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novelai-storage
Stable Diffusion Webui
Commits
599f61a1
Commit
599f61a1
authored
Aug 13, 2023
by
AUTOMATIC1111
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use dataclass for StableDiffusionProcessing
parent
fa9370b7
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2 changed files
with
176 additions
and
147 deletions
+176
-147
modules/processing.py
modules/processing.py
+172
-146
modules/sd_samplers_common.py
modules/sd_samplers_common.py
+4
-1
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modules/processing.py
View file @
599f61a1
from
__future__
import
annotations
import
json
import
logging
import
math
import
os
import
sys
import
hashlib
from
dataclasses
import
dataclass
,
field
import
torch
import
numpy
as
np
...
...
@@ -11,7 +13,7 @@ from PIL import Image, ImageOps
import
random
import
cv2
from
skimage
import
exposure
from
typing
import
Any
,
Dict
,
List
from
typing
import
Any
import
modules.sd_hijack
from
modules
import
devices
,
prompt_parser
,
masking
,
sd_samplers
,
lowvram
,
generation_parameters_copypaste
,
extra_networks
,
sd_vae_approx
,
scripts
,
sd_samplers_common
,
sd_unet
,
errors
,
rng
...
...
@@ -104,106 +106,126 @@ def txt2img_image_conditioning(sd_model, x, width, height):
return
x
.
new_zeros
(
x
.
shape
[
0
],
5
,
1
,
1
,
dtype
=
x
.
dtype
,
device
=
x
.
device
)
@
dataclass
(
repr
=
False
)
class
StableDiffusionProcessing
:
"""
The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
"""
sd_model
:
object
=
None
outpath_samples
:
str
=
None
outpath_grids
:
str
=
None
prompt
:
str
=
""
prompt_for_display
:
str
=
None
negative_prompt
:
str
=
""
styles
:
list
[
str
]
=
field
(
default_factory
=
list
)
seed
:
int
=
-
1
subseed
:
int
=
-
1
subseed_strength
:
float
=
0
seed_resize_from_h
:
int
=
-
1
seed_resize_from_w
:
int
=
-
1
seed_enable_extras
:
bool
=
True
sampler_name
:
str
=
None
batch_size
:
int
=
1
n_iter
:
int
=
1
steps
:
int
=
50
cfg_scale
:
float
=
7.0
width
:
int
=
512
height
:
int
=
512
restore_faces
:
bool
=
None
tiling
:
bool
=
None
do_not_save_samples
:
bool
=
False
do_not_save_grid
:
bool
=
False
extra_generation_params
:
dict
[
str
,
Any
]
=
None
overlay_images
:
list
=
None
eta
:
float
=
None
do_not_reload_embeddings
:
bool
=
False
denoising_strength
:
float
=
0
ddim_discretize
:
str
=
None
s_min_uncond
:
float
=
None
s_churn
:
float
=
None
s_tmax
:
float
=
None
s_tmin
:
float
=
None
s_noise
:
float
=
None
override_settings
:
dict
[
str
,
Any
]
=
None
override_settings_restore_afterwards
:
bool
=
True
sampler_index
:
int
=
None
refiner_checkpoint
:
str
=
None
refiner_switch_at
:
float
=
None
token_merging_ratio
=
0
token_merging_ratio_hr
=
0
disable_extra_networks
:
bool
=
False
script_args
:
list
=
None
cached_uc
=
[
None
,
None
]
cached_c
=
[
None
,
None
]
def
__init__
(
self
,
sd_model
=
None
,
outpath_samples
=
None
,
outpath_grids
=
None
,
prompt
:
str
=
""
,
styles
:
List
[
str
]
=
None
,
seed
:
int
=
-
1
,
subseed
:
int
=
-
1
,
subseed_strength
:
float
=
0
,
seed_resize_from_h
:
int
=
-
1
,
seed_resize_from_w
:
int
=
-
1
,
seed_enable_extras
:
bool
=
True
,
sampler_name
:
str
=
None
,
batch_size
:
int
=
1
,
n_iter
:
int
=
1
,
steps
:
int
=
50
,
cfg_scale
:
float
=
7.0
,
width
:
int
=
512
,
height
:
int
=
512
,
restore_faces
:
bool
=
None
,
tiling
:
bool
=
None
,
do_not_save_samples
:
bool
=
False
,
do_not_save_grid
:
bool
=
False
,
extra_generation_params
:
Dict
[
Any
,
Any
]
=
None
,
overlay_images
:
Any
=
None
,
negative_prompt
:
str
=
None
,
eta
:
float
=
None
,
do_not_reload_embeddings
:
bool
=
False
,
denoising_strength
:
float
=
0
,
ddim_discretize
:
str
=
None
,
s_min_uncond
:
float
=
0.0
,
s_churn
:
float
=
0.0
,
s_tmax
:
float
=
None
,
s_tmin
:
float
=
0.0
,
s_noise
:
float
=
None
,
override_settings
:
Dict
[
str
,
Any
]
=
None
,
override_settings_restore_afterwards
:
bool
=
True
,
sampler_index
:
int
=
None
,
refiner_checkpoint
:
str
=
None
,
refiner_switch_at
:
float
=
None
,
script_args
:
list
=
None
):
if
sampler_index
is
not
None
:
sampler
:
sd_samplers_common
.
