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add self.use_ada_layer_norm_* params back to BasicTransformerBlock #6841

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Merged
yiyixuxu merged 1 commit into from
Feb 4, 2024
Merged

add self.use_ada_layer_norm_* params back to BasicTransformerBlock #6841

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6 changes: 4 additions & 2 deletions examples/community/stable_diffusion_reference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -538,7 +538,7 @@ def hack_CrossAttnDownBlock2D_forward(

return hidden_states, output_states

def hacked_DownBlock2D_forward(self, hidden_states, temb=None):
def hacked_DownBlock2D_forward(self, hidden_states, temb=None, **kwargs):
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@sayakpaul sayakpaul Feb 4, 2024

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Why is kwargs needed?

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@yiyixuxu yiyixuxu Feb 4, 2024

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hacked_DownBlock2D_forward is a function they wrote to replace the forward method of the DownBlock2D ,hence the signature has to match. We added a new argument scale for the lora refactor and causes an error here without **kwargs

I think they should write their custom blocks instead

eps = 1e-6

output_states = ()
Expand Down Expand Up @@ -634,7 +634,9 @@ def hacked_CrossAttnUpBlock2D_forward(

return hidden_states

def hacked_UpBlock2D_forward(self, hidden_states, res_hidden_states_tuple, temb=None, upsample_size=None):
def hacked_UpBlock2D_forward(
self, hidden_states, res_hidden_states_tuple, temb=None, upsample_size=None, **kwargs
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@sayakpaul sayakpaul Feb 4, 2024

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Same.

):
eps = 1e-6
for i, resnet in enumerate(self.resnets):
# pop res hidden states
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6 changes: 4 additions & 2 deletions examples/community/stable_diffusion_xl_reference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -507,7 +507,7 @@ def hack_CrossAttnDownBlock2D_forward(

return hidden_states, output_states

def hacked_DownBlock2D_forward(self, hidden_states, temb=None):
def hacked_DownBlock2D_forward(self, hidden_states, temb=None, **kwargs):
eps = 1e-6

output_states = ()
Expand Down Expand Up @@ -603,7 +603,9 @@ def hacked_CrossAttnUpBlock2D_forward(

return hidden_states

def hacked_UpBlock2D_forward(self, hidden_states, res_hidden_states_tuple, temb=None, upsample_size=None):
def hacked_UpBlock2D_forward(
self, hidden_states, res_hidden_states_tuple, temb=None, upsample_size=None, **kwargs
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@sayakpaul sayakpaul Feb 4, 2024

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Same.

):
eps = 1e-6
for i, resnet in enumerate(self.resnets):
# pop res hidden states
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6 changes: 6 additions & 0 deletions src/diffusers/models/attention.py
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Expand Up @@ -158,6 +158,12 @@ def __init__(
super().__init__()
self.only_cross_attention = only_cross_attention

self.use_ada_layer_norm_zero = (num_embeds_ada_norm is not None) and norm_type == "ada_norm_zero"
self.use_ada_layer_norm = (num_embeds_ada_norm is not None) and norm_type == "ada_norm"
self.use_ada_layer_norm_single = norm_type == "ada_norm_single"
self.use_layer_norm = norm_type == "layer_norm"
self.use_ada_layer_norm_continuous = norm_type == "ada_norm_continuous"
Comment on lines +161 to +165
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@sayakpaul sayakpaul Feb 4, 2024

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I am okay with this.

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@pcuenca pcuenca Feb 6, 2024

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Sorry for the late reply. I'd maybe just add a comment to state that they are kept for back-compatibility reasons.


if norm_type in ("ada_norm", "ada_norm_zero") and num_embeds_ada_norm is None:
raise ValueError(
f"`norm_type` is set to {norm_type}, but `num_embeds_ada_norm` is not defined. Please make sure to"
Expand Down