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feat: TTS on 2 GPUs (cuda:2,cuda:3) for faster inference

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hailin 2026-04-07 03:28:16 -07:00
parent b75e813c03
commit 17923f3bdc
2 changed files with 19 additions and 7 deletions
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2
config/.config.yaml
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@ -42,7 +42,7 @@ TTS:
type: qwen3_tts type: qwen3_tts
model_path: /home/ZeroStack/xiaozhi/Qwen3-TTS-12Hz-1.7B-CustomVoice model_path: /home/ZeroStack/xiaozhi/Qwen3-TTS-12Hz-1.7B-CustomVoice
tokenizer_path: /home/ZeroStack/xiaozhi/Qwen3-TTS-Tokenizer-12Hz tokenizer_path: /home/ZeroStack/xiaozhi/Qwen3-TTS-Tokenizer-12Hz
device: cuda:2 device: cuda:2,cuda:3
dtype: bfloat16 dtype: bfloat16
speaker: uncle_fu speaker: uncle_fu
language: Chinese language: Chinese

24
modules/tts/qwen3_tts.py
View File

@ -37,12 +37,24 @@ class TTSProvider(TTSProviderBase):
) )
t0 = time.time() t0 = time.time()
self.model = Qwen3TTSModel.from_pretrained( # Use multiple GPUs if specified (e.g. "cuda:2,cuda:3")
model_path, if "," in device:
device_map=device, gpu_ids = [d.strip().replace("cuda:", "") for d in device.split(",")]
dtype=dtype, max_memory = {int(g): "22GiB" for g in gpu_ids}
attn_implementation="flash_attention_2", self.model = Qwen3TTSModel.from_pretrained(
) model_path,
device_map="auto",
max_memory=max_memory,
dtype=dtype,
attn_implementation="flash_attention_2",
)
else:
self.model = Qwen3TTSModel.from_pretrained(
model_path,
device_map=device,
dtype=dtype,
attn_implementation="flash_attention_2",
)
self.tokenizer = Qwen3TTSTokenizer.from_pretrained(tokenizer_path) self.tokenizer = Qwen3TTSTokenizer.from_pretrained(tokenizer_path)
# Get supported speakers # Get supported speakers