[tests] set overwrite_modular_index=True in tests

tests/modular_pipelines/anima/test_modular_pipeline_anima.py

@@ -146,7 +146,7 @@ def test_save_load_components(self):
         pipe = self.get_pipeline()
 
         with tempfile.TemporaryDirectory() as tmpdir:
-            pipe.save_pretrained(tmpdir, safe_serialization=True)
+            pipe.save_pretrained(tmpdir, safe_serialization=True, overwrite_modular_index=True)
             pipe = self.pipeline_class.from_pretrained(tmpdir)
             pipe.load_components()
 

tests/modular_pipelines/cosmos/test_modular_pipeline_cosmos3.py

@@ -514,7 +514,7 @@ def test_set_timesteps_native_flow_schedule(self):
 class TestCosmos3OmniModularPipelineLoading(Cosmos3OmniModularPipelineTesterConfig, ModularLoadingTesterMixin):
     def test_save_from_pretrained(self, tmp_path):
         base_pipe = self.get_pipeline().to(torch_device)
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         loaded_pipe = ModularPipeline.from_pretrained(str(tmp_path))
         loaded_pipe.load_components(dtype=torch.float32)

tests/modular_pipelines/cosmos/test_modular_pipeline_cosmos3_distilled.py

@@ -205,7 +205,7 @@ class TestCosmos3DistilledModularPipelineLoading(
 ):
     def test_save_from_pretrained(self, tmp_path):
         base_pipe = self.get_pipeline().to(torch_device)
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         loaded_pipe = ModularPipeline.from_pretrained(str(tmp_path))
         loaded_pipe.load_components(torch_dtype=torch.float32)

tests/modular_pipelines/flux/test_modular_pipeline_flux.py

@@ -162,7 +162,7 @@ def test_float16_inference(self):
 class TestFluxImg2ImgModularPipelineLoading(FluxImg2ImgModularPipelineTesterConfig, ModularLoadingTesterMixin):
     def test_save_from_pretrained(self, tmp_path, base_pipe_output):
         base_pipe = self.get_pipeline().to(torch_device)
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         pipe = ModularPipeline.from_pretrained(tmp_path)
         pipe.load_components(dtype=torch.float32)
@@ -249,7 +249,7 @@ def test_float16_inference(self):
 class TestFluxKontextModularPipelineLoading(FluxKontextModularPipelineTesterConfig, ModularLoadingTesterMixin):
     def test_save_from_pretrained(self, tmp_path, base_pipe_output):
         base_pipe = self.get_pipeline().to(torch_device)
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         pipe = ModularPipeline.from_pretrained(tmp_path)
         pipe.load_components(dtype=torch.float32)

tests/modular_pipelines/minimax_music3/test_modular_pipeline_minimax_music3.py

@@ -139,7 +139,7 @@ class TestMiniMaxMusic3ModularPipelineLoading(MiniMaxMusic3ModularPipelineTester
     def test_save_from_pretrained(self, tmp_path, base_pipe_output):
         # the common implementation indexes 4-D image outputs; compare the audio waveform directly
         base_pipe = self.get_pipeline().to(torch_device)
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         pipe = ModularPipeline.from_pretrained(str(tmp_path))
         pipe.load_components(dtype=torch.float32)

tests/modular_pipelines/stable_diffusion_3/test_modular_pipeline_stable_diffusion_3.py

@@ -86,7 +86,7 @@ def test_save_from_pretrained(self, tmp_path):
         base_pipe = self.get_pipeline().to(torch_device)
         pipes.append(base_pipe)
 
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
         pipe = self.pipeline_class.from_pretrained(tmp_path).to(torch_device)
         pipe.load_components(dtype=torch.float32)
         pipe.to(torch_device)
@@ -102,7 +102,7 @@ def test_save_from_pretrained(self, tmp_path):
 
     def test_load_expected_components_from_save_pretrained(self, tmp_path):
         base_pipe = self.get_pipeline()
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         pipe = self.pipeline_class.from_pretrained(tmp_path)
         pipe.load_components(dtype=torch.float32)
@@ -191,7 +191,7 @@ def test_save_from_pretrained(self, tmp_path):
         base_pipe = self.get_pipeline().to(torch_device)
         pipes.append(base_pipe)
 
