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Fix bugs for torch.nn.MultiheadAttention

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This commit is contained in:
Kohaku-Blueleaf
2024-03-09 12:31:32 +08:00
parent 12bcacf413
commit 851c3d51ed
2 changed files with 13 additions and 4 deletions
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9
extensions-builtin/Lora/networks.py
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@@ -429,9 +429,12 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
if isinstance(self, torch.nn.MultiheadAttention) and module_q and module_k and module_v and module_out:
try:
with torch.no_grad():
updown_q, _ = module_q.calc_updown(self.in_proj_weight)
updown_k, _ = module_k.calc_updown(self.in_proj_weight)
updown_v, _ = module_v.calc_updown(self.in_proj_weight)
# Send "real" orig_weight into MHA's lora module
qw, kw, vw = self.in_proj_weight.chunk(3, 0)
updown_q, _ = module_q.calc_updown(qw)
updown_k, _ = module_k.calc_updown(kw)
updown_v, _ = module_v.calc_updown(vw)
del qw, kw, vw
updown_qkv = torch.vstack([updown_q, updown_k, updown_v])
updown_out, ex_bias = module_out.calc_updown(self.out_proj.weight)