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Administrator
stable-diffusion-webui
Commits
8f591298
Commit
8f591298
authored
Oct 20, 2022
by
Melan
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Plain Diff
Some changes to the tensorboard code and hypernetwork support
parent
a6d593a6
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2 changed files
with
44 additions
and
19 deletions
+44
-19
hypernetwork.py
modules/hypernetworks/hypernetwork.py
+17
-1
textual_inversion.py
modules/textual_inversion/textual_inversion.py
+27
-18
No files found.
modules/hypernetworks/hypernetwork.py
View file @
8f591298
...
@@ -4,6 +4,7 @@ import html
...
@@ -4,6 +4,7 @@ import html
import
os
import
os
import
sys
import
sys
import
traceback
import
traceback
import
tensorboard
import
tqdm
import
tqdm
import
csv
import
csv
...
@@ -18,7 +19,6 @@ import modules.textual_inversion.dataset
...
@@ -18,7 +19,6 @@ import modules.textual_inversion.dataset
from
modules.textual_inversion
import
textual_inversion
from
modules.textual_inversion
import
textual_inversion
from
modules.textual_inversion.learn_schedule
import
LearnRateScheduler
from
modules.textual_inversion.learn_schedule
import
LearnRateScheduler
class
HypernetworkModule
(
torch
.
nn
.
Module
):
class
HypernetworkModule
(
torch
.
nn
.
Module
):
multiplier
=
1.0
multiplier
=
1.0
...
@@ -291,6 +291,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
...
@@ -291,6 +291,9 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
scheduler
=
LearnRateScheduler
(
learn_rate
,
steps
,
ititial_step
)
scheduler
=
LearnRateScheduler
(
learn_rate
,
steps
,
ititial_step
)
optimizer
=
torch
.
optim
.
AdamW
(
weights
,
lr
=
scheduler
.
learn_rate
)
optimizer
=
torch
.
optim
.
AdamW
(
weights
,
lr
=
scheduler
.
learn_rate
)
if
shared
.
opts
.
training_enable_tensorboard
:
tensorboard_writer
=
textual_inversion
.
tensorboard_setup
(
log_directory
)
pbar
=
tqdm
.
tqdm
(
enumerate
(
ds
),
total
=
steps
-
ititial_step
)
pbar
=
tqdm
.
tqdm
(
enumerate
(
ds
),
total
=
steps
-
ititial_step
)
for
i
,
entries
in
pbar
:
for
i
,
entries
in
pbar
:
hypernetwork
.
step
=
i
+
ititial_step
hypernetwork
.
step
=
i
+
ititial_step
...
@@ -315,6 +318,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
...
@@ -315,6 +318,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
optimizer
.
zero_grad
()
optimizer
.
zero_grad
()
loss
.
backward
()
loss
.
backward
()
optimizer
.
step
()
optimizer
.
step
()
mean_loss
=
losses
.
mean
()
mean_loss
=
losses
.
mean
()
if
torch
.
isnan
(
mean_loss
):
if
torch
.
isnan
(
mean_loss
):
raise
RuntimeError
(
"Loss diverged."
)
raise
RuntimeError
(
"Loss diverged."
)
...
@@ -323,6 +327,14 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
...
@@ -323,6 +327,14 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
if
hypernetwork
.
step
>
0
and
hypernetwork_dir
is
not
None
and
hypernetwork
.
step
%
save_hypernetwork_every
==
0
:
if
hypernetwork
.
step
>
0
and
hypernetwork_dir
is
not
None
and
hypernetwork
.
step
%
save_hypernetwork_every
==
0
:
last_saved_file
=
os
.
path
.
join
(
hypernetwork_dir
,
f
'{hypernetwork_name}-{hypernetwork.step}.pt'
)
last_saved_file
=
os
.
path
.
join
(
hypernetwork_dir
,
f
'{hypernetwork_name}-{hypernetwork.step}.pt'
)
hypernetwork
.
save
(
last_saved_file
)
hypernetwork
.
save
(
last_saved_file
)
if
shared
.
opts
.
training_enable_tensorboard
:
epoch_num
=
hypernetwork
.
step
//
len
(
ds
)
epoch_step
=
hypernetwork
.
step
-
(
epoch_num
*
len
(
ds
))
+
1
textual_inversion
.
tensorboard_add
(
tensorboard_writer
,
loss
=
mean_loss
,
global_step
=
hypernetwork
.
step
,
step
=
epoch_step
,
learn_rate
=
scheduler
.
learn_rate
,
epoch_num
=
epoch_num
)
textual_inversion
.
write_loss
(
log_directory
,
"hypernetwork_loss.csv"
,
hypernetwork
.
step
,
len
(
ds
),
{
textual_inversion
.
write_loss
(
log_directory
,
"hypernetwork_loss.csv"
,
hypernetwork
.
step
,
len
(
ds
),
{
"loss"
:
f
"{mean_loss:.7f}"
,
"loss"
:
f
"{mean_loss:.7f}"
,
...
