Standardize on using `image` argument in all pipelines (#1361)

* feat: switch core pipelines to use image arg

* test: update tests for core pipelines

* feat: switch examples to use image arg

* docs: update docs to use image arg

* style: format code using black and doc-builder

* fix: deprecate use of init_image in all pipelines

tests/pipelines/latent_diffusion/test_latent_diffusion_superresolution.py

@@ -79,7 +79,7 @@ class LDMSuperResolutionPipelineFastTests(PipelineTesterMixin, unittest.TestCase
         init_image = self.dummy_image.to(device)
 
         generator = torch.Generator(device=device).manual_seed(0)
-        image = ldm(init_image, generator=generator, num_inference_steps=2, output_type="numpy").images
+        image = ldm(image=init_image, generator=generator, num_inference_steps=2, output_type="numpy").images
 
         image_slice = image[0, -3:, -3:, -1]
 
@@ -124,7 +124,7 @@ class LDMSuperResolutionPipelineIntegrationTests(unittest.TestCase):
         ldm.set_progress_bar_config(disable=None)
 
         generator = torch.Generator(device=torch_device).manual_seed(0)
-        image = ldm(init_image, generator=generator, num_inference_steps=20, output_type="numpy").images
+        image = ldm(image=init_image, generator=generator, num_inference_steps=20, output_type="numpy").images
 
         image_slice = image[0, -3:, -3:, -1]
 

tests/pipelines/stable_diffusion/test_cycle_diffusion.py

@@ -186,7 +186,7 @@ class CycleDiffusionPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
             source_prompt=source_prompt,
             generator=generator,
             num_inference_steps=2,
-            init_image=init_image,
+            image=init_image,
             eta=0.1,
             strength=0.8,
             guidance_scale=3,
@@ -244,7 +244,7 @@ class CycleDiffusionPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
             source_prompt=source_prompt,
             generator=generator,
             num_inference_steps=2,
-            init_image=init_image,
+            image=init_image,
             eta=0.1,
             strength=0.8,
             guidance_scale=3,
@@ -297,7 +297,7 @@ class CycleDiffusionPipelineIntegrationTests(unittest.TestCase):
         output = pipe(
             prompt=prompt,
             source_prompt=source_prompt,
-            init_image=init_image,
+            image=init_image,
             num_inference_steps=100,
             eta=0.1,
             strength=0.85,
@@ -336,7 +336,7 @@ class CycleDiffusionPipelineIntegrationTests(unittest.TestCase):
         output = pipe(
             prompt=prompt,
             source_prompt=source_prompt,
-            init_image=init_image,
+            image=init_image,
             num_inference_steps=100,
             eta=0.1,
             strength=0.85,

tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_img2img.py

@@ -72,7 +72,7 @@ class OnnxStableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         generator = np.random.RandomState(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             strength=0.75,
             guidance_scale=7.5,
             num_inference_steps=10,
@@ -110,7 +110,7 @@ class OnnxStableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         generator = np.random.RandomState(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             strength=0.75,
             guidance_scale=7.5,
             num_inference_steps=10,

tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_inpaint_legacy.py

@@ -80,7 +80,7 @@ class StableDiffusionOnnxInpaintLegacyPipelineIntegrationTests(unittest.TestCase
         generator = np.random.RandomState(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
             strength=0.75,
             guidance_scale=7.5,

tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py

@@ -188,7 +188,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         )
 
         image = output.images
@@ -200,7 +200,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             return_dict=False,
         )[0]
 
@@ -245,7 +245,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         )
         image = output.images
         image_slice = image[0, -3:, -3:, -1]
@@ -285,7 +285,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         )
 
         image = output.images
@@ -328,7 +328,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         )
         image = output.images
 
