forked from huggingface/diffusers
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy path__init__.py
More file actions
147 lines (124 loc) 路 5.76 KB
/
Copy path__init__.py
File metadata and controls
147 lines (124 loc) 路 5.76 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
from typing import TYPE_CHECKING
from ..utils import DIFFUSERS_SLOW_IMPORT, _LazyModule, deprecate
from ..utils.import_utils import is_peft_available, is_torch_available, is_transformers_available
def text_encoder_lora_state_dict(text_encoder):
deprecate(
"text_encoder_load_state_dict in `models`",
"0.27.0",
"`text_encoder_lora_state_dict` is deprecated and will be removed in 0.27.0. Make sure to retrieve the weights using `get_peft_model`. See https://huggingface.co/docs/peft/v0.6.2/en/quicktour#peftmodel for more information.",
)
state_dict = {}
for name, module in text_encoder_attn_modules(text_encoder):
for k, v in module.q_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.q_proj.lora_linear_layer.{k}"] = v
for k, v in module.k_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.k_proj.lora_linear_layer.{k}"] = v
for k, v in module.v_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.v_proj.lora_linear_layer.{k}"] = v
for k, v in module.out_proj.lora_linear_layer.state_dict().items():
state_dict[f"{name}.out_proj.lora_linear_layer.{k}"] = v
return state_dict
if is_transformers_available():
def text_encoder_attn_modules(text_encoder):
deprecate(
"text_encoder_attn_modules in `models`",
"0.27.0",
"`text_encoder_lora_state_dict` is deprecated and will be removed in 0.27.0. Make sure to retrieve the weights using `get_peft_model`. See https://huggingface.co/docs/peft/v0.6.2/en/quicktour#peftmodel for more information.",
)
from transformers import CLIPTextModel, CLIPTextModelWithProjection
attn_modules = []
if isinstance(text_encoder, (CLIPTextModel, CLIPTextModelWithProjection)):
for i, layer in enumerate(text_encoder.text_model.encoder.layers):
name = f"text_model.encoder.layers.{i}.self_attn"
mod = layer.self_attn
attn_modules.append((name, mod))
else:
raise ValueError(f"do not know how to get attention modules for: {text_encoder.__class__.__name__}")
return attn_modules
_import_structure = {}
if is_torch_available():
_import_structure["single_file_model"] = ["FromOriginalModelMixin"]
_import_structure["transformer_flux"] = ["FluxTransformer2DLoadersMixin"]
_import_structure["transformer_sd3"] = ["SD3Transformer2DLoadersMixin"]
_import_structure["unet"] = ["UNet2DConditionLoadersMixin"]
_import_structure["utils"] = ["AttnProcsLayers"]
if is_transformers_available():
_import_structure["single_file"] = ["FromSingleFileMixin"]
_import_structure["lora_pipeline"] = [
"AmusedLoraLoaderMixin",
"StableDiffusionLoraLoaderMixin",
"SD3LoraLoaderMixin",
"AuraFlowLoraLoaderMixin",
"StableDiffusionXLLoraLoaderMixin",
"LTX2LoraLoaderMixin",
"LTXVideoLoraLoaderMixin",
"LoraLoaderMixin",
"FluxLoraLoaderMixin",
"CogVideoXLoraLoaderMixin",
"CogView4LoraLoaderMixin",
"Mochi1LoraLoaderMixin",
"HunyuanVideoLoraLoaderMixin",
"SanaLoraLoaderMixin",
"Lumina2LoraLoaderMixin",
"WanLoraLoaderMixin",
"HeliosLoraLoaderMixin",
"KandinskyLoraLoaderMixin",
"HiDreamImageLoraLoaderMixin",
"SkyReelsV2LoraLoaderMixin",
"QwenImageLoraLoaderMixin",
"ZImageLoraLoaderMixin",
"Flux2LoraLoaderMixin",
]
_import_structure["textual_inversion"] = ["TextualInversionLoaderMixin"]
_import_structure["ip_adapter"] = [
"IPAdapterMixin",
"FluxIPAdapterMixin",
"SD3IPAdapterMixin",
"ModularIPAdapterMixin",
]
_import_structure["peft"] = ["PeftAdapterMixin"]
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
if is_torch_available():
from .single_file_model import FromOriginalModelMixin
from .transformer_flux import FluxTransformer2DLoadersMixin
from .transformer_sd3 import SD3Transformer2DLoadersMixin
from .unet import UNet2DConditionLoadersMixin
from .utils import AttnProcsLayers
if is_transformers_available():
from .ip_adapter import (
FluxIPAdapterMixin,
IPAdapterMixin,
ModularIPAdapterMixin,
SD3IPAdapterMixin,
)
from .lora_pipeline import (
AmusedLoraLoaderMixin,
AuraFlowLoraLoaderMixin,
CogVideoXLoraLoaderMixin,
CogView4LoraLoaderMixin,
Flux2LoraLoaderMixin,
FluxLoraLoaderMixin,
HeliosLoraLoaderMixin,
HiDreamImageLoraLoaderMixin,
HunyuanVideoLoraLoaderMixin,
KandinskyLoraLoaderMixin,
LoraLoaderMixin,
LTX2LoraLoaderMixin,
LTXVideoLoraLoaderMixin,
Lumina2LoraLoaderMixin,
Mochi1LoraLoaderMixin,
QwenImageLoraLoaderMixin,
SanaLoraLoaderMixin,
SD3LoraLoaderMixin,
SkyReelsV2LoraLoaderMixin,
StableDiffusionLoraLoaderMixin,
StableDiffusionXLLoraLoaderMixin,
WanLoraLoaderMixin,
ZImageLoraLoaderMixin,
)
from .single_file import FromSingleFileMixin
from .textual_inversion import TextualInversionLoaderMixin
from .peft import PeftAdapterMixin
else:
import sys
sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)