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renzhc
diffusers_dcu
Commits
5b1af9ab
"src/vscode:/vscode.git/clone" did not exist on "33d7e89c42e0fe7b4a277d7a5bae12ba14828dd8"
Commit
5b1af9ab
authored
Jun 07, 2022
by
Patrick von Platen
Browse files
correct naming in glide
parent
0a1d4c58
Changes
2
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5 additions
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5 deletions
+5
-5
src/diffusers/models/unet.py
src/diffusers/models/unet.py
+2
-2
src/diffusers/models/unet_glide.py
src/diffusers/models/unet_glide.py
+3
-3
No files found.
src/diffusers/models/unet.py
View file @
5b1af9ab
...
@@ -29,7 +29,7 @@ from torchvision import transforms, utils
...
@@ -29,7 +29,7 @@ from torchvision import transforms, utils
from
PIL
import
Image
from
PIL
import
Image
from
tqdm
import
tqdm
from
tqdm
import
tqdm
from
..configuration_utils
import
ConfigMixin
from
..configuration_utils
import
ConfigMixin
Mixin
from
..modeling_utils
import
ModelMixin
from
..modeling_utils
import
ModelMixin
...
@@ -175,7 +175,7 @@ class AttnBlock(nn.Module):
...
@@ -175,7 +175,7 @@ class AttnBlock(nn.Module):
return
x
+
h_
return
x
+
h_
class
UNetModel
(
ModelMixin
,
ConfigMixin
):
class
UNetModel
(
ModelMixin
,
ConfigMixin
Mixin
):
def
__init__
(
def
__init__
(
self
,
self
,
ch
=
128
,
ch
=
128
,
...
...
src/diffusers/models/unet_glide.py
View file @
5b1af9ab
...
@@ -5,8 +5,8 @@ import torch
...
@@ -5,8 +5,8 @@ import torch
import
torch.nn
as
nn
import
torch.nn
as
nn
import
torch.nn.functional
as
F
import
torch.nn.functional
as
F
from
..configuration_utils
import
Config
from
..configuration_utils
import
Config
Mixin
from
..modeling_utils
import
PreTrained
Model
from
..modeling_utils
import
Model
Mixin
def
convert_module_to_f16
(
l
):
def
convert_module_to_f16
(
l
):
...
@@ -388,7 +388,7 @@ class QKVAttention(nn.Module):
...
@@ -388,7 +388,7 @@ class QKVAttention(nn.Module):
return
a
.
reshape
(
bs
,
-
1
,
length
)
return
a
.
reshape
(
bs
,
-
1
,
length
)
class
UNetGLIDEModel
(
PreTrained
Model
,
Config
):
class
UNetGLIDEModel
(
Model
Mixin
,
Config
Mixin
):
"""
"""
The full UNet model with attention and timestep embedding.
The full UNet model with attention and timestep embedding.
...
...
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