add loading from the hub test

Author: sayakpaul

src/diffusers/configuration_utils.py

@@ -364,7 +364,11 @@ def load_config(
             if subfolder is not None:
                 raise ValueError("DDUF file only allow for 1 level of directory. Please check the DDUF structure")
             # paths inside a DDUF file must always be "/"
-            config_file = cls.config_name if pretrained_model_name_or_path == "" else "/".join([pretrained_model_name_or_path, cls.config_name])
+            config_file = (
+                cls.config_name
+                if pretrained_model_name_or_path == ""
+                else "/".join([pretrained_model_name_or_path, cls.config_name])
+            )
             if config_file not in dduf_entries:
                 raise ValueError(
                     f"We did not manage to find the file {config_file} in the dduf file. We only have the following files {dduf_entries.keys()}"

src/diffusers/utils/hub_utils.py

@@ -299,7 +299,11 @@ def _get_model_file(
     if dduf_entries:
         if subfolder is not None:
             raise ValueError("DDUF file only allow for 1 level of directory. Please check the DDUF structure")
-        model_file = weights_name if pretrained_model_name_or_path == "" else "/".join([pretrained_model_name_or_path, weights_name])
+        model_file = (
+            weights_name
+            if pretrained_model_name_or_path == ""
+            else "/".join([pretrained_model_name_or_path, weights_name])
+        )
         if model_file in dduf_entries:
             return model_file
         else:

src/diffusers/utils/testing_utils.py

@@ -476,6 +476,18 @@ def decorator(test_case):
     return decorator
 
 
+def require_hf_hub_version_greater(hf_hub_version):
+    def decorator(test_case):
+        correct_hf_hub_version = version.parse(
+            version.parse(importlib.metadata.version("huggingface_hub")).base_version
+        ) > version.parse(hf_hub_version)
+        return unittest.skipUnless(
+            correct_hf_hub_version, f"Test requires huggingface_hub with the version greater than {hf_hub_version}."
+        )(test_case)
+
+    return decorator
+
+
 def deprecate_after_peft_backend(test_case):
     """
     Decorator marking a test that will be skipped after PEFT backend

tests/pipelines/test_pipelines.py

@@ -75,9 +75,11 @@
     nightly,
     require_compel,
     require_flax,
+    require_hf_hub_version_greater,
     require_onnxruntime,
     require_torch_2,
     require_torch_gpu,
+    require_transformers_version_greater,
     run_test_in_subprocess,
     slow,
     torch_device,
@@ -1802,6 +1804,25 @@ def test_pipe_same_device_id_offload(self):
         sd.maybe_free_model_hooks()
         assert sd._offload_gpu_id == 5
 
+    @require_hf_hub_version_greater("0.26.5")
+    @require_transformers_version_greater("4.47.0")
+    @parameterized.expand([torch.float32, torch.float16])
+    def test_load_dduf_from_hub(self, dtype):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            pipe = DiffusionPipeline.from_pretrained(
+                "DDUF/tiny-flux-dev-pipe-dduf", dduf_file="fluxpipeline.dduf", cache_dir=tmpdir, torch_dtype=dtype
+            ).to(torch_device)
+            out_1 = pipe(prompt="dog", num_inference_steps=5, generator=torch.manual_seed(0), output_type="np").images
+
+            pipe.save_pretrained(tmpdir)
+            loaded_pipe = DiffusionPipeline.from_pretrained(tmpdir, torch_dtype=dtype).to(torch_device)
+
+            out_2 = loaded_pipe(
+                prompt="dog", num_inference_steps=5, generator=torch.manual_seed(0), output_type="np"
+            ).images
+
+        self.assertTrue(np.allclose(out_1, out_2, atol=1e-4, rtol=1e-4))
+
 
 @slow
 @require_torch_gpu

tests/pipelines/test_pipelines_common.py

@@ -43,7 +43,9 @@
     CaptureLogger,
     require_accelerate_version_greater,
     require_accelerator,
+    require_hf_hub_version_greater,
     require_torch,
+    require_transformers_version_greater,
     skip_mps,
     torch_device,
 )
@@ -1902,8 +1904,8 @@ def test_StableDiffusionMixin_component(self):
             )
         )
 
-    # @pytest.mark.xfail(condition=not os.getenv("RUN_DDUF_TEST", False), strict=True)
-    # Should consider guarding the test with proper transformers and huggingface_hub versions.
+    @require_hf_hub_version_greater("0.26.5")
+    @require_transformers_version_greater("4.47.0")
     def test_save_load_dduf(self):
         from huggingface_hub import export_folder_as_dduf
 
@@ -1922,7 +1924,6 @@ def test_save_load_dduf(self):
             dduf_filename = os.path.join(tmpdir, f"{pipe.__class__.__name__.lower()}.dduf")
             pipe.save_pretrained(tmpdir, safe_serialization=True)
             export_folder_as_dduf(dduf_filename, folder_path=tmpdir)
-            print(f"{os.listdir(tmpdir)=}")
             loaded_pipe = self.pipeline_class.from_pretrained(tmpdir, dduf_file=dduf_filename).to(torch_device)
 
         inputs["generator"] = torch.manual_seed(0)