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force set use_flow_cache

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lyuxiang.lx
2025-04-08 12:23:26 +08:00
parent b56dfa223d
commit 9dc559fc2a
1 changed files with 5 additions and 4 deletions
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9
cosyvoice/cli/model.py
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@@ -401,10 +401,6 @@ class CosyVoice2Model(CosyVoiceModel):
prompt_speech_feat=torch.zeros(1, 0, 80), stream=False, speed=1.0, **kwargs):
# this_uuid is used to track variables related to this inference thread
this_uuid = str(uuid.uuid1())
# NOTE in cache mode, trim flow_prompt to same size as flow_decoder_required_cache_size
if self.use_flow_cache is True:
flow_prompt_speech_token = flow_prompt_speech_token[:, -self.flow_decoder_required_cache_size:]
prompt_speech_feat = prompt_speech_feat[:, -self.flow_decoder_required_cache_size * 2:]
with self.lock:
self.tts_speech_token_dict[this_uuid], self.llm_end_dict[this_uuid] = [], False
self.hift_cache_dict[this_uuid] = None
@@ -412,6 +408,10 @@ class CosyVoice2Model(CosyVoiceModel):
p = threading.Thread(target=self.llm_job, args=(text, prompt_text, llm_prompt_speech_token, llm_embedding, this_uuid))
p.start()
if stream is True:
assert self.use_flow_cache is True, "set use_flow_cache=True if you want to use stream inference to avoid OOM"
# NOTE in cache mode, trim flow_prompt to same size as flow_decoder_required_cache_size
flow_prompt_speech_token = flow_prompt_speech_token[:, -self.flow_decoder_required_cache_size:]
prompt_speech_feat = prompt_speech_feat[:, -self.flow_decoder_required_cache_size * 2:]
while True:
time.sleep(0.1)
if len(self.tts_speech_token_dict[this_uuid]) >= self.token_hop_len + self.flow.pre_lookahead_len:
@@ -442,6 +442,7 @@ class CosyVoice2Model(CosyVoiceModel):
yield {'tts_speech': this_tts_speech.cpu()}
else:
# deal with all tokens
assert self.use_flow_cache is False, "set use_flow_cache=False for nonstream inference"
p.join()
this_tts_speech_token = torch.tensor(self.tts_speech_token_dict[this_uuid]).unsqueeze(dim=0)
this_tts_speech = self.token2wav(token=this_tts_speech_token,