fix

Author: williamberman

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

@@ -453,12 +453,12 @@ def run_safety_checker(self, image, device, dtype):
             )
         return image, has_nsfw_concept
 
-    def decode_latents(self, latents, generator=None):
+    def decode_latents(self, latents):
         deprecation_message = "The decode_latents method is deprecated and will be removed in 1.0.0. Please use VaeImageProcessor.postprocess(...) instead"
         deprecate("decode_latents", "1.0.0", deprecation_message, standard_warn=False)
 
         latents = 1 / self.vae.config.scaling_factor * latents
-        image = self.vae.decode(latents, return_dict=False, generator=generator)[0]
+        image = self.vae.decode(latents, return_dict=False)[0]
         image = (image / 2 + 0.5).clamp(0, 1)
         # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()

tests/models/test_models_vae.py

@@ -890,7 +890,7 @@ def test_sd_f16(self):
 
         actual_output = out[:2, :2, :2].flatten().cpu()
         expected_output = torch.tensor(
-            [0.2510, 0.3776, 0.0000, 0.0285, 0.1519, 0.1814, 0.0000, 0.0000], dtype=torch.float16
+            [0.0000, 0.0249, 0.0000, 0.0000, 0.1709, 0.2773, 0.0471, 0.1035], dtype=torch.float16
         )
 
         assert torch_all_close(actual_output, expected_output, atol=5e-3)