@@ -339,7 +339,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             return_dict=False,
         )
         image_from_tuple = output[0]
@@ -382,7 +382,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             prompt,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         ).images
 
         assert images.shape == (1, 32, 32, 3)
@@ -393,7 +393,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             [prompt] * batch_size,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         ).images
 
         assert images.shape == (batch_size, 32, 32, 3)
@@ -404,7 +404,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             prompt,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             num_images_per_prompt=num_images_per_prompt,
         ).images
 
@@ -416,7 +416,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             [prompt] * batch_size,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             num_images_per_prompt=num_images_per_prompt,
         ).images
 
@@ -458,7 +458,7 @@ class StableDiffusionImg2ImgPipelineFastTests(PipelineTesterMixin, unittest.Test
             generator=generator,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         ).images
 
         assert image.shape == (1, 32, 32, 3)
@@ -497,7 +497,7 @@ class StableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         generator = torch.Generator(device=torch_device).manual_seed(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             strength=0.75,
             guidance_scale=7.5,
             generator=generator,
@@ -535,7 +535,7 @@ class StableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         generator = torch.Generator(device=torch_device).manual_seed(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             strength=0.75,
             guidance_scale=7.5,
             generator=generator,
@@ -572,7 +572,7 @@ class StableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         generator = torch.Generator(device=torch_device).manual_seed(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             strength=0.75,
             guidance_scale=7.5,
             generator=generator,
@@ -626,7 +626,7 @@ class StableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         with torch.autocast(torch_device):
             pipe(
                 prompt=prompt,
-                init_image=init_image,
+                image=init_image,
                 strength=0.75,
                 num_inference_steps=50,
                 guidance_scale=7.5,
@@ -663,7 +663,7 @@ class StableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         generator = torch.Generator(device=torch_device).manual_seed(0)
         _ = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             strength=0.75,
             guidance_scale=7.5,
             generator=generator,

tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint_legacy.py

@@ -191,7 +191,7 @@ class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittes
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
         )
 
@@ -204,7 +204,7 @@ class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittes
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
             return_dict=False,
         )[0]
@@ -252,7 +252,7 @@ class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittes
             guidance_scale=6.0,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
         )
 
@@ -295,7 +295,7 @@ class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittes
             prompt,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
         ).images
 
@@ -307,7 +307,7 @@ class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittes
             [prompt] * batch_size,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
         ).images
 
@@ -319,7 +319,7 @@ class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittes
             prompt,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
             num_images_per_prompt=num_images_per_prompt,
         ).images
@@ -332,7 +332,7 @@ class StableDiffusionInpaintLegacyPipelineFastTests(PipelineTesterMixin, unittes
             [prompt] * batch_size,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
             num_images_per_prompt=num_images_per_prompt,
         ).images
@@ -374,7 +374,7 @@ class StableDiffusionInpaintLegacyPipelineIntegrationTests(unittest.TestCase):
         generator = torch.Generator(device=torch_device).manual_seed(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
             strength=0.75,
             guidance_scale=7.5,
@@ -416,7 +416,7 @@ class StableDiffusionInpaintLegacyPipelineIntegrationTests(unittest.TestCase):
         generator = torch.Generator(device=torch_device).manual_seed(0)
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
             strength=0.75,
             guidance_scale=7.5,
@@ -474,7 +474,7 @@ class StableDiffusionInpaintLegacyPipelineIntegrationTests(unittest.TestCase):
         with torch.autocast(torch_device):
             pipe(
                 prompt=prompt,
-                init_image=init_image,
+                image=init_image,
                 mask_image=mask_image,
                 strength=0.75,
                 num_inference_steps=50,

tests/test_pipelines.py

@@ -411,7 +411,7 @@ class PipelineFastTests(unittest.TestCase):
             generator=generator,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
             mask_image=mask_image,
         ).images
         image_img2img = img2img(
@@ -419,7 +419,7 @@ class PipelineFastTests(unittest.TestCase):
             generator=generator,
             num_inference_steps=2,
             output_type="np",
-            init_image=init_image,
+            image=init_image,
         ).images
         image_text2img = text2img(
             [prompt],