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Fix: update type hints for Tuple parameters across multiple files to support variable-length tuples (#12544)
* Fix: update type hints for Tuple parameters across multiple files to support variable-length tuples * Apply style fixes --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
1 parent 8f6328c commit 5a47442

28 files changed

+110
-85
lines changed

‎examples/community/img2img_inpainting.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -45,7 +45,7 @@ def check_size(image, height, width):
4545
raise ValueError(f"Image size should be {height}x{width}, but got {h}x{w}")
4646

4747

48-
def overlay_inner_image(image, inner_image, paste_offset: Tuple[int] = (0, 0)):
48+
def overlay_inner_image(image, inner_image, paste_offset: Tuple[int, ...] = (0, 0)):
4949
inner_image = inner_image.convert("RGBA")
5050
image = image.convert("RGB")
5151

‎examples/community/matryoshka.py‎

Lines changed: 11 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -1966,16 +1966,21 @@ def __init__(
19661966
center_input_sample: bool = False,
19671967
flip_sin_to_cos: bool = True,
19681968
freq_shift: int = 0,
1969-
down_block_types: Tuple[str] = (
1969+
down_block_types: Tuple[str, ...] = (
19701970
"CrossAttnDownBlock2D",
19711971
"CrossAttnDownBlock2D",
19721972
"CrossAttnDownBlock2D",
19731973
"DownBlock2D",
19741974
),
19751975
mid_block_type: Optional[str] = "UNetMidBlock2DCrossAttn",
1976-
up_block_types: Tuple[str] = ("UpBlock2D", "CrossAttnUpBlock2D", "CrossAttnUpBlock2D", "CrossAttnUpBlock2D"),
1976+
up_block_types: Tuple[str, ...] = (
1977+
"UpBlock2D",
1978+
"CrossAttnUpBlock2D",
1979+
"CrossAttnUpBlock2D",
1980+
"CrossAttnUpBlock2D",
1981+
),
19771982
only_cross_attention: Union[bool, Tuple[bool]] = False,
1978-
block_out_channels: Tuple[int] = (320, 640, 1280, 1280),
1983+
block_out_channels: Tuple[int, ...] = (320, 640, 1280, 1280),
19791984
layers_per_block: Union[int, Tuple[int]] = 2,
19801985
downsample_padding: int = 1,
19811986
mid_block_scale_factor: float = 1,
@@ -2294,10 +2299,10 @@ def __init__(
22942299

22952300
def _check_config(
22962301
self,
2297-
down_block_types: Tuple[str],
2298-
up_block_types: Tuple[str],
2302+
down_block_types: Tuple[str, ...],
2303+
up_block_types: Tuple[str, ...],
22992304
only_cross_attention: Union[bool, Tuple[bool]],
2300-
block_out_channels: Tuple[int],
2305+
block_out_channels: Tuple[int, ...],
23012306
layers_per_block: Union[int, Tuple[int]],
23022307
cross_attention_dim: Union[int, Tuple[int]],
23032308
transformer_layers_per_block: Union[int, Tuple[int], Tuple[Tuple[int]]],

‎examples/community/pipeline_faithdiff_stable_diffusion_xl.py‎

Lines changed: 8 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -438,16 +438,21 @@ def __init__(
438438
center_input_sample: bool = False,
439439
flip_sin_to_cos: bool = True,
440440
freq_shift: int = 0,
441-
down_block_types: Tuple[str] = (
441+
down_block_types: Tuple[str, ...] = (
442442
"CrossAttnDownBlock2D",
443443
"CrossAttnDownBlock2D",
444444
"CrossAttnDownBlock2D",
445445
"DownBlock2D",
446446
),
447447
mid_block_type: Optional[str] = "UNetMidBlock2DCrossAttn",
448-
up_block_types: Tuple[str] = ("UpBlock2D", "CrossAttnUpBlock2D", "CrossAttnUpBlock2D", "CrossAttnUpBlock2D"),
448+
up_block_types: Tuple[str, ...] = (
449+
"UpBlock2D",
450+
"CrossAttnUpBlock2D",
451+
"CrossAttnUpBlock2D",
452+
"CrossAttnUpBlock2D",
453+
),
449454
only_cross_attention: Union[bool, Tuple[bool]] = False,
450-
block_out_channels: Tuple[int] = (320, 640, 1280, 1280),
455+
block_out_channels: Tuple[int, ...] = (320, 640, 1280, 1280),
451456
layers_per_block: Union[int, Tuple[int]] = 2,
452457
downsample_padding: int = 1,
453458
mid_block_scale_factor: float = 1,

‎src/diffusers/models/autoencoders/autoencoder_dc.py‎

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -102,7 +102,7 @@ def get_block(
102102
attention_head_dim: int,
103103
norm_type: str,
104104
act_fn: str,
105-
qkv_mutliscales: Tuple[int] = (),
105+
qkv_mutliscales: Tuple[int, ...] = (),
106106
):
107107
if block_type == "ResBlock":
108108
block = ResBlock(in_channels, out_channels, norm_type, act_fn)
@@ -206,8 +206,8 @@ def __init__(
206206
latent_channels: int,
207207
attention_head_dim: int = 32,
208208
block_type: Union[str, Tuple[str]] = "ResBlock",
209-
block_out_channels: Tuple[int] = (128, 256, 512, 512, 1024, 1024),
210-
layers_per_block: Tuple[int] = (2, 2, 2, 2, 2, 2),
209+
block_out_channels: Tuple[int, ...] = (128, 256, 512, 512, 1024, 1024),
210+
layers_per_block: Tuple[int, ...] = (2, 2, 2, 2, 2, 2),
211211
qkv_multiscales: Tuple[Tuple[int, ...], ...] = ((), (), (), (5,), (5,), (5,)),
212212
downsample_block_type: str = "pixel_unshuffle",
213213
out_shortcut: bool = True,
@@ -292,8 +292,8 @@ def __init__(
292292
latent_channels: int,
293293
attention_head_dim: int = 32,
294294
block_type: Union[str, Tuple[str]] = "ResBlock",
295-
block_out_channels: Tuple[int] = (128, 256, 512, 512, 1024, 1024),
296-
layers_per_block: Tuple[int] = (2, 2, 2, 2, 2, 2),
295+
block_out_channels: Tuple[int, ...] = (128, 256, 512, 512, 1024, 1024),
296+
layers_per_block: Tuple[int, ...] = (2, 2, 2, 2, 2, 2),
297297
qkv_multiscales: Tuple[Tuple[int, ...], ...] = ((), (), (), (5,), (5,), (5,)),
298298
norm_type: Union[str, Tuple[str]] = "rms_norm",
299299
act_fn: Union[str, Tuple[str]] = "silu",
@@ -440,8 +440,8 @@ def __init__(
440440
decoder_block_types: Union[str, Tuple[str]] = "ResBlock",
441441
encoder_block_out_channels: Tuple[int, ...] = (128, 256, 512, 512, 1024, 1024),
442442
decoder_block_out_channels: Tuple[int, ...] = (128, 256, 512, 512, 1024, 1024),
443-
encoder_layers_per_block: Tuple[int] = (2, 2, 2, 3, 3, 3),
444-
decoder_layers_per_block: Tuple[int] = (3, 3, 3, 3, 3, 3),
443+
encoder_layers_per_block: Tuple[int, ...] = (2, 2, 2, 3, 3, 3),
444+
decoder_layers_per_block: Tuple[int, ...] = (3, 3, 3, 3, 3, 3),
445445
encoder_qkv_multiscales: Tuple[Tuple[int, ...], ...] = ((), (), (), (5,), (5,), (5,)),
446446
decoder_qkv_multiscales: Tuple[Tuple[int, ...], ...] = ((), (), (), (5,), (5,), (5,)),
447447
upsample_block_type: str = "pixel_shuffle",

