error out when custom pipeline is passed with dduf_file.

Author: sayakpaul

src/diffusers/pipelines/pipeline_utils.py

@@ -728,6 +728,9 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
                 " dispatching. Please make sure to set `low_cpu_mem_usage=True`."
             )
 
+        if dduf_file and custom_pipeline:
+            raise NotImplementedError("Custom pipelines are not supported with DDUF at the moment.")
+
         # 1. Download the checkpoints and configs
         # use snapshot download here to get it working from from_pretrained
         if not os.path.isdir(pretrained_model_name_or_path):
@@ -1325,6 +1328,9 @@ def download(cls, pretrained_model_name, **kwargs) -> Union[str, os.PathLike]:
         trust_remote_code = kwargs.pop("trust_remote_code", False)
         dduf_file: Optional[Dict[str, DDUFEntry]] = kwargs.pop("dduf_file", None)
 
+        if dduf_file and custom_pipeline:
+            raise NotImplementedError("Custom pipelines are not supported with DDUF at the moment.")
+
         allow_pickle = False
         if use_safetensors is None:
             use_safetensors = True
@@ -1488,7 +1494,7 @@ def download(cls, pretrained_model_name, **kwargs) -> Union[str, os.PathLike]:
                 return snapshot_folder
 
         user_agent = {"pipeline_class": cls.__name__}
-        if not dduf_file and custom_pipeline is not None and not custom_pipeline.endswith(".py"):
+        if custom_pipeline is not None and not custom_pipeline.endswith(".py"):
             user_agent["custom_pipeline"] = custom_pipeline
 
         # download all allow_patterns - ignore_patterns

tests/pipelines/test_pipelines.py

@@ -983,6 +983,12 @@ def test_download_ignore_files(self):
             assert not any(f in ["vae/diffusion_pytorch_model.bin", "text_encoder/config.json"] for f in files)
             assert len(files) == 14
 
+    def test_download_dduf_with_custom_pipeline_raises_error(self):
+        with self.assertRaises(NotImplementedError):
+            _ = DiffusionPipeline.download(
+                "DDUF/tiny-flux-dev-pipe-dduf", dduf_file="fluxpipeline.dduf", custom_pipeline="my_pipeline"
+            )
+
     def test_get_pipeline_class_from_flax(self):
         flax_config = {"_class_name": "FlaxStableDiffusionPipeline"}
         config = {"_class_name": "StableDiffusionPipeline"}
@@ -1823,6 +1829,14 @@ def test_load_dduf_from_hub(self, dtype):
 
         self.assertTrue(np.allclose(out_1, out_2, atol=1e-4, rtol=1e-4))
 
+    @require_hf_hub_version_greater("0.26.5")
+    @require_transformers_version_greater("4.47.1")
+    def test_dduf_raises_error_with_custom_pipeline(self):
+        with self.assertRaises(NotImplementedError):
+            _ = DiffusionPipeline.from_pretrained(
+                "DDUF/tiny-flux-dev-pipe-dduf", dduf_file="fluxpipeline.dduf", custom_pipeline="my_pipeline"
+            )
+
     def test_wrong_model(self):
         tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip")
         with self.assertRaises(ValueError) as error_context: