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examples/test_tokenizer_12hz.py

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