@@ -360,6 +372,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
...
@@ -360,6 +372,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
processed
=
processing
.
process_images
(
p
)
processed
=
processing
.
process_images
(
p
)
image
=
processed
.
images
[
0
]
if
len
(
processed
.
images
)
>
0
else
None
image
=
processed
.
images
[
0
]
if
len
(
processed
.
images
)
>
0
else
None
if
shared
.
opts
.
training_enable_tensorboard
and
shared
.
opts
.
training_tensorboard_save_images
:
textual_inversion
.
tensorboard_add_image
(
tensorboard_writer
,
f
"Validation at epoch {epoch_num}"
,
image
,
hypernetwork
.
step
)
if
unload
:
if
unload
:
shared
.
sd_model
.
cond_stage_model
.
to
(
devices
.
cpu
)
shared
.
sd_model
.
cond_stage_model
.
to
(
devices
.
cpu
)
shared
.
sd_model
.
first_stage_model
.
to
(
devices
.
cpu
)
shared
.
sd_model
.
first_stage_model
.
to
(
devices
.
cpu
)
...
...
modules/textual_inversion/textual_inversion.py
View file @
8f591298
...
@@ -201,19 +201,30 @@ def write_loss(log_directory, filename, step, epoch_len, values):
...
@@ -201,19 +201,30 @@ def write_loss(log_directory, filename, step, epoch_len, values):
**
values
,
**
values
,
})
})
def
tensorboard_setup
(
log_directory
):
os
.
makedirs
(
os
.
path
.
join
(
log_directory
,
"tensorboard"
),
exist_ok
=
True
)
return
SummaryWriter
(
log_dir
=
os
.
path
.
join
(
log_directory
,
"tensorboard"
),
flush_secs
=
shared
.
opts
.
training_tensorboard_flush_every
)
def
tensorboard_add
(
tensorboard_writer
,
loss
,
global_step
,
step
,
learn_rate
,
epoch_num
):
tensorboard_add_scaler
(
tensorboard_writer
,
"Loss/train"
,
loss
,
global_step
)
tensorboard_add_scaler
(
tensorboard_writer
,
f
"Loss/train/epoch-{epoch_num}"
,
loss
,
step
)
tensorboard_add_scaler
(
tensorboard_writer
,
"Learn rate/train"
,
learn_rate
,
global_step
)
tensorboard_add_scaler
(
tensorboard_writer
,
f
"Learn rate/train/epoch-{epoch_num}"
,
learn_rate
,
step
)
def
tensorboard_add_scaler
(
tensorboard_writer
,
tag
,
value
,
step
):
def
tensorboard_add_scaler
(
tensorboard_writer
,
tag
,
value
,
step
):
if
shared
.
opts
.
training_enable_tensorboard
:
tensorboard_writer
.
add_scalar
(
tag
=
tag
,
tensorboard_writer
.
add_scalar
(
tag
=
tag
,
scalar_value
=
value
,
global_step
=
step
)
scalar_value
=
value
,
global_step
=
step
)
def
tensorboard_add_image
(
tensorboard_writer
,
tag
,
pil_image
,
step
):
def
tensorboard_add_image
(
tensorboard_writer
,
tag
,
pil_image
,
step
):
if
shared
.
opts
.
training_enable_tensorboard
:
# Convert a pil image to a torch tensor
# Convert a pil image to a torch tensor
img_tensor
=
torch
.
as_tensor
(
np
.
array
(
pil_image
,
copy
=
True
))
img_tensor
=
torch
.
as_tensor
(
np
.
array
(
pil_image
,
copy
=
True
))
img_tensor
=
img_tensor
.
view
(
pil_image
.
size
[
1
],
pil_image
.
size
[
0
],
img_tensor
=
img_tensor
.
view
(
pil_image
.
size
[
1
],
pil_image
.
size
[
0
],
len
(
pil_image
.
getbands
()))
len
(
pil_image
.
getbands
()))
img_tensor
=
img_tensor
.
permute
((
2
,
0
,
1
))
img_tensor
=
img_tensor
.
permute
((
2
,
0
,
1
))
tensorboard_writer
.
add_image
(
tag
,
img_tensor
,
global_step
=
step
)
tensorboard_writer
.
