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Update infer.py (#196)

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This commit is contained in:
OedoSoldier
2023-11-27 13:08:43 +08:00
committed by GitHub
parent 5ec036af22
commit 122afe0251
1 changed files with 16 additions and 15 deletions
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31
infer.py
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@@ -82,7 +82,7 @@ def get_net_g(model_path: str, version: str, device: str, hps):
return net_g return net_g
def get_text(text, reference_audio, emotion, language_str, hps, device): def get_text(text, language_str, hps, device):
# 在此处实现当前版本的get_text # 在此处实现当前版本的get_text
norm_text, phone, tone, word2ph = clean_text(text, language_str) norm_text, phone, tone, word2ph = clean_text(text, language_str)
phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str) phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
@@ -113,12 +113,6 @@ def get_text(text, reference_audio, emotion, language_str, hps, device):
else: else:
raise ValueError("language_str should be ZH, JP or EN") raise ValueError("language_str should be ZH, JP or EN")
emo = (
torch.from_numpy(get_emo(reference_audio))
if reference_audio
else torch.Tensor([emotion])
)
assert bert.shape[-1] == len( assert bert.shape[-1] == len(
phone phone
), f"Bert seq len {bert.shape[-1]} != {len(phone)}" ), f"Bert seq len {bert.shape[-1]} != {len(phone)}"
@@ -126,7 +120,16 @@ def get_text(text, reference_audio, emotion, language_str, hps, device):
phone = torch.LongTensor(phone) phone = torch.LongTensor(phone)
tone = torch.LongTensor(tone) tone = torch.LongTensor(tone)
language = torch.LongTensor(language) language = torch.LongTensor(language)
return bert, ja_bert, en_bert, emo, phone, tone, language return bert, ja_bert, en_bert, phone, tone, language
def get_emo(reference_audio, emotion):
emo = (
torch.from_numpy(get_emo(reference_audio))
if reference_audio
else torch.Tensor([emotion])
)
return emo
def infer( def infer(
@@ -191,9 +194,10 @@ def infer(
device, device,
) )
# 在此处实现当前版本的推理 # 在此处实现当前版本的推理
bert, ja_bert, en_bert, emo, phones, tones, lang_ids = get_text( bert, ja_bert, en_bert, phones, tones, lang_ids = get_text(
text, reference_audio, emotion, language, hps, device text, language, hps, device
) )
emo = get_emo(reference_audio, emotion)
if skip_start: if skip_start:
phones = phones[1:] phones = phones[1:]
tones = tones[1:] tones = tones[1:]
@@ -261,10 +265,8 @@ def infer_multilang(
skip_start=False, skip_start=False,
skip_end=False, skip_end=False,
): ):
bert, ja_bert, en_bert, emo, phones, tones, lang_ids = [], [], [], [], [], [], [] bert, ja_bert, en_bert, phones, tones, lang_ids = [], [], [], [], [], []
# bert, ja_bert, en_bert, phones, tones, lang_ids = get_text( emo = get_emo(reference_audio, emotion)
# text, language, hps, device
# )
for idx, (txt, lang) in enumerate(zip(text, language)): for idx, (txt, lang) in enumerate(zip(text, language)):
skip_start = (idx != 0) or (skip_start and idx == 0) skip_start = (idx != 0) or (skip_start and idx == 0)
skip_end = (idx != len(text) - 1) or (skip_end and idx == len(text) - 1) skip_end = (idx != len(text) - 1) or (skip_end and idx == len(text) - 1)
@@ -300,7 +302,6 @@ def infer_multilang(
bert = torch.concatenate(bert, dim=1) bert = torch.concatenate(bert, dim=1)
ja_bert = torch.concatenate(ja_bert, dim=1) ja_bert = torch.concatenate(ja_bert, dim=1)
en_bert = torch.concatenate(en_bert, dim=1) en_bert = torch.concatenate(en_bert, dim=1)
emo = torch.concatenate(emo, dim=1)
phones = torch.concatenate(phones, dim=0) phones = torch.concatenate(phones, dim=0)
tones = torch.concatenate(tones, dim=0) tones = torch.concatenate(tones, dim=0)
lang_ids = torch.concatenate(lang_ids, dim=0) lang_ids = torch.concatenate(lang_ids, dim=0)