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https://github.com/vladmandic/automatic
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@@ -121,7 +121,6 @@ class TransformerSALayer(nn.Module):
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tgt_mask: Optional[Tensor] = None,
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tgt_key_padding_mask: Optional[Tensor] = None,
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query_pos: Optional[Tensor] = None):
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# self attention
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tgt2 = self.norm1(tgt)
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q = k = self.with_pos_embed(tgt2, query_pos)
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@@ -275,4 +274,4 @@ class CodeFormer(VQAutoEncoder):
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x = self.fuse_convs_dict[f_size](enc_feat_dict[f_size].detach(), x, w)
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out = x
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# logits doesn't need softmax before cross_entropy loss
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return out, logits, lq_feat
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return out, logits, lq_feat
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