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[fix] sync ControlNet-SD3 attention parameters of dual_attention_layer and qk_norm with SD3 #9784

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[fix] sync ControlNet-SD3 attention parameters of dual_attention_layer and qk_norm with SD3 #9784

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8 changes: 7 additions & 1 deletion src/diffusers/models/controlnets/controlnet_sd3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,6 +56,10 @@ def __init__(
out_channels: int = 16,
pos_embed_max_size: int = 96,
extra_conditioning_channels: int = 0,
dual_attention_layers: Tuple[
int, ...
] = (), # () for sd3.0; (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12) for sd3.5
qk_norm: Optional[str] = None,
):
super().__init__()
default_out_channels = in_channels
Expand Down Expand Up @@ -84,6 +88,8 @@ def __init__(
num_attention_heads=num_attention_heads,
attention_head_dim=self.config.attention_head_dim,
context_pre_only=False,
qk_norm=qk_norm,
use_dual_attention=True if i in dual_attention_layers else False,
)
for i in range(num_layers)
]
Expand Down Expand Up @@ -243,7 +249,7 @@ def _set_gradient_checkpointing(self, module, value=False):

@classmethod
def from_transformer(
cls, transformer, num_layers=12, num_extra_conditioning_channels=1, load_weights_from_transformer=True
cls, transformer, num_layers=12, num_extra_conditioning_channels=0, load_weights_from_transformer=True
):
config = transformer.config
config["num_layers"] = num_layers or config.num_layers
Expand Down