines
2.6 KiB
Python
# coding=utf-8
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# Copyright 2026 The Alibaba Qwen team.
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# SPDX-License-Identifier: Apache-2.0
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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 io
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import requests
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import soundfile as sf
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from qwen_tts import Qwen3TTSTokenizer
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audio_1 = "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/tokenizer_demo_1.wav"
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audio_2 = "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/tokenizer_demo_2.wav"
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# -------- Single input: wav path --------
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tokenizer_12hz = Qwen3TTSTokenizer.from_pretrained(
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"Qwen/Qwen3-TTS-Tokenizer-12Hz",
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device_map="cuda:0",
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)
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enc1 = tokenizer_12hz.encode(audio_1)
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wavs1, out_sr1 = tokenizer_12hz.decode(enc1)
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sf.write("decoded_single_12hz.wav", wavs1[0], out_sr1)
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# -------- Batch input: wav path list --------
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enc2 = tokenizer_12hz.encode([audio_1, audio_2])
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wavs2, out_sr2 = tokenizer_12hz.decode(enc2)
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for i, w in enumerate(wavs2):
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sf.write(f"decoded_batch_12hz_{i}.wav", w, out_sr2)
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# -------- Decode input as dict (12hz) --------
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# Take the first sample codes and pass as a dict.
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dict_input_12hz = {"audio_codes": enc2.audio_codes[0]} # torch.Tensor
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wavs_d1, out_sr_d1 = tokenizer_12hz.decode(dict_input_12hz)
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sf.write("decoded_dict_12hz.wav", wavs_d1[0], out_sr_d1)
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# -------- Decode input as list[dict] (12hz) --------
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list_dict_input_12hz = [{"audio_codes": c} for c in enc2.audio_codes] # list of torch.Tensor
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wavs_d2, out_sr_d2 = tokenizer_12hz.decode(list_dict_input_12hz)
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for i, w in enumerate(wavs_d2):
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sf.write(f"decoded_listdict_12hz_{i}.wav", w, out_sr_d2)
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# -------- Decode input as list[dict] with numpy (12hz) --------
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# Convert codes to numpy to simulate "serialized" payload.
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list_dict_numpy_12hz = [{"audio_codes": c.cpu().numpy()} for c in enc2.audio_codes]
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wavs_d3, out_sr_d3 = tokenizer_12hz.decode(list_dict_numpy_12hz)
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for i, w in enumerate(wavs_d3):
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sf.write(f"decoded_listdict_numpy_12hz_{i}.wav", w, out_sr_d3)
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# -------- Numpy input (must pass sr) --------
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data = requests.get(audio_2, timeout=30).content
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y, sr = sf.read(io.BytesIO(data))
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enc3 = tokenizer_12hz.encode(y, sr=sr)
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wavs3, out_sr3 = tokenizer_12hz.decode(enc3)
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sf.write("decoded_numpy_12hz.wav", wavs3[0], out_sr3) |