Merge branch 'main' into flux-control-lora-bnb-8bit

src/diffusers/pipelines/flux/pipeline_flux_inpaint.py

@@ -1193,6 +1193,11 @@ class FluxInpaintPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FluxIPAdapterM
             image = self.vae.decode(latents, return_dict=False)[0]
             image = self.image_processor.postprocess(image, output_type=output_type)
 
+            if padding_mask_crop is not None:
+                image = [
+                    self.image_processor.apply_overlay(mask_image, original_image, i, crops_coords) for i in image
+                ]
+
         # Offload all models
         self.maybe_free_model_hooks()
 

src/diffusers/utils/dynamic_modules_utils.py

@@ -154,12 +154,30 @@ def check_imports(filename):
     return get_relative_imports(filename)
 
 
-def get_class_in_module(class_name, module_path):
+def get_class_in_module(class_name, module_path, pretrained_model_name_or_path=None):
     """
     Import a module on the cache directory for modules and extract a class from it.
     """
     module_path = module_path.replace(os.path.sep, ".")
-    module = importlib.import_module(module_path)
+    try:
+        module = importlib.import_module(module_path)
+    except ModuleNotFoundError as e:
+        # This can happen when the repo id contains ".", which Python's import machinery interprets as a directory
+        # separator. We do a bit of monkey patching to detect and fix this case.
+        if not (
+            pretrained_model_name_or_path is not None
+            and "." in pretrained_model_name_or_path
+            and module_path.startswith("diffusers_modules")
+            and pretrained_model_name_or_path.replace("/", "--") in module_path
+        ):
+            raise e  # We can't figure this one out, just reraise the original error
+
+        corrected_path = os.path.join(HF_MODULES_CACHE, module_path.replace(".", "/")) + ".py"
+        corrected_path = corrected_path.replace(
+            pretrained_model_name_or_path.replace("/", "--").replace(".", "/"),
+            pretrained_model_name_or_path.replace("/", "--"),
+        )
+        module = importlib.machinery.SourceFileLoader(module_path, corrected_path).load_module()
 
     if class_name is None:
         return find_pipeline_class(module)
@@ -454,4 +472,4 @@ def get_class_from_dynamic_module(
         revision=revision,
         local_files_only=local_files_only,
     )
-    return get_class_in_module(class_name, final_module.replace(".py", ""))
+    return get_class_in_module(class_name, final_module.replace(".py", ""), pretrained_model_name_or_path)

tests/pipelines/test_pipelines.py

@@ -1105,6 +1105,21 @@ class CustomPipelineTests(unittest.TestCase):
 
         assert images.shape == (1, 64, 64, 3)
 
+    def test_remote_custom_pipe_with_dot_in_name(self):
+        # make sure that trust remote code has to be passed
+        with self.assertRaises(ValueError):
+            pipeline = DiffusionPipeline.from_pretrained("akasharidas/ddpm-cifar10-32-dot.in.name")
+
+        pipeline = DiffusionPipeline.from_pretrained("akasharidas/ddpm-cifar10-32-dot.in.name", trust_remote_code=True)
+
+        assert pipeline.__class__.__name__ == "CustomPipeline"
+
+        pipeline = pipeline.to(torch_device)
+        images, output_str = pipeline(num_inference_steps=2, output_type="np")
+
+        assert images[0].shape == (1, 32, 32, 3)
+        assert output_str == "This is a test"
+
     def test_local_custom_pipeline_repo(self):
         local_custom_pipeline_path = get_tests_dir("fixtures/custom_pipeline")
         pipeline = DiffusionPipeline.from_pretrained(