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修复了一些bug,优化了一些代码

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chasonjiang
2024-03-11 17:16:04 +08:00
parent 3535cfe3b0
commit d23f3a62c4
5 changed files with 72 additions and 51 deletions
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37
GPT_SoVITS/AR/models/t2s_model.py
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@@ -229,10 +229,15 @@ class Text2SemanticDecoder(nn.Module):
ignore_index=self.EOS,
)
if not flash_attn_enabled:
self.enable_flash_attn(flash_attn_enabled)
def enable_flash_attn(self, enable:bool=True):
if not enable:
print("Not Using Flash Attention")
self.infer_panel = self.infer_panel_batch_only
else:
self.infer_panel = self.infer_panel_batch_infer_with_flash_attn
print("Using Flash Attention")
blocks = []
@@ -497,7 +502,7 @@ class Text2SemanticDecoder(nn.Module):
# 错位
return targets[:, :-1], targets[:, 1:]
def infer_panel(
def infer_panel_batch_infer_with_flash_attn(
self,
x, #####全部文本token
x_lens,
@@ -508,8 +513,10 @@ class Text2SemanticDecoder(nn.Module):
early_stop_num: int = -1,
temperature: float = 1.0,
):
bert_feature = self.bert_proj(bert_feature.transpose(1, 2))
x = self.ar_text_embedding(x)
x = x + self.bert_proj(bert_feature.transpose(1, 2))
x = x + bert_feature
x = self.ar_text_position(x)
# AR Decoder
@@ -546,30 +553,28 @@ class Text2SemanticDecoder(nn.Module):
y_lens = torch.LongTensor([y_len]*bsz).to(x.device)
y_mask = make_pad_mask(y_lens)
x_mask = make_pad_mask(x_lens)
# (bsz, x_len + y_len)
xy_padding_mask = torch.concat([x_mask, y_mask], dim=1)
_xy_padding_mask = (
xy_padding_mask.view(bsz, 1, 1, src_len).expand(-1, self.num_head, -1, -1)
)
x_attn_mask_pad = F.pad(
x_mask = F.pad(
x_attn_mask,
(0, y_len), ###xx的纯0扩展到xx纯0+xy纯1，(x,x+y)
value=True,
)
y_attn_mask = F.pad( ###yy的右上1扩展到左边xy的0,(y,x+y)
y_mask = F.pad( ###yy的右上1扩展到左边xy的0,(y,x+y)
torch.triu(torch.ones(y_len, y_len, dtype=torch.bool), diagonal=1),
(x_len, 0),
value=False,
)
xy_attn_mask = torch.concat([x_attn_mask_pad, y_attn_mask], dim=0).to(
x.device
)
xy_attn_mask = xy_attn_mask.logical_or(_xy_padding_mask)
xy_mask = torch.concat([x_mask, y_mask], dim=0).view(1 , src_len, src_len).expand(bsz, -1, -1).to(x.device)
# xy_mask = torch.triu(torch.ones(src_len, src_len, dtype=torch.bool, device=x.device), diagonal=1)
xy_padding_mask = xy_padding_mask.view(bsz, 1, src_len).expand(-1, src_len, src_len)
xy_attn_mask = xy_mask.logical_or(xy_padding_mask)
xy_attn_mask = xy_attn_mask.unsqueeze(1).expand(-1, self.num_head, -1, -1)
new_attn_mask = torch.zeros_like(xy_attn_mask, dtype=x.dtype)
new_attn_mask.masked_fill_(xy_attn_mask, float("-inf"))
xy_attn_mask = new_attn_mask
xy_attn_mask = new_attn_mask.masked_fill(xy_attn_mask, float("-inf"))
###### decode #####
y_list = [None]*y.shape[0]
@@ -641,7 +646,7 @@ class Text2SemanticDecoder(nn.Module):
####################### update next step ###################################
y_emb = self.ar_audio_embedding(y[:, -1:])
xy_pos = y_emb * self.ar_audio_position.x_scale + self.ar_audio_position.alpha * self.ar_audio_position.pe[:, y_len + idx].to( dtype= y_emb.dtype,device=y_emb.device)
if (None in idx_list):
for i in range(x.shape[0]):
if idx_list[i] is None: