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Update network_lora.py for LyCORIS loading on Diffusers Backend

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This commit is contained in:
AI-Casanova
2023-10-07 12:13:59 -05:00
committed by GitHub
parent b41d3b2efb
commit 4c9459c054
1 changed files with 6 additions and 2 deletions
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extensions-builtin/Lora/network_lora.py
+6 -2
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@@ -1,5 +1,6 @@
import torch
import diffusers.models.lora as diffusers_lora
import lyco_helpers
import network
from modules import devices
@@ -24,8 +25,8 @@ class NetworkModuleLora(network.NetworkModule):
weight = weights.get(key)
if weight is None and none_ok:
return None
is_linear = type(self.sd_module) in [torch.nn.Linear, torch.nn.modules.linear.NonDynamicallyQuantizableLinear, torch.nn.MultiheadAttention]
is_conv = type(self.sd_module) in [torch.nn.Conv2d]
is_linear = type(self.sd_module) in [torch.nn.Linear, torch.nn.modules.linear.NonDynamicallyQuantizableLinear, torch.nn.MultiheadAttention, diffusers_lora.LoRACompatibleLinear]
is_conv = type(self.sd_module) in [torch.nn.Conv2d, diffusers_lora.LoRACompatibleConv]
if is_linear:
weight = weight.reshape(weight.shape[0], -1)
module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False)
@@ -68,4 +69,7 @@ class NetworkModuleLora(network.NetworkModule):
def forward(self, x, y):
self.up_model.to(device=devices.device)
self.down_model.to(device=devices.device)
if hasattr(y, "scale"):
return y(scale=1) + self.up_model(self.down_model(x)) * self.multiplier() * self.calc_scale()
return y + self.up_model(self.down_model(x)) * self.multiplier() * self.calc_scale()