Skip to content
Projects
Groups
Snippets
Help
Loading...
Help
Contribute to GitLab
Sign in / Register
Toggle navigation
S
stable-diffusion-webui
Project
Project
Details
Activity
Cycle Analytics
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Charts
Issues
0
Issues
0
List
Board
Labels
Milestones
Merge Requests
0
Merge Requests
0
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Charts
Wiki
Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Charts
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
Administrator
stable-diffusion-webui
Commits
399b2297
Commit
399b2297
authored
Dec 24, 2022
by
AUTOMATIC
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
eliminate duplicated code
add an option to samplers for skipping next to last sigma
parent
5667ec4c
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
with
14 additions
and
17 deletions
+14
-17
sd_samplers.py
modules/sd_samplers.py
+14
-17
No files found.
modules/sd_samplers.py
View file @
399b2297
...
...
@@ -23,16 +23,16 @@ samplers_k_diffusion = [
(
'Euler'
,
'sample_euler'
,
[
'k_euler'
],
{}),
(
'LMS'
,
'sample_lms'
,
[
'k_lms'
],
{}),
(
'Heun'
,
'sample_heun'
,
[
'k_heun'
],
{}),
(
'DPM2'
,
'sample_dpm_2'
,
[
'k_dpm_2'
],
{}),
(
'DPM2 a'
,
'sample_dpm_2_ancestral'
,
[
'k_dpm_2_a'
],
{}),
(
'DPM2'
,
'sample_dpm_2'
,
[
'k_dpm_2'
],
{
'discard_next_to_last_sigma'
:
True
}),
(
'DPM2 a'
,
'sample_dpm_2_ancestral'
,
[
'k_dpm_2_a'
],
{
'discard_next_to_last_sigma'
:
True
}),
(
'DPM++ 2S a'
,
'sample_dpmpp_2s_ancestral'
,
[
'k_dpmpp_2s_a'
],
{}),
(
'DPM++ 2M'
,
'sample_dpmpp_2m'
,
[
'k_dpmpp_2m'
],
{}),
(
'DPM++ SDE'
,
'sample_dpmpp_sde'
,
[
'k_dpmpp_sde'
],
{}),
(
'DPM fast'
,
'sample_dpm_fast'
,
[
'k_dpm_fast'
],
{}),
(
'DPM adaptive'
,
'sample_dpm_adaptive'
,
[
'k_dpm_ad'
],
{}),
(
'LMS Karras'
,
'sample_lms'
,
[
'k_lms_ka'
],
{
'scheduler'
:
'karras'
}),
(
'DPM2 Karras'
,
'sample_dpm_2'
,
[
'k_dpm_2_ka'
],
{
'scheduler'
:
'karras'
}),
(
'DPM2 a Karras'
,
'sample_dpm_2_ancestral'
,
[
'k_dpm_2_a_ka'
],
{
'scheduler'
:
'karras'
}),
(
'DPM2 Karras'
,
'sample_dpm_2'
,
[
'k_dpm_2_ka'
],
{
'scheduler'
:
'karras'
,
'discard_next_to_last_sigma'
:
True
}),
(
'DPM2 a Karras'
,
'sample_dpm_2_ancestral'
,
[
'k_dpm_2_a_ka'
],
{
'scheduler'
:
'karras'
,
'discard_next_to_last_sigma'
:
True
}),
(
'DPM++ 2S a Karras'
,
'sample_dpmpp_2s_ancestral'
,
[
'k_dpmpp_2s_a_ka'
],
{
'scheduler'
:
'karras'
}),
(
'DPM++ 2M Karras'
,
'sample_dpmpp_2m'
,
[
'k_dpmpp_2m_ka'
],
{
'scheduler'
:
'karras'
}),
(
'DPM++ SDE Karras'
,
'sample_dpmpp_sde'
,
[
'k_dpmpp_sde_ka'
],
{
'scheduler'
:
'karras'
}),
...
...
@@ -444,9 +444,7 @@ class KDiffusionSampler:
return
extra_params_kwargs
def
sample_img2img
(
self
,
p
,
x
,
noise
,
conditioning
,
unconditional_conditioning
,
steps
=
None
,
image_conditioning
=
None
):
steps
,
t_enc
=
setup_img2img_steps
(
p
,
steps
)
def
get_sigmas
(
self
,
p
,
steps
):
if
p
.
sampler_noise_scheduler_override
:
sigmas
=
p
.
sampler_noise_scheduler_override
(
steps
)
elif
self
.
config
is
not
None
and
self
.
config
.
options
.
get
(
'scheduler'
,
None
)
==
'karras'
:
...
...
@@ -454,9 +452,16 @@ class KDiffusionSampler:
else
:
sigmas
=
self
.
model_wrap
.
get_sigmas
(
steps
)
if
self
.
funcname
in
[
'sample_dpm_2_ancestral'
,
'sample_dpm_2'
]
:
if
self
.
config
is
not
None
and
self
.
config
.
options
.
get
(
'discard_next_to_last_sigma'
,
False
)
:
sigmas
=
torch
.
cat
([
sigmas
[:
-
2
],
sigmas
[
-
1
:]])
return
sigmas
def
sample_img2img
(
self
,
p
,
x
,
noise
,
conditioning
,
unconditional_conditioning
,
steps
=
None
,
image_conditioning
=
None
):
steps
,
t_enc
=
setup_img2img_steps
(
p
,
steps
)
sigmas
=
self
.
get_sigmas
(
p
,
steps
)
sigma_sched
=
sigmas
[
steps
-
t_enc
-
1
:]
xi
=
x
+
noise
*
sigma_sched
[
0
]
...
...
@@ -488,18 +493,10 @@ class KDiffusionSampler:
def
sample
(
self
,
p
,
x
,
conditioning
,
unconditional_conditioning
,
steps
=
None
,
image_conditioning
=
None
):
steps
=
steps
or
p
.
steps
if
p
.
sampler_noise_scheduler_override
:
sigmas
=
p
.
sampler_noise_scheduler_override
(
steps
)
elif
self
.
config
is
not
None
and
self
.
config
.
options
.
get
(
'scheduler'
,
None
)
==
'karras'
:
sigmas
=
k_diffusion
.
sampling
.
get_sigmas_karras
(
n
=
steps
,
sigma_min
=
0.1
,
sigma_max
=
10
,
device
=
shared
.
device
)
else
:
sigmas
=
self
.
model_wrap
.
get_sigmas
(
steps
)
sigmas
=
self
.
get_sigmas
(
p
,
steps
)
x
=
x
*
sigmas
[
0
]
if
self
.
funcname
in
[
'sample_dpm_2_ancestral'
,
'sample_dpm_2'
]:
sigmas
=
torch
.
cat
([
sigmas
[:
-
2
],
sigmas
[
-
1
:]])
extra_params_kwargs
=
self
.
initialize
(
p
)
if
'sigma_min'
in
inspect
.
signature
(
self
.
func
)
.
parameters
:
extra_params_kwargs
[
'sigma_min'
]
=
self
.
model_wrap
.
sigmas
[
0
]
.
item
()
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment