"server/vscode:/vscode.git/clone" did not exist on "bf99afe9160f97124ba2ec28afaa97e4364846a8"
__init__.py 4.3 KB
Newer Older
1
2
3
from typing import TYPE_CHECKING

from ..utils import DIFFUSERS_SLOW_IMPORT, _LazyModule, deprecate
4
from ..utils.import_utils import is_peft_available, is_torch_available, is_transformers_available
5
6
7
8
9
10


def text_encoder_lora_state_dict(text_encoder):
    deprecate(
        "text_encoder_load_state_dict in `models`",
        "0.27.0",
11
        "`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.",
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
    )
    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",
37
            "`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.",
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
        )
        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():
57
    _import_structure["single_file_model"] = ["FromOriginalModelMixin"]
58

59
60
61
    _import_structure["unet"] = ["UNet2DConditionLoadersMixin"]
    _import_structure["utils"] = ["AttnProcsLayers"]
    if is_transformers_available():
62
        _import_structure["single_file"] = ["FromSingleFileMixin"]
63
64
65
66
67
        _import_structure["lora_pipeline"] = [
            "AmusedLoraLoaderMixin",
            "StableDiffusionLoraLoaderMixin",
            "SD3LoraLoaderMixin",
            "StableDiffusionXLLoraLoaderMixin",
Aryan's avatar
Aryan committed
68
            "LTXVideoLoraLoaderMixin",
69
            "LoraLoaderMixin",
Sayak Paul's avatar
Sayak Paul committed
70
            "FluxLoraLoaderMixin",
Aryan's avatar
Aryan committed
71
            "CogVideoXLoraLoaderMixin",
72
            "Mochi1LoraLoaderMixin",
73
            "HunyuanVideoLoraLoaderMixin",
74
            "SanaLoraLoaderMixin",
75
        ]
76
        _import_structure["textual_inversion"] = ["TextualInversionLoaderMixin"]
77
        _import_structure["ip_adapter"] = ["IPAdapterMixin"]
78

79
80
_import_structure["peft"] = ["PeftAdapterMixin"]

81
82
83

if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
    if is_torch_available():
84
        from .single_file_model import FromOriginalModelMixin
85
86
87
88
        from .unet import UNet2DConditionLoadersMixin
        from .utils import AttnProcsLayers

        if is_transformers_available():
89
            from .ip_adapter import IPAdapterMixin
90
91
            from .lora_pipeline import (
                AmusedLoraLoaderMixin,
Aryan's avatar
Aryan committed
92
                CogVideoXLoraLoaderMixin,
Sayak Paul's avatar
Sayak Paul committed
93
                FluxLoraLoaderMixin,
94
                HunyuanVideoLoraLoaderMixin,
95
                LoraLoaderMixin,
Aryan's avatar
Aryan committed
96
                LTXVideoLoraLoaderMixin,
97
                Mochi1LoraLoaderMixin,
98
                SanaLoraLoaderMixin,
99
100
101
102
                SD3LoraLoaderMixin,
                StableDiffusionLoraLoaderMixin,
                StableDiffusionXLLoraLoaderMixin,
            )
103
104
            from .single_file import FromSingleFileMixin
            from .textual_inversion import TextualInversionLoaderMixin
105
106

    from .peft import PeftAdapterMixin
107
108
109
110
else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)