Rename StableDiffusionOnnxPipeline -> OnnxStableDiffusionPipeline (#887)

Rename and deprecate

src/diffusers/__init__.py

@@ -58,7 +58,7 @@ else:
     from .utils.dummy_torch_and_transformers_objects import *  # noqa F403
 
 if is_torch_available() and is_transformers_available() and is_onnx_available():
-    from .pipelines import StableDiffusionOnnxPipeline
+    from .pipelines import OnnxStableDiffusionPipeline, StableDiffusionOnnxPipeline
 else:
     from .utils.dummy_torch_and_transformers_and_onnx_objects import *  # noqa F403
 

src/diffusers/pipelines/__init__.py

@@ -20,7 +20,7 @@ if is_torch_available() and is_transformers_available():
     )
 
 if is_transformers_available() and is_onnx_available():
-    from .stable_diffusion import StableDiffusionOnnxPipeline
+    from .stable_diffusion import OnnxStableDiffusionPipeline, StableDiffusionOnnxPipeline
 
 if is_transformers_available() and is_flax_available():
     from .stable_diffusion import FlaxStableDiffusionPipeline

src/diffusers/pipelines/stable_diffusion/__init__.py

@@ -34,7 +34,7 @@ if is_transformers_available() and is_torch_available():
     from .safety_checker import StableDiffusionSafetyChecker
 
 if is_transformers_available() and is_onnx_available():
-    from .pipeline_stable_diffusion_onnx import StableDiffusionOnnxPipeline
+    from .pipeline_onnx_stable_diffusion import OnnxStableDiffusionPipeline, StableDiffusionOnnxPipeline
 
 if is_transformers_available() and is_flax_available():
     import flax

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_onnx.py → src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py

@@ -8,14 +8,14 @@ from transformers import CLIPFeatureExtractor, CLIPTokenizer
 from ...onnx_utils import OnnxRuntimeModel
 from ...pipeline_utils import DiffusionPipeline
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
-from ...utils import logging
+from ...utils import deprecate, logging
 from . import StableDiffusionPipelineOutput
 
 
 logger = logging.get_logger(__name__)
 
 
-class StableDiffusionOnnxPipeline(DiffusionPipeline):
+class OnnxStableDiffusionPipeline(DiffusionPipeline):
     vae_decoder: OnnxRuntimeModel
     text_encoder: OnnxRuntimeModel
     tokenizer: CLIPTokenizer
@@ -198,3 +198,27 @@ class StableDiffusionOnnxPipeline(DiffusionPipeline):
             return (image, has_nsfw_concept)
 
         return StableDiffusionPipelineOutput(images=image, nsfw_content_detected=has_nsfw_concept)
+
+
+class StableDiffusionOnnxPipeline(OnnxStableDiffusionPipeline):
+    def __init__(
+        self,
+        vae_decoder: OnnxRuntimeModel,
+        text_encoder: OnnxRuntimeModel,
+        tokenizer: CLIPTokenizer,
+        unet: OnnxRuntimeModel,
+        scheduler: Union[DDIMScheduler, PNDMScheduler, LMSDiscreteScheduler],
+        safety_checker: OnnxRuntimeModel,
+        feature_extractor: CLIPFeatureExtractor,
+    ):
+        deprecation_message = "Please use `OnnxStableDiffusionPipeline` instead of `StableDiffusionOnnxPipeline`."
+        deprecate("StableDiffusionOnnxPipeline", "1.0.0", deprecation_message)
+        super().__init__(
+            vae_decoder=vae_decoder,
+            text_encoder=text_encoder,
+            tokenizer=tokenizer,
+            unet=unet,
+            scheduler=scheduler,
+            safety_checker=safety_checker,
+            feature_extractor=feature_extractor,
+        )

src/diffusers/utils/dummy_torch_and_transformers_and_onnx_objects.py

@@ -4,6 +4,21 @@
 from ..utils import DummyObject, requires_backends
 
 
+class OnnxStableDiffusionPipeline(metaclass=DummyObject):
+    _backends = ["torch", "transformers", "onnx"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch", "transformers", "onnx"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers", "onnx"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers", "onnx"])
+
+
 class StableDiffusionOnnxPipeline(metaclass=DummyObject):
     _backends = ["torch", "transformers", "onnx"]
 

tests/test_pipelines.py

@@ -37,13 +37,13 @@ from diffusers import (
     LDMPipeline,
     LDMTextToImagePipeline,
     LMSDiscreteScheduler,
+    OnnxStableDiffusionPipeline,
     PNDMPipeline,
     PNDMScheduler,
     ScoreSdeVePipeline,
     ScoreSdeVeScheduler,
     StableDiffusionImg2ImgPipeline,
     StableDiffusionInpaintPipeline,
-    StableDiffusionOnnxPipeline,
     StableDiffusionPipeline,
     UNet2DConditionModel,
     UNet2DModel,
@@ -2010,7 +2010,7 @@ class PipelineTesterMixin(unittest.TestCase):
 
     @slow
     def test_stable_diffusion_onnx(self):
-        sd_pipe = StableDiffusionOnnxPipeline.from_pretrained(
+        sd_pipe = OnnxStableDiffusionPipeline.from_pretrained(
             "CompVis/stable-diffusion-v1-4", revision="onnx", provider="CPUExecutionProvider"
         )
 
@@ -2214,7 +2214,7 @@ class PipelineTesterMixin(unittest.TestCase):
 
         test_callback_fn.has_been_called = False
 
-        pipe = StableDiffusionOnnxPipeline.from_pretrained(
+        pipe = OnnxStableDiffusionPipeline.from_pretrained(
             "CompVis/stable-diffusion-v1-4", revision="onnx", provider="CPUExecutionProvider"
         )
         pipe.set_progress_bar_config(disable=None)