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Overbill1683
Stable Diffusion Webui
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c833d5bf
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Stable Diffusion Webui
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Stable Diffusion Webui
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c833d5bf
编写于
11月 25, 2022
作者:
J
Jay Smith
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电子邮件补丁
差异文件
fixes #3449 - VRAM leak when switching to/from inpainting model
上级
828438b4
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
15 addition
and
18 deletion
+15
-18
modules/sd_samplers.py
modules/sd_samplers.py
+15
-18
未找到文件。
modules/sd_samplers.py
浏览文件 @
c833d5bf
from
collections
import
namedtuple
from
collections
import
namedtuple
,
deque
import
numpy
as
np
import
numpy
as
np
from
math
import
floor
from
math
import
floor
import
torch
import
torch
...
@@ -335,18 +335,28 @@ class CFGDenoiser(torch.nn.Module):
...
@@ -335,18 +335,28 @@ class CFGDenoiser(torch.nn.Module):
class
TorchHijack
:
class
TorchHijack
:
def
__init__
(
self
,
kdiff_sampler
):
def
__init__
(
self
,
sampler_noises
):
self
.
kdiff_sampler
=
kdiff_sampler
# Using a deque to efficiently receive the sampler_noises in the same order as the previous index-based
# implementation.
self
.
sampler_noises
=
deque
(
sampler_noises
)
def
__getattr__
(
self
,
item
):
def
__getattr__
(
self
,
item
):
if
item
==
'randn_like'
:
if
item
==
'randn_like'
:
return
self
.
kdiff_sampler
.
randn_like
return
self
.
randn_like
if
hasattr
(
torch
,
item
):
if
hasattr
(
torch
,
item
):
return
getattr
(
torch
,
item
)
return
getattr
(
torch
,
item
)
raise
AttributeError
(
"'{}' object has no attribute '{}'"
.
format
(
type
(
self
).
__name__
,
item
))
raise
AttributeError
(
"'{}' object has no attribute '{}'"
.
format
(
type
(
self
).
__name__
,
item
))
def
randn_like
(
self
,
x
):
if
self
.
sampler_noises
:
noise
=
self
.
sampler_noises
.
popleft
()
if
noise
.
shape
==
x
.
shape
:
return
noise
return
torch
.
randn_like
(
x
)
class
KDiffusionSampler
:
class
KDiffusionSampler
:
def
__init__
(
self
,
funcname
,
sd_model
):
def
__init__
(
self
,
funcname
,
sd_model
):
...
@@ -356,7 +366,6 @@ class KDiffusionSampler:
...
@@ -356,7 +366,6 @@ class KDiffusionSampler:
self
.
extra_params
=
sampler_extra_params
.
get
(
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
.
stop_at
=
None
self
.
stop_at
=
None
self
.
eta
=
None
self
.
eta
=
None
self
.
default_eta
=
1.0
self
.
default_eta
=
1.0
...
@@ -389,26 +398,14 @@ class KDiffusionSampler:
...
@@ -389,26 +398,14 @@ class KDiffusionSampler:
def
number_of_needed_noises
(
self
,
p
):
def
number_of_needed_noises
(
self
,
p
):
return
p
.
steps
return
p
.
steps
def
randn_like
(
self
,
x
):
noise
=
self
.
sampler_noises
[
self
.
sampler_noise_index
]
if
self
.
sampler_noises
is
not
None
and
self
.
sampler_noise_index
<
len
(
self
.
sampler_noises
)
else
None
if
noise
is
not
None
and
x
.
shape
==
noise
.
shape
:
res
=
noise
else
:
res
=
torch
.
randn_like
(
x
)
self
.
sampler_noise_index
+=
1
return
res
def
initialize
(
self
,
p
):
def
initialize
(
self
,
p
):
self
.
model_wrap_cfg
.
mask
=
p
.
mask
if
hasattr
(
p
,
'mask'
)
else
None
self
.
model_wrap_cfg
.
mask
=
p
.
mask
if
hasattr
(
p
,
'mask'
)
else
None
self
.
model_wrap_cfg
.
nmask
=
p
.
nmask
if
hasattr
(
p
,
'nmask'
)
else
None
self
.
model_wrap_cfg
.
nmask
=
p
.
nmask
if
hasattr
(
p
,
'nmask'
)
else
None
self
.
model_wrap
.
step
=
0
self
.
model_wrap
.
step
=
0
self
.
sampler_noise_index
=
0
self
.
eta
=
p
.
eta
or
opts
.
eta_ancestral
self
.
eta
=
p
.
eta
or
opts
.
eta_ancestral
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
.
sampler_noises
)
extra_params_kwargs
=
{}
extra_params_kwargs
=
{}
for
param_name
in
self
.
extra_params
:
for
param_name
in
self
.
extra_params
:
...
...
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