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Add Quanto Lora hijack additionally

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Disty0
2024-08-18 00:09:13 +03:00
parent 5a75b120ae
commit d1b87efb92
1 changed files with 8 additions and 10 deletions
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extensions-builtin/Lora/lora_patches.py
+8 -10
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@@ -22,12 +22,11 @@ class LoraPatches:
return
if "Model" in shared.opts.optimum_quanto_weights or "Text Encoder" in shared.opts.optimum_quanto_weights:
from optimum import quanto
self.Linear_forward = patches.patch(__name__, quanto.nn.QLinear, 'forward', networks.network_QLinear_forward)
self.Conv2d_forward = patches.patch(__name__, quanto.nn.QConv2d, 'forward', networks.network_QConv2d_forward)
else:
self.Linear_forward = patches.patch(__name__, torch.nn.Linear, 'forward', networks.network_Linear_forward)
self.Conv2d_forward = patches.patch(__name__, torch.nn.Conv2d, 'forward', networks.network_Conv2d_forward)
self.QLinear_forward = patches.patch(__name__, quanto.nn.QLinear, 'forward', networks.network_QLinear_forward)
self.QConv2d_forward = patches.patch(__name__, quanto.nn.QConv2d, 'forward', networks.network_QConv2d_forward)
self.Linear_forward = patches.patch(__name__, torch.nn.Linear, 'forward', networks.network_Linear_forward)
self.Linear_load_state_dict = patches.patch(__name__, torch.nn.Linear, '_load_from_state_dict', networks.network_Linear_load_state_dict)
self.Conv2d_forward = patches.patch(__name__, torch.nn.Conv2d, 'forward', networks.network_Conv2d_forward)
self.Conv2d_load_state_dict = patches.patch(__name__, torch.nn.Conv2d, '_load_from_state_dict', networks.network_Conv2d_load_state_dict)
self.GroupNorm_forward = patches.patch(__name__, torch.nn.GroupNorm, 'forward', networks.network_GroupNorm_forward)
self.GroupNorm_load_state_dict = patches.patch(__name__, torch.nn.GroupNorm, '_load_from_state_dict', networks.network_GroupNorm_load_state_dict)
@@ -45,12 +44,11 @@ class LoraPatches:
return
if "Model" in shared.opts.optimum_quanto_weights or "Text Encoder" in shared.opts.optimum_quanto_weights:
from optimum import quanto
self.Linear_forward = patches.undo(__name__, quanto.nn.QLinear, 'forward') # pylint: disable=E1128
self.Conv2d_forward = patches.undo(__name__, quanto.nn.QConv2d, 'forward') # pylint: disable=E1128
else:
self.Linear_forward = patches.undo(__name__, torch.nn.Linear, 'forward') # pylint: disable=E1128
self.Conv2d_forward = patches.undo(__name__, torch.nn.Conv2d, 'forward') # pylint: disable=E1128
self.QLinear_forward = patches.undo(__name__, quanto.nn.QLinear, 'forward') # pylint: disable=E1128
self.QConv2d_forward = patches.undo(__name__, quanto.nn.QConv2d, 'forward') # pylint: disable=E1128
self.Linear_forward = patches.undo(__name__, torch.nn.Linear, 'forward') # pylint: disable=E1128
self.Linear_load_state_dict = patches.undo(__name__, torch.nn.Linear, '_load_from_state_dict') # pylint: disable=E1128
self.Conv2d_forward = patches.undo(__name__, torch.nn.Conv2d, 'forward') # pylint: disable=E1128
self.Conv2d_load_state_dict = patches.undo(__name__, torch.nn.Conv2d, '_load_from_state_dict') # pylint: disable=E1128
self.GroupNorm_forward = patches.undo(__name__, torch.nn.GroupNorm, 'forward') # pylint: disable=E1128
self.GroupNorm_load_state_dict = patches.undo(__name__, torch.nn.GroupNorm, '_load_from_state_dict') # pylint: disable=E1128