Sampler
|
None
=
field
(
default
=
None
,
init
=
False
)
is_using_inpainting_conditioning
:
bool
=
field
(
default
=
False
,
init
=
False
)
paste_to
:
tuple
|
None
=
field
(
default
=
None
,
init
=
False
)
is_hr_pass
:
bool
=
field
(
default
=
False
,
init
=
False
)
c
:
tuple
=
field
(
default
=
None
,
init
=
False
)
uc
:
tuple
=
field
(
default
=
None
,
init
=
False
)
rng
:
rng
.
ImageRNG
|
None
=
field
(
default
=
None
,
init
=
False
)
step_multiplier
:
int
=
field
(
default
=
1
,
init
=
False
)
color_corrections
:
list
=
field
(
default
=
None
,
init
=
False
)
scripts
:
list
=
field
(
default
=
None
,
init
=
False
)
all_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
all_negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
all_seeds
:
list
=
field
(
default
=
None
,
init
=
False
)
all_subseeds
:
list
=
field
(
default
=
None
,
init
=
False
)
iteration
:
int
=
field
(
default
=
0
,
init
=
False
)
main_prompt
:
str
=
field
(
default
=
None
,
init
=
False
)
main_negative_prompt
:
str
=
field
(
default
=
None
,
init
=
False
)
prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
seeds
:
list
=
field
(
default
=
None
,
init
=
False
)
subseeds
:
list
=
field
(
default
=
None
,
init
=
False
)
extra_network_data
:
dict
=
field
(
default
=
None
,
init
=
False
)
user
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_model_name
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_model_hash
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_vae_name
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_vae_hash
:
str
=
field
(
default
=
None
,
init
=
False
)
def
__post_init__
(
self
):
if
self
.
sampler_index
is
not
None
:
print
(
"sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name"
,
file
=
sys
.
stderr
)
self
.
outpath_samples
:
str
=
outpath_samples
self
.
outpath_grids
:
str
=
outpath_grids
self
.
prompt
:
str
=
prompt
self
.
prompt_for_display
:
str
=
None
self
.
negative_prompt
:
str
=
(
negative_prompt
or
""
)
self
.
styles
:
list
=
styles
or
[]
self
.
seed
:
int
=
seed
self
.
subseed
:
int
=
subseed
self
.
subseed_strength
:
float
=
subseed_strength
self
.
seed_resize_from_h
:
int
=
seed_resize_from_h
self
.
seed_resize_from_w
:
int
=
seed_resize_from_w
self
.
sampler_name
:
str
=
sampler_name
self
.
batch_size
:
int
=
batch_size
self
.
n_iter
:
int
=
n_iter
self
.
steps
:
int
=
steps
self
.
cfg_scale
:
float
=
cfg_scale
self
.
width
:
int
=
width
self
.
height
:
int
=
height
self
.
restore_faces
:
bool
=
restore_faces
self
.
tiling
:
bool
=
tiling
self
.
do_not_save_samples
:
bool
=
do_not_save_samples
self
.
do_not_save_grid
:
bool
=
do_not_save_grid
self
.
extra_generation_params
:
dict
=
extra_generation_params
or
{}
self
.
overlay_images
=
overlay_images
self
.
eta
=
eta
self
.
do_not_reload_embeddings
=
do_not_reload_embeddings
self
.
paste_to
=
None
self
.
color_corrections
=
None
self
.
denoising_strength
:
float
=
denoising_strength
self
.
sampler_noise_scheduler_override
=
None
self
.
ddim_discretize
=
ddim_discretize
or
opts
.
ddim_discretize
self
.
s_min_uncond
=
s_min_uncond
or
opts
.
s_min_uncond
self
.
s_churn
=
s_churn
or
opts
.
s_churn
self
.
s_tmin
=
s_tmin
or
opts
.
s_tmin
self
.
