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Move monkeypatch for diffusers/torch bug to hotfixes.py

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This commit is contained in:
Sergey Borisov 2023-08-28 18:29:49 +03:00
parent 3efb1f6f17
commit bb085c5fba
2 changed files with 17 additions and 11 deletions
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13
invokeai/backend/model_management/seamless.py
View File

@ -1,7 +1,7 @@
from __future__ import annotations
from contextlib import contextmanager
from typing import Union
from typing import Union, List
import diffusers
import torch.nn as nn
from diffusers.models import UNet2DModel, AutoencoderKL
@ -24,11 +24,8 @@ def _conv_forward_asymmetric(self, input, weight, bias):
)
ModelType = Union[UNet2DModel, AutoencoderKL]
@contextmanager
def set_seamless(model: ModelType, seamless_axes):
def set_seamless(model: Union[UNet2DModel, AutoencoderKL], seamless_axes: List[str]):
try:
to_restore = []
@ -53,8 +50,6 @@ def set_seamless(model: ModelType, seamless_axes):
to_restore.append((m, m._conv_forward))
m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
if isinstance(m, diffusers.models.lora.LoRACompatibleConv) and m.lora_layer is None:
m.forward = nn.Conv2d.forward.__get__(m, nn.Conv2d)
yield
@ -65,7 +60,3 @@ def set_seamless(model: ModelType, seamless_axes):
del m.asymmetric_padding_mode
if hasattr(m, "asymmetric_padding"):
del m.asymmetric_padding
if isinstance(m, diffusers.models.lora.LoRACompatibleConv):
m.forward = diffusers.models.lora.LoRACompatibleConv.forward.__get__(
m, diffusers.models.lora.LoRACompatibleConv
)

15
invokeai/backend/util/hotfixes.py
View File

@ -761,3 +761,18 @@ class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
diffusers.ControlNetModel = ControlNetModel
diffusers.models.controlnet.ControlNetModel = ControlNetModel
# patch LoRACompatibleConv to use original Conv2D forward function
# this needed to make work seamless patch
# NOTE: with this patch, torch.compile crashes on 2.0 torch(already fixed in nightly)
# https://github.com/huggingface/diffusers/pull/4315
# https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/lora.py#L96C18-L96C18
def new_LoRACompatibleConv_forward(self, x):
if self.lora_layer is None:
return super(diffusers.models.lora.LoRACompatibleConv, self).forward(x)
else:
return super(diffusers.models.lora.LoRACompatibleConv, self).forward(x) + self.lora_layer(x)
diffusers.models.lora.LoRACompatibleConv.forward = new_LoRACompatibleConv_forward