Fix device on save/load tests

tests/test_pipelines.py

@@ -102,8 +102,12 @@ class DownloadTests(unittest.TestCase):
 
         pipe_2 = StableDiffusionPipeline.from_pretrained("hf-internal-testing/tiny-stable-diffusion-torch")
         pipe_2 = pipe_2.to(torch_device)
-        generator_2 = generator.manual_seed(0)
-        out_2 = pipe_2(prompt, num_inference_steps=2, generator=generator_2, output_type="numpy").images
+        if torch_device == "mps":
+            # device type MPS is not supported for torch.Generator() api.
+            generator = torch.manual_seed(0)
+        else:
+            generator = torch.Generator(device=torch_device).manual_seed(0)
+        out_2 = pipe_2(prompt, num_inference_steps=2, generator=generator, output_type="numpy").images
 
         assert np.max(np.abs(out - out_2)) < 1e-3
 
@@ -124,8 +128,14 @@ class DownloadTests(unittest.TestCase):
             pipe.save_pretrained(tmpdirname)
             pipe_2 = StableDiffusionPipeline.from_pretrained(tmpdirname, safety_checker=None)
             pipe_2 = pipe_2.to(torch_device)
-            generator_2 = generator.manual_seed(0)
-            out_2 = pipe_2(prompt, num_inference_steps=2, generator=generator_2, output_type="numpy").images
+
+            if torch_device == "mps":
+                # device type MPS is not supported for torch.Generator() api.
+                generator = torch.manual_seed(0)
+            else:
+                generator = torch.Generator(device=torch_device).manual_seed(0)
+
+            out_2 = pipe_2(prompt, num_inference_steps=2, generator=generator, output_type="numpy").images
 
         assert np.max(np.abs(out - out_2)) < 1e-3
 
@@ -144,8 +154,14 @@ class DownloadTests(unittest.TestCase):
             pipe.save_pretrained(tmpdirname)
             pipe_2 = StableDiffusionPipeline.from_pretrained(tmpdirname)
             pipe_2 = pipe_2.to(torch_device)
-            generator_2 = generator.manual_seed(0)
-            out_2 = pipe_2(prompt, num_inference_steps=2, generator=generator_2, output_type="numpy").images
+
+            if torch_device == "mps":
+                # device type MPS is not supported for torch.Generator() api.
+                generator = torch.manual_seed(0)
+            else:
+                generator = torch.Generator(device=torch_device).manual_seed(0)
+
+            out_2 = pipe_2(prompt, num_inference_steps=2, generator=generator, output_type="numpy").images
 
         assert np.max(np.abs(out - out_2)) < 1e-3