Release: v0.26.2-patch

fix sd reference community ppeline

Co-authored-by: yiyixuxu <yixu310@gmail,com>

examples/community/stable_diffusion_reference.py

@@ -538,7 +538,7 @@ class StableDiffusionReferencePipeline(StableDiffusionPipeline):
 
             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 = ()
@@ -634,7 +634,9 @@ class StableDiffusionReferencePipeline(StableDiffusionPipeline):
 
             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
+        ):
             eps = 1e-6
             for i, resnet in enumerate(self.resnets):
                 # pop res hidden states

examples/community/stable_diffusion_xl_reference.py

@@ -507,7 +507,7 @@ class StableDiffusionXLReferencePipeline(StableDiffusionXLPipeline):
 
             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 = ()
@@ -603,7 +603,9 @@ class StableDiffusionXLReferencePipeline(StableDiffusionXLPipeline):
 
             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
+        ):
             eps = 1e-6
             for i, resnet in enumerate(self.resnets):
                 # pop res hidden states

setup.py

@@ -249,7 +249,7 @@ version_range_max = max(sys.version_info[1], 10) + 1
 
 setup(
     name="diffusers",
-    version="0.26.1",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
+    version="0.26.2",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
     description="State-of-the-art diffusion in PyTorch and JAX.",
     long_description=open("README.md", "r", encoding="utf-8").read(),
     long_description_content_type="text/markdown",

src/diffusers/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.26.1"
+__version__ = "0.26.2"
 
 from typing import TYPE_CHECKING
 

src/diffusers/models/attention.py

@@ -158,6 +158,12 @@ class BasicTransformerBlock(nn.Module):
         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"
+
         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"