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Administrator
stable-diffusion-webui
Commits
21ee77db
Unverified
Commit
21ee77db
authored
Jan 04, 2023
by
Vladimir Mandic
Committed by
GitHub
Jan 04, 2023
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add cross-attention info
parent
c923de0e
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1 changed file
with
11 additions
and
1 deletion
+11
-1
sd_hijack.py
modules/sd_hijack.py
+11
-1
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modules/sd_hijack.py
View file @
21ee77db
...
@@ -35,26 +35,35 @@ def apply_optimizations():
...
@@ -35,26 +35,35 @@ def apply_optimizations():
ldm
.
modules
.
diffusionmodules
.
model
.
nonlinearity
=
silu
ldm
.
modules
.
diffusionmodules
.
model
.
nonlinearity
=
silu
ldm
.
modules
.
diffusionmodules
.
openaimodel
.
th
=
sd_hijack_unet
.
th
ldm
.
modules
.
diffusionmodules
.
openaimodel
.
th
=
sd_hijack_unet
.
th
optimization_method
=
None
if
cmd_opts
.
force_enable_xformers
or
(
cmd_opts
.
xformers
and
shared
.
xformers_available
and
torch
.
version
.
cuda
and
(
6
,
0
)
<=
torch
.
cuda
.
get_device_capability
(
shared
.
device
)
<=
(
9
,
0
)):
if
cmd_opts
.
force_enable_xformers
or
(
cmd_opts
.
xformers
and
shared
.
xformers_available
and
torch
.
version
.
cuda
and
(
6
,
0
)
<=
torch
.
cuda
.
get_device_capability
(
shared
.
device
)
<=
(
9
,
0
)):
print
(
"Applying xformers cross attention optimization."
)
print
(
"Applying xformers cross attention optimization."
)
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
xformers_attention_forward
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
xformers_attention_forward
ldm
.
modules
.
diffusionmodules
.
model
.
AttnBlock
.
forward
=
sd_hijack_optimizations
.
xformers_attnblock_forward
ldm
.
modules
.
diffusionmodules
.
model
.
AttnBlock
.
forward
=
sd_hijack_optimizations
.
xformers_attnblock_forward
optimization_method
=
'xformers'
elif
cmd_opts
.
opt_split_attention_v1
:
elif
cmd_opts
.
opt_split_attention_v1
:
print
(
"Applying v1 cross attention optimization."
)
print
(
"Applying v1 cross attention optimization."
)
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward_v1
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward_v1
optimization_method
=
'V1'
elif
not
cmd_opts
.
disable_opt_split_attention
and
(
cmd_opts
.
opt_split_attention_invokeai
or
not
torch
.
cuda
.
is_available
()):
elif
not
cmd_opts
.
disable_opt_split_attention
and
(
cmd_opts
.
opt_split_attention_invokeai
or
not
torch
.
cuda
.
is_available
()):
if
not
invokeAI_mps_available
and
shared
.
device
.
type
==
'mps'
:
if
not
invokeAI_mps_available
and
shared
.
device
.
type
==
'mps'
:
print
(
"The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed."
)
print
(
"The InvokeAI cross attention optimization for MPS requires the psutil package which is not installed."
)
print
(
"Applying v1 cross attention optimization."
)
print
(
"Applying v1 cross attention optimization."
)
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward_v1
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward_v1
optimization_method
=
'V1'
else
:
else
:
print
(
"Applying cross attention optimization (InvokeAI)."
)
print
(
"Applying cross attention optimization (InvokeAI)."
)
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward_invokeAI
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward_invokeAI
optimization_method
=
'InvokeAI'
elif
not
cmd_opts
.
disable_opt_split_attention
and
(
cmd_opts
.
opt_split_attention
or
torch
.
cuda
.
is_available
()):
elif
not
cmd_opts
.
disable_opt_split_attention
and
(
cmd_opts
.
opt_split_attention
or
torch
.
cuda
.
is_available
()):
print
(
"Applying cross attention optimization (Doggettx)."
)
print
(
"Applying cross attention optimization (Doggettx)."
)
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward
ldm
.
modules
.
attention
.
CrossAttention
.
forward
=
sd_hijack_optimizations
.
split_cross_attention_forward
ldm
.
modules
.
diffusionmodules
.
model
.
AttnBlock
.
forward
=
sd_hijack_optimizations
.
cross_attention_attnblock_forward
ldm
.
modules
.
diffusionmodules
.
model
.
AttnBlock
.
forward
=
sd_hijack_optimizations
.
cross_attention_attnblock_forward
optimization_method
=
'Doggettx'
return
optimization_method
def
undo_optimizations
():
def
undo_optimizations
():
...
@@ -75,6 +84,7 @@ class StableDiffusionModelHijack:
...
@@ -75,6 +84,7 @@ class StableDiffusionModelHijack:
layers
=
None
layers
=
None
circular_enabled
=
False
circular_enabled
=
False
clip
=
None
clip
=
None
optimization_method
=
None
embedding_db
=
modules
.
textual_inversion
.
textual_inversion
.
EmbeddingDatabase
(
cmd_opts
.
embeddings_dir
)
embedding_db
=
modules
.
textual_inversion
.
textual_inversion
.
EmbeddingDatabase
(
cmd_opts
.
embeddings_dir
)
...
@@ -94,7 +104,7 @@ class StableDiffusionModelHijack:
...
@@ -94,7 +104,7 @@ class StableDiffusionModelHijack:
m
.
cond_stage_model
.
model
.
token_embedding
=
EmbeddingsWithFixes
(
m
.
cond_stage_model
.
model
.
token_embedding
,
self
)
m
.
cond_stage_model
.
model
.
token_embedding
=
EmbeddingsWithFixes
(
m
.
cond_stage_model
.
model
.
token_embedding
,
self
)
m
.
cond_stage_model
=
sd_hijack_open_clip
.
FrozenOpenCLIPEmbedderWithCustomWords
(
m
.
cond_stage_model
,
self
)
m
.
cond_stage_model
=
sd_hijack_open_clip
.
FrozenOpenCLIPEmbedderWithCustomWords
(
m
.
cond_stage_model
,
self
)
apply_optimizations
()
self
.
optimization_method
=
apply_optimizations
()
self
.
clip
=
m
.
cond_stage_model
self
.
clip
=
m
.
cond_stage_model
...
...
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