Describe the bug
the transformer model introduced in SD3 expects the below parameters (transformer_sd3.py). there are two missing parameters that remain undefined in the SD3ControlNetModel class (controlnet_sd3.py) - dual_attention_layers and qk_norm.
@register_to_config
def __init__(
self,
sample_size: int = 128,
patch_size: int = 2,
in_channels: int = 16,
num_layers: int = 18,
attention_head_dim: int = 64,
num_attention_heads: int = 18,
joint_attention_dim: int = 4096,
caption_projection_dim: int = 1152,
pooled_projection_dim: int = 2048,
out_channels: int = 16,
pos_embed_max_size: int = 96,
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
self.out_channels = out_channels if out_channels is not None else default_out_channels
self.inner_dim = self.config.num_attention_heads * self.config.attention_head_dim
Reproduction
class SD3ControlNetModel(ModelMixin, ConfigMixin, PeftAdapterMixin, FromOriginalModelMixin):
_supports_gradient_checkpointing = True
@register_to_config
def __init__(
self,
sample_size: int = 128,
patch_size: int = 2,
in_channels: int = 16,
num_layers: int = 18,
attention_head_dim: int = 64,
num_attention_heads: int = 18,
joint_attention_dim: int = 4096,
caption_projection_dim: int = 1152,
pooled_projection_dim: int = 2048,
out_channels: int = 16,
pos_embed_max_size: int = 96,
extra_conditioning_channels: int = 0,
dual_attention_layers=(),
qk_norm=None,
):
super().__init__()
default_out_channels = in_channels
self.out_channels = out_channels if out_channels is not None else default_out_channels
self.inner_dim = num_attention_heads * attention_head_dim
Logs
Traceback (most recent call last):
File "/data/user/user/project/controlnet_huggingface/diffusers/examples/controlnet/train_controlnet_sd3.py", line 1412, in<module>
main(args)
File "/data/user/user/project/controlnet_huggingface/diffusers/examples/controlnet/train_controlnet_sd3.py", line 989, in main
controlnet = SD3ControlNetModel.from_transformer(transformer)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/user/data/conda/envs/diffusers/lib/python3.11/site-packages/diffusers/models/controlnets/controlnet_sd3.py", line 251, in from_transformer
controlnet = cls(**config)
^^^^^^^^^^^^^
File "/home/user/data/conda/envs/diffusers/lib/python3.11/site-packages/diffusers/configuration_utils.py", line 665, in inner_init
init(self, *args, **init_kwargs)
TypeError: SD3ControlNetModel.__init__() got an unexpected keyword argument 'dual_attention_layers'
System Info
diffusers: 0.32.0.dev0
Who can help?
@yiyixuxu@sayakpaul@DN6@asomoza
Describe the bug
the transformer model introduced in SD3 expects the below parameters (transformer_sd3.py). there are two missing parameters that remain undefined in the SD3ControlNetModel class (controlnet_sd3.py) - dual_attention_layers and qk_norm.
Reproduction
class SD3ControlNetModel(ModelMixin, ConfigMixin, PeftAdapterMixin, FromOriginalModelMixin):
_supports_gradient_checkpointing = True
Logs
System Info
diffusers: 0.32.0.dev0
Who can help?
@yiyixuxu@sayakpaul@DN6@asomoza