s_tmax
=
(
s_tmax
if
s_tmax
is
not
None
else
opts
.
s_tmax
)
or
float
(
'inf'
)
self
.
s_noise
=
s_noise
if
s_noise
is
not
None
else
opts
.
s_noise
self
.
override_settings
=
{
k
:
v
for
k
,
v
in
(
override_settings
or
{})
.
items
()
if
k
not
in
shared
.
restricted_opts
}
self
.
override_settings_restore_afterwards
=
override_settings_restore_afterwards
self
.
refiner_checkpoint
=
refiner_checkpoint
self
.
refiner_switch_at
=
refiner_switch_at
self
.
is_using_inpainting_conditioning
=
False
self
.
disable_extra_networks
=
False
self
.
token_merging_ratio
=
0
self
.
token_merging_ratio_hr
=
0
self
.
s_min_uncond
=
self
.
s_min_uncond
if
self
.
s_min_uncond
is
not
None
else
opts
.
s_min_uncond
self
.
s_churn
=
self
.
s_churn
if
self
.
s_churn
is
not
None
else
opts
.
s_churn
self
.
s_tmin
=
self
.
s_tmin
if
self
.
s_tmin
is
not
None
else
opts
.
s_tmin
self
.
s_tmax
=
(
self
.
s_tmax
if
self
.
s_tmax
is
not
None
else
opts
.
s_tmax
)
or
float
(
'inf'
)
self
.
s_noise
=
self
.
s_noise
if
self
.
s_noise
is
not
None
else
opts
.
s_noise
self
.
extra_generation_params
=
self
.
extra_generation_params
or
{}
self
.
override_settings
=
self
.
override_settings
or
{}
self
.
script_args
=
self
.
script_args
or
{}
self
.
refiner_checkpoint_info
=
None
if
not
seed_enable_extras
:
if
not
se
lf
.
se
ed_enable_extras
:
self
.
subseed
=
-
1
self
.
subseed_strength
=
0
self
.
seed_resize_from_h
=
0
self
.
seed_resize_from_w
=
0
self
.
scripts
=
None
self
.
script_args
=
script_args
self
.
all_prompts
=
None
self
.
all_negative_prompts
=
None
self
.
all_seeds
=
None
self
.
all_subseeds
=
None
self
.
iteration
=
0
self
.
is_hr_pass
=
False
self
.
sampler
=
None
self
.
main_prompt
=
None
self
.
main_negative_prompt
=
None
self
.
prompts
=
None
self
.
negative_prompts
=
None
self
.
extra_network_data
=
None
self
.
seeds
=
None
self
.
subseeds
=
None
self
.
step_multiplier
=
1
self
.
cached_uc
=
StableDiffusionProcessing
.
cached_uc
self
.
cached_c
=
StableDiffusionProcessing
.
cached_c
self
.
uc
=
None
self
.
c
=
None
self
.
rng
:
rng
.
ImageRNG
=
None
self
.
user
=
None
self
.
sd_model_name
=
None
self
.
sd_model_hash
=
None
self
.
sd_vae_name
=
None
self
.
sd_vae_hash
=
None
@
property
def
sd_model
(
self
):
return
shared
.
sd_model
@
sd_model
.
setter
def
sd_model
(
self
,
value
):
pass
def
txt2img_image_conditioning
(
self
,
x
,
width
=
None
,
height
=
None
):
self
.
is_using_inpainting_conditioning
=
self
.
sd_model
.
model
.
conditioning_key
in
{
'hybrid'
,
'concat'
}
...
...
@@ -932,49 +954,51 @@ def old_hires_fix_first_pass_dimensions(width, height):
return
width
,
height
@
dataclass
(
repr
=
False
)
class
StableDiffusionProcessingTxt2Img
(
StableDiffusionProcessing
):
sampler
=
None
enable_hr
:
bool
=
False
denoising_strength
:
float
=
0.75
firstphase_width
:
int
=
0
firstphase_height
:
int
=
0
hr_scale
:
float
=
2.0
hr_upscaler
:
str
=
None
hr_second_pass_steps
:
int
=
0
hr_resize_x
:
int
=
0
hr_resize_y
:
int
=
0
hr_checkpoint_name
:
str
=
None
hr_sampler_name
:
str
=
None
hr_prompt
:
str
=
''
hr_negative_prompt
:
str
=
''
cached_hr_uc
=
[
None
,
None
]
cached_hr_c
=
[
None
,
None
]
def
__init__
(
self
,
enable_hr
:
bool
=
False
,
denoising_strength
:
float
=
0.75
,
firstphase_width
:
int
=
0
,
firstphase_height
:
int
=
0
,
hr_scale
:
float
=
2.0
,
hr_upscaler
:
str
=
None
,
hr_second_pass_steps
:
int
=
0
,
hr_resize_x
:
int
=
0
,
hr_resize_y
:
int
=
0
,
hr_checkpoint_name
:
str
=
None
,
hr_sampler_name
:
str
=
None
,
hr_prompt
:
str
=
''
,
hr_negative_prompt
:
str
=
''
,
**
kwargs
):
super
()
.
