store patches for Lora in a specialized module

1 files changed, 18 insertions, 14 deletions

diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py
index 22fdff4a..9fca36b6 100644
--- a/extensions-builtin/Lora/networks.py
+++ b/extensions-builtin/Lora/networks.py
@@ -2,6 +2,7 @@ import logging
 import os

 import re

 

+import lora_patches

 import network

 import network_lora

 import network_hada

@@ -418,74 +419,74 @@ def network_reset_cached_weight(self: Union[torch.nn.Conv2d, torch.nn.Linear]):
 

 def network_Linear_forward(self, input):

     if shared.opts.lora_functional:

-        return network_forward(self, input, torch.nn.Linear_forward_before_network)

+        return network_forward(self, input, originals.Linear_forward)

 

     network_apply_weights(self)

 

-    return torch.nn.Linear_forward_before_network(self, input)

+    return originals.Linear_forward(self, input)

 

 

 def network_Linear_load_state_dict(self, *args, **kwargs):

     network_reset_cached_weight(self)

 

-    return torch.nn.Linear_load_state_dict_before_network(self, *args, **kwargs)

+    return originals.Linear_load_state_dict(self, *args, **kwargs)

 

 

 def network_Conv2d_forward(self, input):

     if shared.opts.lora_functional:

-        return network_forward(self, input, torch.nn.Conv2d_forward_before_network)

+        return network_forward(self, input, originals.Conv2d_forward)

 

     network_apply_weights(self)

 

-    return torch.nn.Conv2d_forward_before_network(self, input)

+    return originals.Conv2d_forward(self, input)

 

 

 def network_Conv2d_load_state_dict(self, *args, **kwargs):

     network_reset_cached_weight(self)

 

-    return torch.nn.Conv2d_load_state_dict_before_network(self, *args, **kwargs)

+    return originals.Conv2d_load_state_dict(self, *args, **kwargs)

 

 

 def network_GroupNorm_forward(self, input):

     if shared.opts.lora_functional:

-        return network_forward(self, input, torch.nn.GroupNorm_forward_before_network)

+        return network_forward(self, input, originals.GroupNorm_forward)

 

     network_apply_weights(self)

 

-    return torch.nn.GroupNorm_forward_before_network(self, input)

+    return originals.GroupNorm_forward(self, input)

 

 

 def network_GroupNorm_load_state_dict(self, *args, **kwargs):

     network_reset_cached_weight(self)

 

-    return torch.nn.GroupNorm_load_state_dict_before_network(self, *args, **kwargs)

+    return originals.GroupNorm_load_state_dict(self, *args, **kwargs)

 

 

 def network_LayerNorm_forward(self, input):

     if shared.opts.lora_functional:

-        return network_forward(self, input, torch.nn.LayerNorm_forward_before_network)

+        return network_forward(self, input, originals.LayerNorm_forward)

 

     network_apply_weights(self)

 

-    return torch.nn.LayerNorm_forward_before_network(self, input)

+    return originals.LayerNorm_forward(self, input)

 

 

 def network_LayerNorm_load_state_dict(self, *args, **kwargs):

     network_reset_cached_weight(self)

 

-    return torch.nn.LayerNorm_load_state_dict_before_network(self, *args, **kwargs)

+    return originals.LayerNorm_load_state_dict(self, *args, **kwargs)

 

 

 def network_MultiheadAttention_forward(self, *args, **kwargs):

     network_apply_weights(self)

 

-    return torch.nn.MultiheadAttention_forward_before_network(self, *args, **kwargs)

+    return originals.MultiheadAttention_forward(self, *args, **kwargs)

 

 

 def network_MultiheadAttention_load_state_dict(self, *args, **kwargs):

     network_reset_cached_weight(self)

 

-    return torch.nn.MultiheadAttention_load_state_dict_before_network(self, *args, **kwargs)

+    return originals.MultiheadAttention_load_state_dict(self, *args, **kwargs)

 

 

 def list_available_networks():

@@ -552,6 +553,9 @@ def infotext_pasted(infotext, params):
     if added:

         params["Prompt"] += "\n" + "".join(added)

 

+

+originals: lora_patches.LoraPatches = None

+

 extra_network_lora = None

 

 available_networks = {}