deepgeek/CosyVoice
2
0
Fork 0
mirror of https://github.com/FunAudioLLM/CosyVoice.git synced 2026-02-04 17:39:25 +08:00
Code Issues Packages Projects Releases Wiki Activity

update flow cache

Browse Source
This commit is contained in:
lyuxiang.lx
2024-10-16 15:24:47 +08:00
parent ace734def8
commit a4db3db8ed
3 changed files with 26 additions and 31 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
cosyvoice/cli/model.py
View File

@@ -52,8 +52,8 @@ class CosyVoiceModel:
# dict used to store session related variable
self.tts_speech_token_dict = {}
self.llm_end_dict = {}
self.flow_cache_dict = {}
self.mel_overlap_dict = {}
self.flow_cache_dict = {}
self.hift_cache_dict = {}
def load(self, llm_model, flow_model, hift_model):
@@ -102,18 +102,17 @@ class CosyVoiceModel:
def token2wav(self, token, prompt_token, prompt_feat, embedding, uuid, finalize=False, speed=1.0):
tts_mel, flow_cache = self.flow.inference(token=token.to(self.device),
token_len=torch.tensor([token.shape[1]], dtype=torch.int32).to(self.device),
prompt_token=prompt_token.to(self.device),
prompt_token_len=torch.tensor([prompt_token.shape[1]], dtype=torch.int32).to(self.device),
prompt_feat=prompt_feat.to(self.device),
prompt_feat_len=torch.tensor([prompt_feat.shape[1]], dtype=torch.int32).to(self.device),
embedding=embedding.to(self.device),
required_cache_size=self.mel_overlap_len,
flow_cache=self.flow_cache_dict[uuid])
token_len=torch.tensor([token.shape[1]], dtype=torch.int32).to(self.device),
prompt_token=prompt_token.to(self.device),
prompt_token_len=torch.tensor([prompt_token.shape[1]], dtype=torch.int32).to(self.device),
prompt_feat=prompt_feat.to(self.device),
prompt_feat_len=torch.tensor([prompt_feat.shape[1]], dtype=torch.int32).to(self.device),
embedding=embedding.to(self.device),
flow_cache=self.flow_cache_dict[uuid])
self.flow_cache_dict[uuid] = flow_cache
# mel overlap fade in out
if self.mel_overlap_dict[uuid] is not None:
if self.mel_overlap_dict[uuid].shape[2] != 0:
tts_mel = fade_in_out(tts_mel, self.mel_overlap_dict[uuid], self.mel_window)
# append hift cache
if self.hift_cache_dict[uuid] is not None:
@@ -150,8 +149,9 @@ class CosyVoiceModel:
this_uuid = str(uuid.uuid1())
with self.lock:
self.tts_speech_token_dict[this_uuid], self.llm_end_dict[this_uuid] = [], False
self.flow_cache_dict[this_uuid] = None
self.mel_overlap_dict[this_uuid], self.hift_cache_dict[this_uuid] = None, None
self.hift_cache_dict[this_uuid] = None
self.mel_overlap_dict[this_uuid] = torch.zeros(1, 80, 0)
self.flow_cache_dict[this_uuid] = torch.zeros(1, 80, 0, 2)
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:
@@ -207,7 +207,9 @@ class CosyVoiceModel:
this_uuid = str(uuid.uuid1())
with self.lock:
self.tts_speech_token_dict[this_uuid], self.llm_end_dict[this_uuid] = source_speech_token.flatten().tolist(), True
self.mel_overlap_dict[this_uuid], self.hift_cache_dict[this_uuid] = None, None
self.hift_cache_dict[this_uuid] = None
self.mel_overlap_dict[this_uuid] = torch.zeros(1, 80, 0)
self.flow_cache_dict[this_uuid] = torch.zeros(1, 80, 0, 2)
if stream is True:
token_hop_len = self.token_min_hop_len
while True: