[core] deprecate onnx (huggingface#14658)

* deprecate onnx

* up

Author: sayakpaul

.github/workflows/nightly_tests.yml

@@ -461,7 +461,6 @@ jobs:
       run_big_gpu_torch_tests,
       run_nightly_quantization_tests,
       run_nightly_pipeline_level_quantization_tests,
-      # run_nightly_onnx_tests,
       torch_minimum_version_cuda_tests,
     ]
     if: always()

src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_onnx_stable_diffusion_inpaint_legacy.py

@@ -10,7 +10,7 @@
 from ....schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ....utils import deprecate, logging
 from ...onnx_utils import ORT_TO_NP_TYPE, OnnxRuntimeModel
-from ...pipeline_utils import DiffusionPipeline
+from ...pipeline_utils import DeprecatedPipelineMixin, DiffusionPipeline
 from ...stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
 
 
@@ -38,7 +38,9 @@ def preprocess_mask(mask, scale_factor=8):
     return mask
 
 
-class OnnxStableDiffusionInpaintPipelineLegacy(DiffusionPipeline):
+class OnnxStableDiffusionInpaintPipelineLegacy(DeprecatedPipelineMixin, DiffusionPipeline):
+    _last_supported_version = "0.43.0"
+
     r"""
     Pipeline for text-guided image inpainting using Stable Diffusion. This is a *legacy feature* for Onnx pipelines to
     provide compatibility with StableDiffusionInpaintPipelineLegacy and may be removed in the future.

src/diffusers/pipelines/onnx_utils.py

@@ -24,7 +24,7 @@
 from huggingface_hub import hf_hub_download
 from huggingface_hub.utils import validate_hf_hub_args
 
-from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
+from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, deprecate, is_onnx_available, logging
 
 
 if is_onnx_available():
@@ -50,8 +50,14 @@
 
 
 class OnnxRuntimeModel:
+    _last_supported_version = "0.43.0"
+
     def __init__(self, model=None, **kwargs):
-        logger.info("`diffusers.OnnxRuntimeModel` is experimental and might change in the future.")
+        deprecate(
+            "OnnxRuntimeModel",
+            "0.43.0",
+            "Please use Optimum for ONNX Runtime support.",
+        )
         self.model = model
         self.model_save_dir = kwargs.get("model_save_dir", None)
         self.latest_model_name = kwargs.get("latest_model_name", ONNX_WEIGHTS_NAME)

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py

@@ -23,14 +23,16 @@
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import deprecate, logging
 from ..onnx_utils import ORT_TO_NP_TYPE, OnnxRuntimeModel
-from ..pipeline_utils import DiffusionPipeline
+from ..pipeline_utils import DeprecatedPipelineMixin, DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 
 
 logger = logging.get_logger(__name__)
 
 
-class OnnxStableDiffusionPipeline(DiffusionPipeline):
+class OnnxStableDiffusionPipeline(DeprecatedPipelineMixin, DiffusionPipeline):
+    _last_supported_version = "0.43.0"
+
     vae_encoder: OnnxRuntimeModel
     vae_decoder: OnnxRuntimeModel
     text_encoder: OnnxRuntimeModel

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py

@@ -24,7 +24,7 @@
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import PIL_INTERPOLATION, deprecate, logging
 from ..onnx_utils import ORT_TO_NP_TYPE, OnnxRuntimeModel
-from ..pipeline_utils import DiffusionPipeline
+from ..pipeline_utils import DeprecatedPipelineMixin, DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 
 
@@ -55,7 +55,9 @@ def preprocess(image):
     return image
 
 
-class OnnxStableDiffusionImg2ImgPipeline(DiffusionPipeline):
+class OnnxStableDiffusionImg2ImgPipeline(DeprecatedPipelineMixin, DiffusionPipeline):
+    _last_supported_version = "0.43.0"
+
     r"""
     Pipeline for text-guided image to image generation using Stable Diffusion.
 

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint.py

@@ -24,7 +24,7 @@
 from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
 from ...utils import PIL_INTERPOLATION, deprecate, logging
 from ..onnx_utils import ORT_TO_NP_TYPE, OnnxRuntimeModel
-from ..pipeline_utils import DiffusionPipeline
+from ..pipeline_utils import DeprecatedPipelineMixin, DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 
 
@@ -53,7 +53,9 @@ def prepare_mask_and_masked_image(image, mask, latents_shape):
     return mask, masked_image
 
 
-class OnnxStableDiffusionInpaintPipeline(DiffusionPipeline):
+class OnnxStableDiffusionInpaintPipeline(DeprecatedPipelineMixin, DiffusionPipeline):
+    _last_supported_version = "0.43.0"
+
     r"""
     Pipeline for text-guided image inpainting using Stable Diffusion. *This is an experimental feature*.
 

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_upscale.py

@@ -24,7 +24,7 @@
 from ...schedulers import DDPMScheduler, KarrasDiffusionSchedulers
 from ...utils import deprecate, logging
 from ..onnx_utils import ORT_TO_NP_TYPE, OnnxRuntimeModel
-from ..pipeline_utils import DiffusionPipeline
+from ..pipeline_utils import DeprecatedPipelineMixin, DiffusionPipeline
 from . import StableDiffusionPipelineOutput
 
 
@@ -53,7 +53,9 @@ def preprocess(image):
     return image
 
 
-class OnnxStableDiffusionUpscalePipeline(DiffusionPipeline):
+class OnnxStableDiffusionUpscalePipeline(DeprecatedPipelineMixin, DiffusionPipeline):
+    _last_supported_version = "0.43.0"
+
     vae: OnnxRuntimeModel
     text_encoder: OnnxRuntimeModel
     tokenizer: CLIPTokenizer

tests/others/test_check_dummies.py

@@ -43,23 +43,16 @@ def test_find_backend(self):
         # )
         # assert double_backend_with_underscore == "sentencepiece_and_tensorflow_text"
 
-        triple_backend = find_backend(
-            "    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):"
-        )
-        assert triple_backend == "torch_and_transformers_and_onnx"
-
     def test_read_init(self):
         objects = read_init()
         # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
         assert "torch" in objects
         assert "torch_and_transformers" in objects
-        assert "torch_and_transformers_and_onnx" in objects
 
         # Likewise, we can't assert on the exact content of a key
         assert "UNet2DModel" in objects["torch"]
         assert "StableDiffusionPipeline" in objects["torch_and_transformers"]
         assert "LMSDiscreteScheduler" in objects["torch_and_scipy"]
-        assert "OnnxStableDiffusionPipeline" in objects["torch_and_transformers_and_onnx"]
 
     def test_create_dummy_object(self):
         dummy_constant = create_dummy_object("CONSTANT", "'torch'")