[Quality] Make style (#3341)

setup.py

@@ -111,6 +111,7 @@ _deps = [
     "torch>=1.4",
     "torchvision",
     "transformers>=4.25.1",
+    "urllib3<=2.0.0",
 ]
 
 # this is a lookup table with items like:
@@ -181,7 +182,7 @@ extras = {}
 
 
 extras = {}
-extras["quality"] = deps_list("black", "isort", "ruff", "hf-doc-builder")
+extras["quality"] = deps_list("urllib3", "black", "isort", "ruff", "hf-doc-builder")
 extras["docs"] = deps_list("hf-doc-builder")
 extras["training"] = deps_list("accelerate", "datasets", "protobuf", "tensorboard", "Jinja2")
 extras["test"] = deps_list(

src/diffusers/dependency_versions_table.py

@@ -35,4 +35,5 @@ deps = {
     "torch": "torch>=1.4",
     "torchvision": "torchvision",
     "transformers": "transformers>=4.25.1",
+    "urllib3": "urllib3<=2.0.0",
 }

src/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img_superresolution.py

@@ -762,7 +762,7 @@ class IFImg2ImgSuperResolutionPipeline(DiffusionPipeline):
             image = [np.array(i).astype(np.float32) / 255.0 for i in image]
 
             image = np.stack(image, axis=0)  # to np
-            torch.from_numpy(image.transpose(0, 3, 1, 2))
+            image = torch.from_numpy(image.transpose(0, 3, 1, 2))
         elif isinstance(image[0], np.ndarray):
             image = np.stack(image, axis=0)  # to np
             if image.ndim == 5:

src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting_superresolution.py

@@ -798,7 +798,7 @@ class IFInpaintingSuperResolutionPipeline(DiffusionPipeline):
             image = [np.array(i).astype(np.float32) / 255.0 for i in image]
 
             image = np.stack(image, axis=0)  # to np
-            torch.from_numpy(image.transpose(0, 3, 1, 2))
+            image = torch.from_numpy(image.transpose(0, 3, 1, 2))
         elif isinstance(image[0], np.ndarray):
             image = np.stack(image, axis=0)  # to np
             if image.ndim == 5: