Reorganize pipeline tests (#963)

* Reorganize pipeline tests

* fix vq

tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py

@@ -30,13 +30,16 @@ from diffusers import (
     VQModel,
 )
 from diffusers.utils import floats_tensor, load_image, slow, torch_device
+from diffusers.utils.testing_utils import require_torch_gpu
 from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
 
+from ...test_pipelines_common import PipelineTesterMixin
+
 
 torch.backends.cuda.matmul.allow_tf32 = False
 
 
-class PipelineFastTests(unittest.TestCase):
+class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
     def tearDown(self):
         # clean up the VRAM after each test
         super().tearDown()
@@ -461,8 +464,8 @@ class PipelineFastTests(unittest.TestCase):
 
 
 @slow
-@unittest.skipIf(torch_device == "cpu", "Stable diffusion is supposed to run on GPU")
-class PipelineIntegrationTests(unittest.TestCase):
+@require_torch_gpu
+class StableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):
         # clean up the VRAM after each test
         super().tearDown()

tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint.py

@@ -29,14 +29,17 @@ from diffusers import (
     VQModel,
 )
 from diffusers.utils import floats_tensor, load_image, slow, torch_device
+from diffusers.utils.testing_utils import require_torch_gpu
 from PIL import Image
 from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
 
+from ...test_pipelines_common import PipelineTesterMixin
+
 
 torch.backends.cuda.matmul.allow_tf32 = False
 
 
-class PipelineFastTests(unittest.TestCase):
+class StableDiffusionInpaintPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
     def tearDown(self):
         # clean up the VRAM after each test
         super().tearDown()
@@ -258,8 +261,8 @@ class PipelineFastTests(unittest.TestCase):
 
 
 @slow
-@unittest.skipIf(torch_device == "cpu", "Stable diffusion is supposed to run on GPU")
-class PipelineIntegrationTests(unittest.TestCase):
+@require_torch_gpu
+class StableDiffusionInpaintPipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):
         # clean up the VRAM after each test
         super().tearDown()

tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint_legacy.py

@@ -31,14 +31,17 @@ from diffusers import (
     VQModel,
 )
 from diffusers.utils import floats_tensor, load_image, slow, torch_device
+from diffusers.utils.testing_utils import require_torch_gpu
 from PIL import Image
 from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
 
+from ...test_pipelines_common import PipelineTesterMixin
+
 
 torch.backends.cuda.matmul.allow_tf32 = False
 
 
-class PipelineFastTests(unittest.TestCase):
+class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
     def tearDown(self):
         # clean up the VRAM after each test
         super().tearDown()
@@ -338,8 +341,8 @@ class PipelineFastTests(unittest.TestCase):
 
 
 @slow
-@unittest.skipIf(torch_device == "cpu", "Stable diffusion is supposed to run on GPU")
-class PipelineIntegrationTests(unittest.TestCase):
+@require_torch_gpu
+class StableDiffusionInpaintLegacyPipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):
         # clean up the VRAM after each test
         super().tearDown()

tests/test_pipelines_common.py

+from diffusers.utils.testing_utils import require_torch
+
+
+@require_torch
+class PipelineTesterMixin:
+    """
+    This mixin is designed to be used with unittest.TestCase classes.
+    It provides a set of common tests for each PyTorch pipeline, e.g. saving and loading the pipeline,
+    equivalence of dict and tuple outputs, etc.
+    """
+
+    pass

tests/test_pipelines_flax.py

@@ -30,8 +30,8 @@ if is_flax_available():
     from jax import pmap
 
 
-@require_flax
 @slow
+@require_flax
 class FlaxPipelineTests(unittest.TestCase):
     def test_dummy_all_tpus(self):
         pipeline, params = FlaxStableDiffusionPipeline.from_pretrained(

tests/test_pipelines_onnx_common.py

+from diffusers.utils.testing_utils import require_onnxruntime
+
+
+@require_onnxruntime
+class OnnxPipelineTesterMixin:
+    """
+    This mixin is designed to be used with unittest.TestCase classes.
+    It provides a set of common tests for each ONNXRuntime pipeline, e.g. saving and loading the pipeline,
+    equivalence of dict and tuple outputs, etc.
+    """
+
+    pass