Merge branch 'main' into add-trtquant-backend

Author: sayakpaul

docs/source/en/using-diffusers/other-formats.md

@@ -176,7 +176,7 @@ Benefits of using the Diffusers-multifolder layout include:
     ).to("cuda")
     turbo_pipeline.scheduler = EulerDiscreteScheduler.from_config(
         turbo_pipeline.scheduler.config,
-        timestep+spacing="trailing"
+        timestep_spacing="trailing"
     )
     image = turbo_pipeline(
         "an astronaut riding a unicorn on mars",
@@ -267,6 +267,7 @@ pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_d
 save_folder = "flux-dev"
 pipe.save_pretrained("flux-dev")
 export_folder_as_dduf("flux-dev.dduf", folder_path=save_folder)
+```
 
 > [!TIP]
 > Packaging and loading quantized checkpoints in the DDUF format is supported as long as they respect the multi-folder structure.

docs/source/en/using-diffusers/text-img2vid.md

@@ -287,7 +287,7 @@ export_to_video(output, "output.mp4", fps=16)
 
 ## Reduce memory usage
 
-Recent video models like [`HunyuanVideoPipeline`] and [`WanPipeline`], which have 10B+ parameters, require a lot of memory and it often exceeds the memory availabe on consumer hardware. Diffusers offers several techniques for reducing the memory requirements of these large models.
+Recent video models like [`HunyuanVideoPipeline`] and [`WanPipeline`], which have 10B+ parameters, require a lot of memory and it often exceeds the memory available on consumer hardware. Diffusers offers several techniques for reducing the memory requirements of these large models.
 
 > [!TIP]
 > Refer to the [Reduce memory usage](../optimization/memory) guide for more details about other memory saving techniques.

src/diffusers/utils/import_utils.py

@@ -70,10 +70,11 @@ def _is_package_available(pkg_name: str, get_dist_name: bool = False) -> Tuple[b
                 # Fallback for Python < 3.10
                 for dist in importlib_metadata.distributions():
                     _top_level_declared = (dist.read_text("top_level.txt") or "").split()
-                    _infered_opt_names = {
+                    # Infer top-level package names from file structure
+                    _inferred_opt_names = {
                         f.parts[0] if len(f.parts) > 1 else inspect.getmodulename(f) for f in (dist.files or [])
                     } - {None}
-                    _top_level_inferred = filter(lambda name: "." not in name, _infered_opt_names)
+                    _top_level_inferred = filter(lambda name: "." not in name, _inferred_opt_names)
                     for pkg in _top_level_declared or _top_level_inferred:
                         _package_map[pkg].append(dist.metadata["Name"])
             except Exception as _:
@@ -119,7 +120,7 @@ def _is_package_available(pkg_name: str, get_dist_name: bool = False) -> Tuple[b
     _safetensors_available, _safetensors_version = _is_package_available("safetensors")
 
 else:
-    logger.info("Disabling Safetensors because USE_TF is set")
+    logger.info("Disabling Safetensors because USE_SAFETENSORS is set")
     _safetensors_available = False
 
 _onnxruntime_version = "N/A"

tests/hooks/test_hooks.py

@@ -219,6 +219,7 @@ def test_inference(self):
 
         self.assertAlmostEqual(output1, output2, places=5)
         self.assertAlmostEqual(output1, output3, places=5)
+        self.assertAlmostEqual(output2, output3, places=5)
 
     def test_skip_layer_hook(self):
         registry = HookRegistry.check_if_exists_or_initialize(self.model)