__init__
(
**
kwargs
)
self
.
enable_hr
=
enable_hr
self
.
denoising_strength
=
denoising_strength
self
.
hr_scale
=
hr_scale
self
.
hr_upscaler
=
hr_upscaler
self
.
hr_second_pass_steps
=
hr_second_pass_steps
self
.
hr_resize_x
=
hr_resize_x
self
.
hr_resize_y
=
hr_resize_y
self
.
hr_upscale_to_x
=
hr_resize_x
self
.
hr_upscale_to_y
=
hr_resize_y
self
.
hr_checkpoint_name
=
hr_checkpoint_name
self
.
hr_checkpoint_info
=
None
self
.
hr_sampler_name
=
hr_sampler_name
self
.
hr_prompt
=
hr_prompt
self
.
hr_negative_prompt
=
hr_negative_prompt
self
.
all_hr_prompts
=
None
self
.
all_hr_negative_prompts
=
None
self
.
latent_scale_mode
=
None
if
firstphase_width
!=
0
or
firstphase_height
!=
0
:
hr_checkpoint_info
:
dict
=
field
(
default
=
None
,
init
=
False
)
hr_upscale_to_x
:
int
=
field
(
default
=
0
,
init
=
False
)
hr_upscale_to_y
:
int
=
field
(
default
=
0
,
init
=
False
)
truncate_x
:
int
=
field
(
default
=
0
,
init
=
False
)
truncate_y
:
int
=
field
(
default
=
0
,
init
=
False
)
applied_old_hires_behavior_to
:
tuple
=
field
(
default
=
None
,
init
=
False
)
latent_scale_mode
:
dict
=
field
(
default
=
None
,
init
=
False
)
hr_c
:
tuple
|
None
=
field
(
default
=
None
,
init
=
False
)
hr_uc
:
tuple
|
None
=
field
(
default
=
None
,
init
=
False
)
all_hr_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
all_hr_negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
hr_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
hr_negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
hr_extra_network_data
:
list
=
field
(
default
=
None
,
init
=
False
)
def
__post_init__
(
self
):
super
()
.
__post_init__
()
if
self
.
firstphase_width
!=
0
or
self
.
firstphase_height
!=
0
:
self
.
hr_upscale_to_x
=
self
.
width
self
.
hr_upscale_to_y
=
self
.
height
self
.
width
=
firstphase_width
self
.
height
=
firstphase_height
self
.
truncate_x
=
0
self
.
truncate_y
=
0
self
.
applied_old_hires_behavior_to
=
None
self
.
hr_prompts
=
None
self
.
hr_negative_prompts
=
None
self
.
hr_extra_network_data
=
None
self
.
width
=
self
.
firstphase_width
self
.
height
=
self
.
firstphase_height
self
.
cached_hr_uc
=
StableDiffusionProcessingTxt2Img
.
cached_hr_uc
self
.
cached_hr_c
=
StableDiffusionProcessingTxt2Img
.
cached_hr_c
self
.
hr_c
=
None
self
.
hr_uc
=
None
def
calculate_target_resolution
(
self
):
if
opts
.
use_old_hires_fix_width_height
and
self
.
applied_old_hires_behavior_to
!=
(
self
.
width
,
self
.
height
):
...
...
@@ -1252,7 +1276,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
return
super
()
.
get_conds
()
def
parse_extra_network_prompts
(
self
):
res
=
super
()
.
parse_extra_network_prompts
()
...
...
@@ -1265,32 +1288,37 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
return
res
@
dataclass
(
repr
=
False
)
class
StableDiffusionProcessingImg2Img
(
StableDiffusionProcessing
):
sampler
=
None
def
__init__
(
self
,
init_images
:
list
=
None
,
resize_mode
:
int
=
0
,
denoising_strength
:
float
=
0.75
,
image_cfg_scale
:
float
=
None
,
mask
:
Any
=
None
,
mask_blur
:
int
=
None
,
mask_blur_x
:
int
=
4
,
mask_blur_y
:
int
=
4
,
inpainting_fill
:
int
=
0
,
inpaint_full_res
:
bool
=
True
,
inpaint_full_res_padding
:
int
=
0
,
inpainting_mask_invert
:
int
=
0
,
initial_noise_multiplier
:
float
=
None
,
**
kwargs
):
super
()
.
