File size: 6,014 Bytes
6728bc2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
148
149
150
151
import argparse
import enum


class EnumAction(argparse.Action):
    """Argparse `action` for handling Enum"""

    def __init__(self, **kwargs):
        enum_type = kwargs.pop("type", None)
        assert issubclass(enum_type, enum.Enum)

        choices = tuple(e.value for e in enum_type)
        kwargs.setdefault("choices", choices)
        kwargs.setdefault("metavar", f"[{','.join(list(choices))}]")

        super(EnumAction, self).__init__(**kwargs)
        self._enum = enum_type

    def __call__(self, parser, namespace, values, option_string=None):
        value = self._enum(values)
        setattr(namespace, self.dest, value)


parser = argparse.ArgumentParser()

parser.add_argument("--gpu-device-id", type=int, default=None, metavar="DEVICE_ID")

fp_group = parser.add_mutually_exclusive_group()
fp_group.add_argument("--all-in-fp32", action="store_true")
fp_group.add_argument("--all-in-fp16", action="store_true")

fpunet_group = parser.add_mutually_exclusive_group()
fpunet_group.add_argument("--unet-in-bf16", action="store_true")
fpunet_group.add_argument("--unet-in-fp16", action="store_true")
fpunet_group.add_argument("--unet-in-fp8-e4m3fn", action="store_true")
fpunet_group.add_argument("--unet-in-fp8-e5m2", action="store_true")

fpvae_group = parser.add_mutually_exclusive_group()
fpvae_group.add_argument("--vae-in-fp16", action="store_true")
fpvae_group.add_argument("--vae-in-fp32", action="store_true")
fpvae_group.add_argument("--vae-in-bf16", action="store_true")

parser.add_argument("--vae-in-cpu", action="store_true")

fpte_group = parser.add_mutually_exclusive_group()
fpte_group.add_argument("--clip-in-fp8-e4m3fn", action="store_true")
fpte_group.add_argument("--clip-in-fp8-e5m2", action="store_true")
fpte_group.add_argument("--clip-in-fp16", action="store_true")
fpte_group.add_argument("--clip-in-fp32", action="store_true")

parser.add_argument("--clip-in-cpu", action="store_true")

attn_group = parser.add_mutually_exclusive_group()
attn_group.add_argument("--attention-split", action="store_true")
attn_group.add_argument("--attention-pytorch", action="store_true")

upcast = parser.add_mutually_exclusive_group()
upcast.add_argument("--force-upcast-attention", action="store_true")
upcast.add_argument("--disable-attention-upcast", action="store_true")

parser.add_argument("--xformers", action="store_true", help="install xformers for cross attention")
parser.add_argument("--sage", action="store_true", help="install sageattention")
parser.add_argument("--flash", action="store_true", help="install flash_attn")
parser.add_argument("--nunchaku", action="store_true", help="install nunchaku for SVDQ inference")
parser.add_argument("--bnb", action="store_true", help="install bitsandbytes for 4-bit inference")
parser.add_argument("--onnxruntime-gpu", action="store_true", help="install nightly onnxruntime-gpu with cu130 support")

parser.add_argument("--disable-xformers", action="store_true")
parser.add_argument("--disable-sage", action="store_true")
parser.add_argument("--disable-flash", action="store_true")

parser.add_argument("--force-xformers-vae", action="store_true")

parser.add_argument("--directml", type=int, nargs="?", metavar="DIRECTML_DEVICE", const=-1)
parser.add_argument("--disable-ipex-hijack", action="store_true")

vram_group = parser.add_mutually_exclusive_group()
vram_group.add_argument("--always-gpu", action="store_true")
vram_group.add_argument("--always-high-vram", action="store_true")
vram_group.add_argument("--always-normal-vram", action="store_true")
vram_group.add_argument("--always-low-vram", action="store_true")
vram_group.add_argument("--always-no-vram", action="store_true")
vram_group.add_argument("--always-cpu", action="store_true")

parser.add_argument("--always-offload-from-vram", action="store_true")
parser.add_argument("--pytorch-deterministic", action="store_true")

parser.add_argument("--cuda-malloc", action="store_true")
parser.add_argument("--cuda-stream", action="store_true")
parser.add_argument("--pin-shared-memory", action="store_true")

parser.add_argument("--disable-gpu-warning", action="store_true")
parser.add_argument("--fast-fp16", action="store_true")

parser.add_argument("--mmap-torch-files", action="store_true")
parser.add_argument("--disable-mmap", action="store_true")


class SageAttentionFuncs(enum.Enum):
    auto = "auto"
    fp16_triton = "fp16_triton"
    fp16_cuda = "fp16_cuda"
    fp8_cuda = "fp8_cuda"


class Sage_quantization_backend(enum.Enum):
    cuda = "cuda"
    triton = "triton"


class Sage_qk_quant_gran(enum.Enum):
    per_warp = "per_warp"
    per_thread = "per_thread"


class Sage_pv_accum_dtype(enum.Enum):
    fp16 = "fp16"
    fp32 = "fp32"
    fp16fp32 = "fp16+fp32"
    fp32fp32 = "fp32+fp32"


parser.add_argument("--sage2-function", type=SageAttentionFuncs, default=SageAttentionFuncs.auto, action=EnumAction)
parser.add_argument("--sage-quantization-backend", type=Sage_quantization_backend, default=Sage_quantization_backend.triton, action=EnumAction)
parser.add_argument("--sage-quant-gran", type=Sage_qk_quant_gran, default=Sage_qk_quant_gran.per_thread, action=EnumAction)
parser.add_argument("--sage-accum-dtype", type=Sage_pv_accum_dtype, default=Sage_pv_accum_dtype.fp32, action=EnumAction)


args, _ = parser.parse_known_args()

# TODO: Stop using this to hack every problem...
dynamic_args = dict(
    embedding_dir=None,
    forge_unet_storage_dtype=None,
    kontext=False,
    edit=False,
    nunchaku=False,
    ref_latents=[],
    concat_latent=None,
)
"""
Some parameters that are used throughout the Webui
- embedding_dir: `str` - set in modules/sd_models/forge_model_reload
- forge_unet_storage_dtype: `torch.dtype` - set in modules/sd_models/forge_model_reload
- kontext: `bool` - Flux Kontext
- edit: `bool` - Qwen-Image-Edit
- nunchaku: `bool` - Nunchaku (SVDQ) Models
- ref_latents: `list[torch.Tensor]` - Reference Latent(s) for Flux Kontext & Qwen-Image-Edit
- concat_latent: `torch.Tensor` - Input Latent for Wan 2.2 I2V
"""