@@ -51,7 +51,7 @@ class StableDiffusionXLPipelineFastTests(PipelineLatentTesterMixin, PipelineTest
5151 def get_dummy_components (self ):
5252 torch .manual_seed (0 )
5353 unet = UNet2DConditionModel (
54- block_out_channels = (32 , 64 ),
54+ block_out_channels = (2 , 4 ),
5555 layers_per_block = 2 ,
5656 sample_size = 32 ,
5757 in_channels = 4 ,
@@ -66,6 +66,7 @@ def get_dummy_components(self):
6666 transformer_layers_per_block = (1 , 2 ),
6767 projection_class_embeddings_input_dim = 80 , # 6 * 8 + 32
6868 cross_attention_dim = 64 ,
69+ norm_num_groups = 1 ,
6970 )
7071 scheduler = EulerDiscreteScheduler (
7172 beta_start = 0.00085 ,
@@ -144,7 +145,7 @@ def test_stable_diffusion_xl_euler(self):
144145 image_slice = image [0 , - 3 :, - 3 :, - 1 ]
145146
146147 assert image .shape == (1 , 64 , 64 , 3 )
147- expected_slice = np .array ([0.5873 , 0.6128 , 0.4797 , 0.5122 , 0.5674 , 0.4639 , 0.5227 , 0.5149 , 0.4747 ])
148+ expected_slice = np .array ([0.5552 , 0.5569 , 0.4725 , 0.4348 , 0.4994 , 0.4632 , 0.5142 , 0.5012 , 0.47 ])
148149
149150 assert np .abs (image_slice .flatten () - expected_slice ).max () < 1e-2
150151
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