Improve downloads of sharded variants

src/diffusers/pipelines/pipeline_loading_utils.py

@@ -198,10 +198,31 @@ def convert_to_variant(filename):
             variant_filename = f"{filename.split('.')[0]}.{variant}.{filename.split('.')[1]}"
         return variant_filename
 
-    for f in non_variant_filenames:
-        variant_filename = convert_to_variant(f)
-        if variant_filename not in usable_filenames:
-            usable_filenames.add(f)
+    def find_component(filename):
+        if not len(filename.split("/")) == 2:
+            return
+        component = filename.split("/")[0]
+        return component
+
+    def has_sharded_variant(component, variant, variant_filenames):
+        # If component exists check for sharded variant index filename
+        # If component doesn't exist check main dir for sharded variant index filename
+        component = component + "/" if component else ""
+        variant_index_re = re.compile(
+            rf"{component}({'|'.join(weight_prefixes)})\.({'|'.join(weight_suffixs)})\.index\.{variant}\.json$"
+        )
+        return any(f for f in variant_filenames if variant_index_re.match(f) is not None)
+
+    for filename in non_variant_filenames:
+        if convert_to_variant(filename) in variant_filenames:
+            continue
+
+        component = find_component(filename)
+        # If a sharded variant exists skip adding to allowed patterns
+        if has_sharded_variant(component, variant, variant_filenames):
+            continue
+
+        usable_filenames.add(filename)
 
     return usable_filenames, variant_filenames
 

tests/pipelines/test_pipeline_utils.py

@@ -18,7 +18,7 @@
     StableDiffusionPipeline,
     UNet2DConditionModel,
 )
-from diffusers.pipelines.pipeline_loading_utils import is_safetensors_compatible
+from diffusers.pipelines.pipeline_loading_utils import is_safetensors_compatible, variant_compatible_siblings
 from diffusers.utils.testing_utils import torch_device
 
 
@@ -210,6 +210,135 @@ def test_diffusers_is_compatible_no_components_only_variants(self):
         self.assertFalse(is_safetensors_compatible(filenames))
 
 
+class VariantCompatibleSiblingsTest(unittest.TestCase):
+    def test_only_non_variants_downloaded(self):
+        variant = "fp16"
+        filenames = [
+            f"vae/diffusion_pytorch_model.{variant}.safetensors",
+            "vae/diffusion_pytorch_model.safetensors",
+            f"text_encoder/model.{variant}.safetensors",
+            "text_encoder/model.safetensors",
+            f"unet/diffusion_pytorch_model.{variant}.safetensors",
+            "unet/diffusion_pytorch_model.safetensors",
+        ]
+
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=None)
+        assert all(variant not in f for f in model_filenames)
+
+    def test_only_variants_downloaded(self):
+        variant = "fp16"
+        filenames = [
+            f"vae/diffusion_pytorch_model.{variant}.safetensors",
+            "vae/diffusion_pytorch_model.safetensors",
+            f"text_encoder/model.{variant}.safetensors",
+            "text_encoder/model.safetensors",
+            f"unet/diffusion_pytorch_model.{variant}.safetensors",
+            "unet/diffusion_pytorch_model.safetensors",
+        ]
+
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=variant)
+        assert all(variant in f for f in model_filenames)
+
+    def test_mixed_variants_downloaded(self):
+        variant = "fp16"
+        non_variant_file = "text_encoder/model.safetensors"
+        filenames = [
+            f"vae/diffusion_pytorch_model.{variant}.safetensors",
+            "vae/diffusion_pytorch_model.safetensors",
+            "text_encoder/model.safetensors",
+            f"unet/diffusion_pytorch_model.{variant}.safetensors",
+            "unet/diffusion_pytorch_model.safetensors",
+        ]
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=variant)
+        assert all(variant in f if f != non_variant_file else variant not in f for f in model_filenames)
+
+    def test_non_variants_in_main_dir_downloaded(self):
+        variant = "fp16"
+        filenames = [
+            f"diffusion_pytorch_model.{variant}.safetensors",
+            "diffusion_pytorch_model.safetensors",
+            "model.safetensors",
+            f"model.{variant}.safetensors",
+            f"diffusion_pytorch_model.{variant}.safetensors",
+            "diffusion_pytorch_model.safetensors",
+        ]
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=None)
+        assert all(variant not in f for f in model_filenames)
+
+    def test_variants_in_main_dir_downloaded(self):
+        variant = "fp16"
+        filenames = [
+            f"diffusion_pytorch_model.{variant}.safetensors",
+            "diffusion_pytorch_model.safetensors",
+            "model.safetensors",
+            f"model.{variant}.safetensors",
+            f"diffusion_pytorch_model.{variant}.safetensors",
+            "diffusion_pytorch_model.safetensors",
+        ]
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=variant)
+        assert all(variant in f for f in model_filenames)
+
+    def test_mixed_variants_in_main_dir_downloaded(self):
+        variant = "fp16"
+        non_variant_file = "model.safetensors"
+        filenames = [
+            f"diffusion_pytorch_model.{variant}.safetensors",
+            "diffusion_pytorch_model.safetensors",
+            "model.safetensors",
+            f"diffusion_pytorch_model.{variant}.safetensors",
+            "diffusion_pytorch_model.safetensors",
+        ]
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=variant)
+        assert all(variant in f if f != non_variant_file else variant not in f for f in model_filenames)
+
+    def test_sharded_non_variants_downloaded(self):
+        variant = "fp16"
+        filenames = [
+            f"unet/diffusion_pytorch_model.safetensors.index.{variant}.json",
+            "unet/diffusion_pytorch_model.safetensors.index.json",
+            "unet/diffusion_pytorch_model-00001-of-00003.safetensors",
+            "unet/diffusion_pytorch_model-00002-of-00003.safetensors",
+            "unet/diffusion_pytorch_model-00003-of-00003.safetensors",
+            f"unet/diffusion_pytorch_model.{variant}-00001-of-00002.safetensors",
+            f"unet/diffusion_pytorch_model.{variant}-00002-of-00002.safetensors",
+        ]
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=None)
+        assert all(variant not in f for f in model_filenames)
+
+    def test_sharded_variants_downloaded(self):
+        variant = "fp16"
+        filenames = [
+            f"unet/diffusion_pytorch_model.safetensors.index.{variant}.json",
+            "unet/diffusion_pytorch_model.safetensors.index.json",
+            "unet/diffusion_pytorch_model-00001-of-00003.safetensors",
+            "unet/diffusion_pytorch_model-00002-of-00003.safetensors",
+            "unet/diffusion_pytorch_model-00003-of-00003.safetensors",
+            f"unet/diffusion_pytorch_model.{variant}-00001-of-00002.safetensors",
+            f"unet/diffusion_pytorch_model.{variant}-00002-of-00002.safetensors",
+        ]
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=variant)
+        assert all(variant in f for f in model_filenames)
+
+    def test_sharded_mixed_variants_downloaded(self):
+        variant = "fp16"
+        allowed_non_variant = "unet"
+        filenames = [
+            f"vae/diffusion_pytorch_model.safetensors.index.{variant}.json",
+            "vae/diffusion_pytorch_model.safetensors.index.json",
+            "unet/diffusion_pytorch_model.safetensors.index.json",
+            "unet/diffusion_pytorch_model-00001-of-00003.safetensors",
+            "unet/diffusion_pytorch_model-00002-of-00003.safetensors",
+            "unet/diffusion_pytorch_model-00003-of-00003.safetensors",
+            f"vae/diffusion_pytorch_model.{variant}-00001-of-00002.safetensors",
+            f"vae/diffusion_pytorch_model.{variant}-00002-of-00002.safetensors",
+            "vae/diffusion_pytorch_model-00001-of-00003.safetensors",
+            "vae/diffusion_pytorch_model-00002-of-00003.safetensors",
+            "vae/diffusion_pytorch_model-00003-of-00003.safetensors",
+        ]
+        model_filenames, variant_filenames = variant_compatible_siblings(filenames, variant=variant)
+        assert all(variant in f if allowed_non_variant not in f else variant not in f for f in model_filenames)
+
+
 class ProgressBarTests(unittest.TestCase):
     def get_dummy_components_image_generation(self):
         cross_attention_dim = 8