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
         pipe = self.pipeline_class.from_pretrained(tmp_path).to(torch_device)
         pipe.load_components(dtype=torch.float32)
         pipe.to(torch_device)
@@ -208,7 +208,7 @@ def test_save_from_pretrained(self, tmp_path):
 
     def test_load_expected_components_from_save_pretrained(self, tmp_path):
         base_pipe = self.get_pipeline()
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         pipe = self.pipeline_class.from_pretrained(tmp_path)
         pipe.load_components(dtype=torch.float32)

tests/modular_pipelines/test_modular_pipeline_loading.py

@@ -16,6 +16,7 @@
 import json
 import os
 import shutil
+import warnings
 
 import pytest
 import torch
@@ -156,7 +157,7 @@ def test_save_pretrained_roundtrip_with_local_model(self, tmp_path):
         original_state_dict = pipe.unet.state_dict()
 
         save_dir = str(tmp_path / "my-pipeline")
-        pipe.save_pretrained(save_dir)
+        pipe.save_pretrained(save_dir, overwrite_modular_index=True)
 
         loaded_pipe = ModularPipeline.from_pretrained(save_dir)
         loaded_pipe.load_components(dtype=torch.float32)
@@ -204,7 +205,8 @@ def test_save_pretrained_default_writes_self_contained_local_copy(self, tmp_path
         pipe.load_components(names=["unet"], dtype=torch.float32)
 
         save_dir = str(tmp_path / "my-pipeline")
-        pipe.save_pretrained(save_dir)
+        with pytest.warns(FutureWarning, match="overwrite_modular_index"):
+            pipe.save_pretrained(save_dir)
 
         with open(os.path.join(save_dir, "modular_model_index.json")) as f:
             index = json.load(f)
@@ -221,6 +223,15 @@ def test_save_pretrained_default_writes_self_contained_local_copy(self, tmp_path
         loaded_pipe.load_components(names=["unet"], dtype=torch.float32, local_files_only=True)
         assert loaded_pipe.unet is not None
 
+    @pytest.mark.parametrize("overwrite_modular_index", [True, False])
+    def test_save_pretrained_explicit_overwrite_modular_index_does_not_warn(self, tmp_path, overwrite_modular_index):
+        pipe = ModularPipeline.from_pretrained("hf-internal-testing/tiny-stable-diffusion-xl-pipe")
+        pipe.load_components(names=["unet"], dtype=torch.float32)
+
+        with warnings.catch_warnings():
+            warnings.filterwarnings("error", message=".*overwrite_modular_index", category=FutureWarning)
+            pipe.save_pretrained(str(tmp_path / "my-pipeline"), overwrite_modular_index=overwrite_modular_index)
+
     def test_save_pretrained_overwrite_modular_index(self, tmp_path):
         """With overwrite_modular_index=True, all component references should point to the save directory."""
         pipe = ModularPipeline.from_pretrained("hf-internal-testing/tiny-stable-diffusion-xl-pipe")
@@ -266,7 +277,7 @@ def test_init_fallback_when_blocks_class_name_is_base_class(self, tmp_path):
 
         # 3. Save and reload — the saved config will have _blocks_class_name="SequentialPipelineBlocks"
         save_dir = str(tmp_path / "pipeline")
-        t2i_pipe.save_pretrained(save_dir)
+        t2i_pipe.save_pretrained(save_dir, overwrite_modular_index=True)
         loaded_pipe = ModularPipeline.from_pretrained(save_dir)
 
         # 4. Verify it fell back to default_blocks_name and has correct blocks

tests/modular_pipelines/test_modular_pipelines_custom_blocks.py

@@ -364,7 +364,7 @@ def __call__(self, components, state: PipelineState) -> PipelineState:
 
             block = ModularPipelineBlocks.from_pretrained(pipeline_repo_dir, trust_remote_code=True)
             pipe = block.init_pipeline()
-            pipe.save_pretrained(pipeline_repo_dir)
+            pipe.save_pretrained(pipeline_repo_dir, overwrite_modular_index=True)
 
             # Step 3: Load the pipeline from the saved directory.
             loaded_pipe = ModularPipeline.from_pretrained(pipeline_repo_dir, trust_remote_code=True)

tests/modular_pipelines/testing_utils/loading.py

@@ -38,7 +38,7 @@ class ModularLoadingTesterMixin(BaseModularPipelineOutputMixin):
 
     def test_save_from_pretrained(self, tmp_path, base_pipe_output):
         base_pipe = self.get_pipeline().to(torch_device)
-        base_pipe.save_pretrained(str(tmp_path))
+        base_pipe.save_pretrained(str(tmp_path), overwrite_modular_index=True)
 
         pipe = ModularPipeline.from_pretrained(tmp_path)
         pipe.load_components(dtype=torch.float32)
@@ -67,7 +67,7 @@ def test_load_expected_components_from_pretrained(self, tmp_path):
     def test_load_expected_components_from_save_pretrained(self, tmp_path):
         pipe = self.get_pipeline()
         save_dir = str(tmp_path / "saved-pipeline")
-        pipe.save_pretrained(save_dir)
+        pipe.save_pretrained(save_dir, overwrite_modular_index=True)
 
         expected = get_specified_components(save_dir)
         loaded_pipe = ModularPipeline.from_pretrained(save_dir)