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Use self.scale instead of custom finalize

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Kohaku-Blueleaf
2023-12-14 01:43:24 +08:00
parent 735c9e8059
commit 265bc26c21
1 changed files with 2 additions and 18 deletions
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20
extensions-builtin/Lora/network_oft.py
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@@ -21,6 +21,8 @@ class NetworkModuleOFT(network.NetworkModule):
self.lin_module = None self.lin_module = None
self.org_module: list[torch.Module] = [self.sd_module] self.org_module: list[torch.Module] = [self.sd_module]
self.scale = 1.0
# kohya-ss # kohya-ss
if "oft_blocks" in weights.w.keys(): if "oft_blocks" in weights.w.keys():
self.is_kohya = True self.is_kohya = True
@@ -78,21 +80,3 @@ class NetworkModuleOFT(network.NetworkModule):
print(torch.norm(updown)) print(torch.norm(updown))
output_shape = orig_weight.shape output_shape = orig_weight.shape
return self.finalize_updown(updown, orig_weight, output_shape) return self.finalize_updown(updown, orig_weight, output_shape)
def finalize_updown(self, updown, orig_weight, output_shape, ex_bias=None):
if self.bias is not None:
updown = updown.reshape(self.bias.shape)
updown += self.bias.to(orig_weight.device, dtype=orig_weight.dtype)
updown = updown.reshape(output_shape)
if len(output_shape) == 4:
updown = updown.reshape(output_shape)
if orig_weight.size().numel() == updown.size().numel():
updown = updown.reshape(orig_weight.shape)
if ex_bias is not None:
ex_bias = ex_bias * self.multiplier()
# Ignore calc_scale, which is not used in OFT.
return updown * self.multiplier(), ex_bias