hoelee/stable-diffusion-webui
1
0
Fork 0
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git synced 2025-08-03 19:02:27 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

custom unet support

Browse Source
This commit is contained in:
AUTOMATIC
2023-05-27 15:47:33 +03:00
parent a6e653be26
commit 339b531570
8 changed files with 148 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
modules/sd_hijack.py
View File

@@ -3,7 +3,7 @@ from torch.nn.functional import silu
from types import MethodType
import modules.textual_inversion.textual_inversion
from modules import devices, sd_hijack_optimizations, shared, script_callbacks, errors
from modules import devices, sd_hijack_optimizations, shared, script_callbacks, errors, sd_unet
from modules.hypernetworks import hypernetwork
from modules.shared import cmd_opts
from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr
@@ -43,7 +43,7 @@ def list_optimizers():
optimizers.extend(new_optimizers)
def apply_optimizations():
def apply_optimizations(option=None):
global current_optimizer
undo_optimizations()
@@ -60,7 +60,7 @@ def apply_optimizations():
current_optimizer.undo()
current_optimizer = None
selection = shared.opts.cross_attention_optimization
selection = option or shared.opts.cross_attention_optimization
if selection == "Automatic" and len(optimizers) > 0:
matching_optimizer = next(iter([x for x in optimizers if x.cmd_opt and getattr(shared.cmd_opts, x.cmd_opt, False)]), optimizers[0])
else:
@@ -72,12 +72,13 @@ def apply_optimizations():
matching_optimizer = optimizers[0]
if matching_optimizer is not None:
print(f"Applying optimization: {matching_optimizer.name}... ", end='')
print(f"Applying attention optimization: {matching_optimizer.name}... ", end='')
matching_optimizer.apply()
print("done.")
current_optimizer = matching_optimizer
return current_optimizer.name
else:
print("Disabling attention optimization")
return ''
@@ -155,9 +156,9 @@ class StableDiffusionModelHijack:
def __init__(self):
self.embedding_db.add_embedding_dir(cmd_opts.embeddings_dir)
def apply_optimizations(self):
def apply_optimizations(self, option=None):
try:
self.optimization_method = apply_optimizations()
self.optimization_method = apply_optimizations(option)
except Exception as e:
errors.display(e, "applying cross attention optimization")
undo_optimizations()
@@ -194,6 +195,11 @@ class StableDiffusionModelHijack:
self.layers = flatten(m)
if not hasattr(ldm.modules.diffusionmodules.openaimodel, 'copy_of_UNetModel_forward_for_webui'):
ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui = ldm.modules.diffusionmodules.openaimodel.UNetModel.forward
ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = sd_unet.UNetModel_forward
def undo_hijack(self, m):
if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:
m.cond_stage_model = m.cond_stage_model.wrapped
@@ -215,6 +221,8 @@ class StableDiffusionModelHijack:
self.layers = None
self.clip = None
ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui
def apply_circular(self, enable):
if self.circular_enabled == enable:
return