__init__
(
**
kwargs
)
self
.
init_images
=
init_images
self
.
resize_mode
:
int
=
resize_mode
self
.
denoising_strength
:
float
=
denoising_strength
self
.
image_cfg_scale
:
float
=
image_cfg_scale
if
shared
.
sd_model
.
cond_stage_key
==
"edit"
else
None
self
.
init_latent
=
None
self
.
image_mask
=
mask
self
.
latent_mask
=
None
self
.
mask_for_overlay
=
None
self
.
mask_blur_x
=
mask_blur_x
self
.
mask_blur_y
=
mask_blur_y
if
mask_blur
is
not
None
:
self
.
mask_blur
=
mask_blur
self
.
inpainting_fill
=
inpainting_fill
self
.
inpaint_full_res
=
inpaint_full_res
self
.
inpaint_full_res_padding
=
inpaint_full_res_padding
self
.
inpainting_mask_invert
=
inpainting_mask_invert
self
.
initial_noise_multiplier
=
opts
.
initial_noise_multiplier
if
initial_noise_multiplier
is
None
else
initial_noise_multiplier
init_images
:
list
=
None
resize_mode
:
int
=
0
denoising_strength
:
float
=
0.75
image_cfg_scale
:
float
=
None
mask
:
Any
=
None
mask_blur_x
:
int
=
4
mask_blur_y
:
int
=
4
mask_blur
:
int
=
None
inpainting_fill
:
int
=
0
inpaint_full_res
:
bool
=
True
inpaint_full_res_padding
:
int
=
0
inpainting_mask_invert
:
int
=
0
initial_noise_multiplier
:
float
=
None
latent_mask
:
Image
=
None
image_mask
:
Any
=
field
(
default
=
None
,
init
=
False
)
nmask
:
torch
.
Tensor
=
field
(
default
=
None
,
init
=
False
)
image_conditioning
:
torch
.
Tensor
=
field
(
default
=
None
,
init
=
False
)
init_img_hash
:
str
=
field
(
default
=
None
,
init
=
False
)
mask_for_overlay
:
Image
=
field
(
default
=
None
,
init
=
False
)
init_latent
:
torch
.
Tensor
=
field
(
default
=
None
,
init
=
False
)
def
__post_init__
(
self
):
super
()
.
__post_init__
()
self
.
image_mask
=
self
.
mask
self
.
mask
=
None
self
.
nmask
=
None
self
.
image_conditioning
=
None
self
.
initial_noise_multiplier
=
opts
.
initial_noise_multiplier
if
self
.
initial_noise_multiplier
is
None
else
self
.
initial_noise_multiplier
@
property
def
mask_blur
(
self
):
...
...
@@ -1300,15 +1328,13 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
@
mask_blur
.
setter
def
mask_blur
(
self
,
value
):
self
.
mask_blur_x
=
value
self
.
mask_blur_y
=
value
@
mask_blur
.
deleter
def
mask_blur
(
self
):
del
self
.
mask_blur_x
del
self
.
mask_blur_y
if
isinstance
(
value
,
int
):
self
.
mask_blur_x
=
value
self
.
mask_blur_y
=
value
def
init
(
self
,
all_prompts
,
all_seeds
,
all_subseeds
):
self
.
image_cfg_scale
:
float
=
self
.
image_cfg_scale
if
shared
.
sd_model
.
cond_stage_key
==
"edit"
else
None
self
.
sampler
=
sd_samplers
.
create_sampler
(
self
.
sampler_name
,
self
.
sd_model
)
crop_region
=
None
...
...
modules/sd_samplers_common.py
View file @
599f61a1
...
...
@@ -305,5 +305,8 @@ class Sampler:
current_iter_seeds
=
p
.
all_seeds
[
p
.
iteration
*
p
.
batch_size
:(
p
.
iteration
+
1
)
*
p
.
batch_size
]
return
BrownianTreeNoiseSampler
(
x
,
sigma_min
,
sigma_max
,
seed
=
current_iter_seeds
)
def
sample
(
self
,
p
,
x
,
conditioning
,
unconditional_conditioning
,
steps
=
None
,
image_conditioning
=
None
):
raise
NotImplementedError
()
def
sample_img2img
(
self
,
p
,
x
,
noise
,
conditioning
,
unconditional_conditioning
,
steps
=
None
,
image_conditioning
=
None
):
raise
NotImplementedError
()
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