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Seamless fixes

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This commit is contained in:
Kent Keirsey 2023-08-28 00:10:46 -04:00
parent 5fdd25501b
commit 1f476692da
2 changed files with 9 additions and 5 deletions
invokeai
app/invocations
model.py
backend/model_management
seamless.py

2
invokeai/app/invocations/model.py

@ -404,7 +404,7 @@ class SeamlessModeOutput(BaseInvocationOutput):
@title("Seamless")
@tags("seamless", "model")
class SeamlessModeInvocation(BaseInvocation):
"""Apply seamless mode to unet."""
"""Applies the seamless transformation to the Model UNet and VAE."""
type: Literal["seamless"] = "seamless"

12
invokeai/backend/model_management/seamless.py

@ -1,7 +1,8 @@
from __future__ import annotations
from contextlib import contextmanager
from typing import TypeVar, Union
from typing import TypeVar
import diffusers
import torch.nn as nn
from diffusers.models import UNet2DModel, AutoencoderKL
@ -22,10 +23,9 @@ def _conv_forward_asymmetric(self, input, weight, bias):
)
@contextmanager
ModelType = TypeVar('ModelType', UNet2DModel, AutoencoderKL)
@contextmanager
def set_seamless(model: ModelType, seamless_axes):
try:
to_restore = []
@ -51,6 +51,8 @@ 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
@ -60,4 +62,6 @@ def set_seamless(model: ModelType, seamless_axes):
if hasattr(m, "asymmetric_padding_mode"):
del m.asymmetric_padding_mode
if hasattr(m, "asymmetric_padding"):
del 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)