Speed up test and remove kwargs from call (#1446)

Remove kwargs from call

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion.py

@@ -445,7 +445,6 @@ class AltDiffusionPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py

@@ -484,7 +484,6 @@ class AltDiffusionImg2ImgPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py

@@ -528,7 +528,6 @@ class CycleDiffusionPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion.py

@@ -289,7 +289,6 @@ class FlaxStableDiffusionPipeline(FlaxDiffusionPipeline):
         jit: bool = False,
         debug: bool = False,
         neg_prompt_ids: jnp.array = None,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py

@@ -205,7 +205,6 @@ class OnnxStableDiffusionPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, np.ndarray], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         if isinstance(prompt, str):
             batch_size = 1

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py

@@ -241,7 +241,6 @@ class OnnxStableDiffusionImg2ImgPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, np.ndarray], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint.py

@@ -259,7 +259,6 @@ class OnnxStableDiffusionInpaintPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, np.ndarray], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint_legacy.py

@@ -241,7 +241,6 @@ class OnnxStableDiffusionInpaintPipelineLegacy(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, np.ndarray], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

@@ -444,7 +444,6 @@ class StableDiffusionPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_image_variation.py

@@ -342,7 +342,6 @@ class StableDiffusionImageVariationPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py

@@ -493,7 +493,6 @@ class StableDiffusionImg2ImgPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py

@@ -566,7 +566,6 @@ class StableDiffusionInpaintPipeline(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py

@@ -492,7 +492,6 @@ class StableDiffusionInpaintPipelineLegacy(DiffusionPipeline):
         return_dict: bool = True,
         callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
         callback_steps: Optional[int] = 1,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py

@@ -546,7 +546,6 @@ class StableDiffusionPipelineSafe(DiffusionPipeline):
         sld_threshold: Optional[float] = 0.01,
         sld_momentum_scale: Optional[float] = 0.3,
         sld_mom_beta: Optional[float] = 0.4,
-        **kwargs,
     ):
         r"""
         Function invoked when calling the pipeline for generation.

tests/pipelines/stable_diffusion/test_stable_diffusion.py

@@ -765,18 +765,18 @@ class StableDiffusionPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
 
         prompt = "hey"
 
-        output = sd_pipe(prompt, number_of_steps=1, output_type="np")
+        output = sd_pipe(prompt, num_inference_steps=1, output_type="np")
         image_shape = output.images[0].shape[:2]
         assert image_shape == (64, 64)
 
-        output = sd_pipe(prompt, number_of_steps=1, height=96, width=96, output_type="np")
+        output = sd_pipe(prompt, num_inference_steps=1, height=96, width=96, output_type="np")
         image_shape = output.images[0].shape[:2]
         assert image_shape == (96, 96)
 
         config = dict(sd_pipe.unet.config)
         config["sample_size"] = 96
         sd_pipe.unet = UNet2DConditionModel.from_config(config).to(torch_device)
-        output = sd_pipe(prompt, number_of_steps=1, output_type="np")
+        output = sd_pipe(prompt, num_inference_steps=1, output_type="np")
         image_shape = output.images[0].shape[:2]
         assert image_shape == (192, 192)