fix tests

tests/test_modeling_utils.py

@@ -845,7 +845,6 @@ class PipelineTesterMixin(unittest.TestCase):
 
     @slow
     def test_ddpm_cifar10(self):
-        generator = torch.manual_seed(0)
         model_id = "fusing/ddpm-cifar10"
 
         unet = UNetModel.from_pretrained(model_id)
@@ -853,12 +852,14 @@ class PipelineTesterMixin(unittest.TestCase):
         noise_scheduler = noise_scheduler.set_format("pt")
 
         ddpm = DDPMPipeline(unet=unet, noise_scheduler=noise_scheduler)
+
+        generator = torch.manual_seed(0)
         image = ddpm(generator=generator)
 
         image_slice = image[0, -1, -3:, -3:].cpu()
 
         assert image.shape == (1, 3, 32, 32)
-        expected_slice = torch.tensor([0.2249, 0.3375, 0.2359, 0.0929, 0.3439, 0.3156, 0.1937, 0.3585, 0.1761])
+        expected_slice = torch.tensor([-0.5712, -0.6215, -0.5953, -0.5438, -0.4775, -0.4539, -0.5172, -0.4872, -0.5105])
         assert (image_slice.flatten() - expected_slice).abs().max() < 1e-2
 
     @slow
@@ -883,20 +884,20 @@ class PipelineTesterMixin(unittest.TestCase):
 
     @slow
     def test_pndm_cifar10(self):
-        generator = torch.manual_seed(0)
         model_id = "fusing/ddpm-cifar10"
 
         unet = UNetModel.from_pretrained(model_id)
         noise_scheduler = PNDMScheduler(tensor_format="pt")
 
         pndm = PNDMPipeline(unet=unet, noise_scheduler=noise_scheduler)
+        generator = torch.manual_seed(0)
         image = pndm(generator=generator)
 
         image_slice = image[0, -1, -3:, -3:].cpu()
 
         assert image.shape == (1, 3, 32, 32)
         expected_slice = torch.tensor(
-            [-0.7925, -0.7902, -0.7789, -0.7796, -0.8000, -0.7596, -0.6852, -0.7125, -0.7494]
+            [-0.6872, -0.7071, -0.7188, -0.7057, -0.7515, -0.7191, -0.7377, -0.7565, -0.7500]
         )
         assert (image_slice.flatten() - expected_slice).abs().max() < 1e-2