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修复有时候会出现长段无意义音频的bug

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Added logic to handle bad tokens and adjust logits based on repeated tokens during decoding.
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MiaoMiao Li 2025-10-28 16:08:06 +08:00 committed by GitHub
parent 11aa78bd9b
commit 8ca6bf3f11
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1 changed files with 27 additions and 0 deletions
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GPT_SoVITS/AR/models/t2s_model.py
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@ -698,6 +698,10 @@ class Text2SemanticDecoder(nn.Module):
y_list = [None] * y.shape[0]
batch_idx_map = list(range(y.shape[0]))
idx_list = [None] * y.shape[0]
bad_tokens_list = [809, 207,411,679,676,25,23,7]
bad_tokens = torch.tensor(bad_tokens_list, device=x.device, dtype=torch.long)
last_2_token = 0
repeat_count = 0
for idx in tqdm(range(1500)):
if idx == 0:
xy_dec, k_cache, v_cache = self.t2s_transformer.process_prompt(xy_pos, attn_mask, None)
@ -710,7 +714,30 @@ class Text2SemanticDecoder(nn.Module):
logits = logits[:, :-1]
else:
attn_mask = F.pad(attn_mask, (0, 1), value=False)
# 1. 获取上一步生成的 token
last_token = y[:, -1]
# 2. 检查对于批次中的每个序列，其上一步生成的token是否已经重复，如果重复，降低选中概率
# is_last_token_bad 的形状是 [batch_size], dtype=torch.bool
is_last_token_bad = torch.isin(last_token, bad_tokens)
if last_token == last_2_token:
repeat_count += 1
if 0 < logits[:, last_2_token] < 35:
logits[:, last_2_token] *= 0.618**repeat_count
elif logits[:, last_2_token] < 0:
logits[:, last_2_token] *= 1.414**repeat_count
elif logits[:, last_2_token] >= 35:
logits[:, last_2_token] *= 0
else:
logits[:, last_2_token] = -float('inf')
else:
repeat_count = 0
last_2_token = last_token
# 3. 如果某个序列的上一个token是恶性token，则在这一步的logits中，
# 将所有恶性token的概率都设为-inf，以禁止选择它们。
# 我们使用高级索引(advanced indexing)来只修改需要修改的行。
if is_last_token_bad.any():
logits[is_last_token_bad, bad_tokens] = -float('inf')
samples = sample(
logits, y, top_k=top_k, top_p=top_p, repetition_penalty=repetition_penalty, temperature=temperature
)[0]