add_image
(
tag
,
img_tensor
,
global_step
=
step
)
def
train_embedding
(
embedding_name
,
learn_rate
,
batch_size
,
data_root
,
log_directory
,
training_width
,
training_height
,
steps
,
create_image_every
,
save_embedding_every
,
template_file
,
save_image_with_stored_embedding
,
preview_from_txt2img
,
preview_prompt
,
preview_negative_prompt
,
preview_steps
,
preview_sampler_index
,
preview_cfg_scale
,
preview_seed
,
preview_width
,
preview_height
):
def
train_embedding
(
embedding_name
,
learn_rate
,
batch_size
,
data_root
,
log_directory
,
training_width
,
training_height
,
steps
,
create_image_every
,
save_embedding_every
,
template_file
,
save_image_with_stored_embedding
,
preview_from_txt2img
,
preview_prompt
,
preview_negative_prompt
,
preview_steps
,
preview_sampler_index
,
preview_cfg_scale
,
preview_seed
,
preview_width
,
preview_height
):
assert
embedding_name
,
'embedding not selected'
assert
embedding_name
,
'embedding not selected'
...
@@ -268,10 +279,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
...
@@ -268,10 +279,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
optimizer
=
torch
.
optim
.
AdamW
([
embedding
.
vec
],
lr
=
scheduler
.
learn_rate
)
optimizer
=
torch
.
optim
.
AdamW
([
embedding
.
vec
],
lr
=
scheduler
.
learn_rate
)
if
shared
.
opts
.
training_enable_tensorboard
:
if
shared
.
opts
.
training_enable_tensorboard
:
os
.
makedirs
(
os
.
path
.
join
(
log_directory
,
"tensorboard"
),
exist_ok
=
True
)
tensorboard_writer
=
tensorboard_setup
(
log_directory
)
tensorboard_writer
=
SummaryWriter
(
log_dir
=
os
.
path
.
join
(
log_directory
,
"tensorboard"
),
flush_secs
=
shared
.
opts
.
training_tensorboard_flush_every
)
pbar
=
tqdm
.
tqdm
(
enumerate
(
ds
),
total
=
steps
-
initial_step
)
pbar
=
tqdm
.
tqdm
(
enumerate
(
ds
),
total
=
steps
-
initial_step
)
for
i
,
entries
in
pbar
:
for
i
,
entries
in
pbar
:
...
@@ -308,10 +316,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
...
@@ -308,10 +316,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
embedding_yet_to_be_embedded
=
True
embedding_yet_to_be_embedded
=
True
if
shared
.
opts
.
training_enable_tensorboard
:
if
shared
.
opts
.
training_enable_tensorboard
:
tensorboard_add_scaler
(
tensorboard_writer
,
"Loss/train"
,
losses
.
mean
(),
embedding
.
step
)
tensorboard_add
(
tensorboard_writer
,
loss
=
losses
.
mean
(),
global_step
=
embedding
.
step
,
tensorboard_add_scaler
(
tensorboard_writer
,
f
"Loss/train/epoch-{epoch_num}"
,
losses
.
mean
(),
epoch_step
)
step
=
epoch_step
,
learn_rate
=
scheduler
.
learn_rate
,
epoch_num
=
epoch_num
)
tensorboard_add_scaler
(
tensorboard_writer
,
"Learn rate/train"
,
scheduler
.
learn_rate
,
embedding
.
step
)
tensorboard_add_scaler
(
tensorboard_writer
,
f
"Learn rate/train/epoch-{epoch_num}"
,
scheduler
.
learn_rate
,
epoch_step
)
write_loss
(
log_directory
,
"textual_inversion_loss.csv"
,
embedding
.
step
,
len
(
ds
),
{
write_loss
(
log_directory
,
"textual_inversion_loss.csv"
,
embedding
.
step
,
len
(
ds
),
{
"loss"
:
f
"{losses.mean():.7f}"
,
"loss"
:
f
"{losses.mean():.7f}"
,
...
@@ -377,7 +383,10 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
...
@@ -377,7 +383,10 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
embedding_yet_to_be_embedded
=
False
embedding_yet_to_be_embedded
=
False
image
.
save
(
last_saved_image
)
image
.
save
(
last_saved_image
)
tensorboard_add_image
(
tensorboard_writer
,
f
"Validation at epoch {epoch_num}"
,
image
,
embedding
.
step
)
if
shared
.
opts
.
training_enable_tensorboard
and
shared
.
opts
.
training_tensorboard_save_images
:
tensorboard_add_image
(
tensorboard_writer
,
f
"Validation at epoch {epoch_num}"
,
image
,
embedding
.
step
)
last_saved_image
+=
f
", prompt: {preview_text}"
last_saved_image
+=
f
", prompt: {preview_text}"
...
...
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