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Merge pull request #205 from LeiHao0/main

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Resolved the issue of duplicate inference in the Bert1 model
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RVC-Boss 2024-01-26 11:11:49 +08:00 committed by GitHub
commit 43d69fdaca
1 changed files with 10 additions and 7 deletions
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GPT_SoVITS/inference_webui.py
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@ -198,12 +198,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
phones1 = cleaned_text_to_sequence(phones1) phones1 = cleaned_text_to_sequence(phones1)
texts = text.split("\n") texts = text.split("\n")
audio_opt = [] audio_opt = []
for text in texts:
# 解决输入目标文本的空行导致报错的问题
if (len(text.strip()) == 0):
continue
phones2, word2ph2, norm_text2 = clean_text(text, text_language)
phones2 = cleaned_text_to_sequence(phones2)
if prompt_language == "zh": if prompt_language == "zh":
bert1 = get_bert_feature(norm_text1, word2ph1).to(device) bert1 = get_bert_feature(norm_text1, word2ph1).to(device)
else: else:
@ -211,6 +206,14 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
(1024, len(phones1)), (1024, len(phones1)),
dtype=torch.float16 if is_half == True else torch.float32, dtype=torch.float16 if is_half == True else torch.float32,
).to(device) ).to(device)
for text in texts:
# 解决输入目标文本的空行导致报错的问题
if (len(text.strip()) == 0):
continue
phones2, word2ph2, norm_text2 = clean_text(text, text_language)
phones2 = cleaned_text_to_sequence(phones2)
if text_language == "zh": if text_language == "zh":
bert2 = get_bert_feature(norm_text2, word2ph2).to(device) bert2 = get_bert_feature(norm_text2, word2ph2).to(device)
else: else: