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Stable Diffusion Webui
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7bb0fbed
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Stable Diffusion Webui
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Stable Diffusion Webui
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7bb0fbed
编写于
7月 18, 2023
作者:
L
lambertae
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code styling
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1
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Showing
1 changed file
with
5 addition
and
9 deletion
+5
-9
modules/sd_samplers_kdiffusion.py
modules/sd_samplers_kdiffusion.py
+5
-9
未找到文件。
modules/sd_samplers_kdiffusion.py
浏览文件 @
7bb0fbed
...
...
@@ -35,17 +35,15 @@ samplers_k_diffusion = [
@
torch
.
no_grad
()
def
restart_sampler
(
model
,
x
,
sigmas
,
extra_args
=
None
,
callback
=
None
,
disable
=
None
,
s_noise
=
1.
,
restart_list
=
{
0.1
:
[
10
,
2
,
2
]}
):
def
restart_sampler
(
model
,
x
,
sigmas
,
extra_args
=
None
,
callback
=
None
,
disable
=
None
,
s_noise
=
1.
):
"""Implements restart sampling in Restart Sampling for Improving Generative Processes (2023)"""
'''Restart_list format: {min_sigma: [ restart_steps, restart_times, max_sigma]}'''
from
tqdm.auto
import
trange
,
tqdm
restart_list
=
{
0.1
:
[
10
,
2
,
2
]}
from
tqdm.auto
import
trange
extra_args
=
{}
if
extra_args
is
None
else
extra_args
s_in
=
x
.
new_ones
([
x
.
shape
[
0
]])
step_id
=
0
from
k_diffusion.sampling
import
to_d
,
append_zero
def
heun_step
(
x
,
old_sigma
,
new_sigma
):
nonlocal
step_id
denoised
=
model
(
x
,
old_sigma
*
s_in
,
**
extra_args
)
...
...
@@ -70,8 +68,6 @@ def restart_sampler(model, x, sigmas, extra_args=None, callback=None, disable=No
for
key
,
value
in
restart_list
.
items
():
temp_list
[
int
(
torch
.
argmin
(
abs
(
sigmas
-
key
),
dim
=
0
))]
=
value
restart_list
=
temp_list
def
get_sigmas_karras
(
n
,
sigma_min
,
sigma_max
,
rho
=
7.
,
device
=
'cpu'
):
ramp
=
torch
.
linspace
(
0
,
1
,
n
).
to
(
device
)
min_inv_rho
=
(
sigma_min
**
(
1
/
rho
))
...
...
@@ -82,7 +78,6 @@ def restart_sampler(model, x, sigmas, extra_args=None, callback=None, disable=No
max_inv_rho
=
max_inv_rho
.
to
(
device
)
sigmas
=
(
max_inv_rho
+
ramp
*
(
min_inv_rho
-
max_inv_rho
))
**
rho
return
append_zero
(
sigmas
).
to
(
device
)
for
i
in
trange
(
len
(
sigmas
)
-
1
,
disable
=
disable
):
x
=
heun_step
(
x
,
sigmas
[
i
],
sigmas
[
i
+
1
])
if
i
+
1
in
restart_list
:
...
...
@@ -91,7 +86,8 @@ def restart_sampler(model, x, sigmas, extra_args=None, callback=None, disable=No
max_idx
=
int
(
torch
.
argmin
(
abs
(
sigmas
-
restart_max
),
dim
=
0
))
if
max_idx
<
min_idx
:
sigma_restart
=
get_sigmas_karras
(
restart_steps
,
sigmas
[
min_idx
],
sigmas
[
max_idx
],
device
=
sigmas
.
device
)[:
-
1
]
# remove the zero at the end
for
times
in
range
(
restart_times
):
while
restart_times
>
0
:
restart_times
-=
1
x
=
x
+
torch
.
randn_like
(
x
)
*
s_noise
*
(
sigmas
[
max_idx
]
**
2
-
sigmas
[
min_idx
]
**
2
)
**
0.5
for
(
old_sigma
,
new_sigma
)
in
zip
(
sigma_restart
[:
-
1
],
sigma_restart
[
1
:]):
x
=
heun_step
(
x
,
old_sigma
,
new_sigma
)
...
...
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