Allow saving None pipeline components

src/diffusers/pipeline_flax_utils.py

@@ -161,6 +161,10 @@ def save_pretrained(self, save_directory: Union[str, os.PathLike], params: Union
 
         for pipeline_component_name in model_index_dict.keys():
             sub_model = getattr(self, pipeline_component_name)
+            if sub_model is None:
+                # edge case for saving a pipeline with safety_checker=None
+                continue
+
             model_cls = sub_model.__class__
 
             save_method_name = None
@@ -367,6 +371,11 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
 
         # 3. Load each module in the pipeline
         for name, (library_name, class_name) in init_dict.items():
+            if class_name is None:
+                # edge case for when the pipeline was saved with safety_checker=None
+                init_kwargs[name] = None
+                continue
+
             is_pipeline_module = hasattr(pipelines, library_name)
             loaded_sub_model = None
             sub_model_should_be_defined = True

src/diffusers/pipeline_utils.py

@@ -176,6 +176,10 @@ def save_pretrained(self, save_directory: Union[str, os.PathLike]):
 
         for pipeline_component_name in model_index_dict.keys():
             sub_model = getattr(self, pipeline_component_name)
+            if sub_model is None:
+                # edge case for saving a pipeline with safety_checker=None
+                continue
+
             model_cls = sub_model.__class__
 
             save_method_name = None
@@ -477,6 +481,11 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
 
         # 3. Load each module in the pipeline
         for name, (library_name, class_name) in init_dict.items():
+            if class_name is None:
+                # edge case for when the pipeline was saved with safety_checker=None
+                init_kwargs[name] = None
+                continue
+
             # 3.1 - now that JAX/Flax is an official framework of the library, we might load from Flax names
             if class_name.startswith("Flax"):
                 class_name = class_name[4:]

tests/pipelines/stable_diffusion/test_stable_diffusion.py

@@ -15,6 +15,7 @@
 
 import gc
 import random
+import tempfile
 import time
 import unittest
 
@@ -318,6 +319,16 @@ def test_stable_diffusion_no_safety_checker(self):
         image = pipe("example prompt", num_inference_steps=2).images[0]
         assert image is not None
 
+        # check that there's no error when saving a pipeline with one of the models being None
+        with tempfile.TemporaryDirectory() as tmpdirname:
+            pipe.save_pretrained(tmpdirname)
+            pipe = StableDiffusionPipeline.from_pretrained(tmpdirname)
+
+        # sanity check that the pipeline still works
+        assert pipe.safety_checker is None
+        image = pipe("example prompt", num_inference_steps=2).images[0]
+        assert image is not None
+
     def test_stable_diffusion_k_lms(self):
         device = "cpu"  # ensure determinism for the device-dependent torch.Generator
         unet = self.dummy_cond_unet