‎src/diffusers/models/autoencoders/autoencoder_kl.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -78,9 +78,9 @@ def __init__(
7878
self,
7979
in_channels: int = 3,
8080
out_channels: int = 3,
81-
down_block_types: Tuple[str] = ("DownEncoderBlock2D",),
82-
up_block_types: Tuple[str] = ("UpDecoderBlock2D",),
83-
block_out_channels: Tuple[int] = (64,),
81+
down_block_types: Tuple[str, ...] = ("DownEncoderBlock2D",),
82+
up_block_types: Tuple[str, ...] = ("UpDecoderBlock2D",),
83+
block_out_channels: Tuple[int, ...] = (64,),
8484
layers_per_block: int = 1,
8585
act_fn: str = "silu",
8686
latent_channels: int = 4,

‎src/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -995,19 +995,19 @@ def __init__(
995995
self,
996996
in_channels: int = 3,
997997
out_channels: int = 3,
998-
down_block_types: Tuple[str] = (
998+
down_block_types: Tuple[str, ...] = (
999999
"CogVideoXDownBlock3D",
10001000
"CogVideoXDownBlock3D",
10011001
"CogVideoXDownBlock3D",
10021002
"CogVideoXDownBlock3D",
10031003
),
1004-
up_block_types: Tuple[str] = (
1004+
up_block_types: Tuple[str, ...] = (
10051005
"CogVideoXUpBlock3D",
10061006
"CogVideoXUpBlock3D",
10071007
"CogVideoXUpBlock3D",
10081008
"CogVideoXUpBlock3D",
10091009
),
1010-
block_out_channels: Tuple[int] = (128, 256, 256, 512),
1010+
block_out_channels: Tuple[int, ...] = (128, 256, 256, 512),
10111011
latent_channels: int = 16,
10121012
layers_per_block: int = 3,
10131013
act_fn: str = "silu",

‎src/diffusers/models/autoencoders/autoencoder_kl_hunyuan_video.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -653,7 +653,7 @@ def __init__(
653653
"HunyuanVideoUpBlock3D",
654654
"HunyuanVideoUpBlock3D",
655655
),
656-
block_out_channels: Tuple[int] = (128, 256, 512, 512),
656+
block_out_channels: Tuple[int, ...] = (128, 256, 512, 512),
657657
layers_per_block: int = 2,
658658
act_fn: str = "silu",
659659
norm_num_groups: int = 32,

‎src/diffusers/models/autoencoders/autoencoder_kl_hunyuanimage_refiner.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -601,7 +601,7 @@ def __init__(
601601
in_channels: int = 3,
602602
out_channels: int = 3,
603603
latent_channels: int = 32,
604-
block_out_channels: Tuple[int] = (128, 256, 512, 1024, 1024),
604+
block_out_channels: Tuple[int, ...] = (128, 256, 512, 1024, 1024),
605605
layers_per_block: int = 2,
606606
spatial_compression_ratio: int = 16,
607607
temporal_compression_ratio: int = 4,

‎src/diffusers/models/autoencoders/autoencoder_kl_mochi.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -688,8 +688,8 @@ def __init__(
688688
self,
689689
in_channels: int = 15,
690690
out_channels: int = 3,
691-
encoder_block_out_channels: Tuple[int] = (64, 128, 256, 384),
692-
decoder_block_out_channels: Tuple[int] = (128, 256, 512, 768),
691+
encoder_block_out_channels: Tuple[int, ...] = (64, 128, 256, 384),
692+
decoder_block_out_channels: Tuple[int, ...] = (128, 256, 512, 768),
693693
latent_channels: int = 12,
694694
layers_per_block: Tuple[int, ...] = (3, 3, 4, 6, 3),
695695
act_fn: str = "silu",

‎src/diffusers/models/autoencoders/autoencoder_kl_qwenimage.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -679,7 +679,7 @@ def __init__(
679679
self,
680680
base_dim: int = 96,
681681
z_dim: int = 16,
682-
dim_mult: Tuple[int] = [1, 2, 4, 4],
682+
dim_mult: Tuple[int, ...] = (1, 2, 4, 4),
683683
num_res_blocks: int = 2,
684684
attn_scales: List[float] = [],
685685
temperal_downsample: List[bool] = [False, True, True],

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