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stable-diffusion-webui
Commits
2ab3d593
Commit
2ab3d593
authored
Sep 26, 2022
by
DepFA
Committed by
AUTOMATIC1111
Sep 27, 2022
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pass extra KDiffusionSampler function parameters
parent
6b78833e
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1 changed file
with
18 additions
and
2 deletions
+18
-2
sd_samplers.py
modules/sd_samplers.py
+18
-2
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modules/sd_samplers.py
View file @
2ab3d593
...
@@ -37,6 +37,11 @@ samplers = [
...
@@ -37,6 +37,11 @@ samplers = [
]
]
samplers_for_img2img
=
[
x
for
x
in
samplers
if
x
.
name
!=
'PLMS'
]
samplers_for_img2img
=
[
x
for
x
in
samplers
if
x
.
name
!=
'PLMS'
]
sampler_extra_params
=
{
'sample_euler'
:[
's_churn'
,
's_tmin'
,
's_noise'
],
'sample_heun'
:[
's_churn'
,
's_tmin'
,
's_noise'
],
'sample_dpm_2'
:[
's_churn'
,
's_tmin'
,
's_noise'
],
}
def
setup_img2img_steps
(
p
,
steps
=
None
):
def
setup_img2img_steps
(
p
,
steps
=
None
):
if
opts
.
img2img_fix_steps
or
steps
is
not
None
:
if
opts
.
img2img_fix_steps
or
steps
is
not
None
:
...
@@ -224,6 +229,7 @@ class KDiffusionSampler:
...
@@ -224,6 +229,7 @@ class KDiffusionSampler:
self
.
model_wrap
=
k_diffusion
.
external
.
CompVisDenoiser
(
sd_model
,
quantize
=
shared
.
opts
.
enable_quantization
)
self
.
model_wrap
=
k_diffusion
.
external
.
CompVisDenoiser
(
sd_model
,
quantize
=
shared
.
opts
.
enable_quantization
)
self
.
funcname
=
funcname
self
.
funcname
=
funcname
self
.
func
=
getattr
(
k_diffusion
.
sampling
,
self
.
funcname
)
self
.
func
=
getattr
(
k_diffusion
.
sampling
,
self
.
funcname
)
self
.
extra_params
=
sampler_extra_params
.
get
(
funcname
,[])
self
.
model_wrap_cfg
=
CFGDenoiser
(
self
.
model_wrap
)
self
.
model_wrap_cfg
=
CFGDenoiser
(
self
.
model_wrap
)
self
.
sampler_noises
=
None
self
.
sampler_noises
=
None
self
.
sampler_noise_index
=
0
self
.
sampler_noise_index
=
0
...
@@ -269,7 +275,12 @@ class KDiffusionSampler:
...
@@ -269,7 +275,12 @@ class KDiffusionSampler:
if
self
.
sampler_noises
is
not
None
:
if
self
.
sampler_noises
is
not
None
:
k_diffusion
.
sampling
.
torch
=
TorchHijack
(
self
)
k_diffusion
.
sampling
.
torch
=
TorchHijack
(
self
)
return
self
.
func
(
self
.
model_wrap_cfg
,
xi
,
sigma_sched
,
extra_args
=
{
'cond'
:
conditioning
,
'uncond'
:
unconditional_conditioning
,
'cond_scale'
:
p
.
cfg_scale
},
disable
=
False
,
callback
=
self
.
callback_state
)
extra_params_kwargs
=
{}
for
val
in
self
.
extra_params
:
if
hasattr
(
opts
,
val
):
extra_params_kwargs
[
val
]
=
getattr
(
opts
,
val
)
return
self
.
func
(
self
.
model_wrap_cfg
,
xi
,
sigma_sched
,
extra_args
=
{
'cond'
:
conditioning
,
'uncond'
:
unconditional_conditioning
,
'cond_scale'
:
p
.
cfg_scale
},
disable
=
False
,
callback
=
self
.
callback_state
,
**
extra_params_kwargs
)
def
sample
(
self
,
p
,
x
,
conditioning
,
unconditional_conditioning
,
steps
=
None
):
def
sample
(
self
,
p
,
x
,
conditioning
,
unconditional_conditioning
,
steps
=
None
):
steps
=
steps
or
p
.
steps
steps
=
steps
or
p
.
steps
...
@@ -286,7 +297,12 @@ class KDiffusionSampler:
...
@@ -286,7 +297,12 @@ class KDiffusionSampler:
if
self
.
sampler_noises
is
not
None
:
if
self
.
sampler_noises
is
not
None
:
k_diffusion
.
sampling
.
torch
=
TorchHijack
(
self
)
k_diffusion
.
sampling
.
torch
=
TorchHijack
(
self
)
samples
=
self
.
func
(
self
.
model_wrap_cfg
,
x
,
sigmas
,
extra_args
=
{
'cond'
:
conditioning
,
'uncond'
:
unconditional_conditioning
,
'cond_scale'
:
p
.
cfg_scale
},
disable
=
False
,
callback
=
self
.
callback_state
)
extra_params_kwargs
=
{}
for
val
in
self
.
extra_params
:
if
hasattr
(
opts
,
val
):
extra_params_kwargs
[
val
]
=
getattr
(
opts
,
val
)
samples
=
self
.
func
(
self
.
model_wrap_cfg
,
x
,
sigmas
,
extra_args
=
{
'cond'
:
conditioning
,
'uncond'
:
unconditional_conditioning
,
'cond_scale'
:
p
.
cfg_scale
},
disable
=
False
,
callback
=
self
.
callback_state
,
**
extra_params_kwargs
)
return
samples
return
samples
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