Fix FasterCache crash and SmoothedEnergyGuidance hook install bugs

src/diffusers/guiders/smoothed_energy_guidance.py

@@ -126,7 +126,9 @@ def __init__(
                 raise ValueError(
                     f"Expected `seg_guidance_layers` to be an int or a list of ints, but got {type(seg_guidance_layers)}."
                 )
-            seg_guidance_config = [SmoothedEnergyGuidanceConfig(layer, fqn="auto") for layer in seg_guidance_layers]
+            seg_guidance_config = [
+                SmoothedEnergyGuidanceConfig(indices=[layer], fqn="auto") for layer in seg_guidance_layers
+            ]
 
         if isinstance(seg_guidance_config, dict):
             seg_guidance_config = SmoothedEnergyGuidanceConfig.from_dict(seg_guidance_config)
@@ -145,6 +147,7 @@ def __init__(
         self._seg_layer_hook_names = [f"SmoothedEnergyGuidance_{i}" for i in range(len(self.seg_guidance_config))]
 
     def prepare_models(self, denoiser: torch.nn.Module) -> None:
+        self._count_prepared += 1
         if self._is_seg_enabled() and self.is_conditional and self._count_prepared > 1:
             for name, config in zip(self._seg_layer_hook_names, self.seg_guidance_config):
                 _apply_smoothed_energy_guidance_hook(denoiser, config, self.seg_blur_sigma, name=name)

src/diffusers/hooks/faster_cache.py

@@ -428,7 +428,9 @@ def new_forward(self, module: torch.nn.Module, *args, **kwargs) -> Any:
             should_compute_attention = self.state.iteration > 0 and self.state.iteration % self.block_skip_range == 0
             should_skip_attention = not should_compute_attention
         if should_skip_attention:
-            should_skip_attention = self.is_guidance_distilled or self.state.batch_size != batch_size
+            should_skip_attention = self.state.cache is not None and (
+                self.is_guidance_distilled or self.state.batch_size != batch_size
+            )
 
         if should_skip_attention:
             logger.debug("FasterCache - Skipping attention and using approximation")

tests/guiders/test_smoothed_energy_guidance.py

@@ -0,0 +1,75 @@
+# Copyright 2025 HuggingFace Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest.mock import patch
+
+import torch
+
+from diffusers.guiders.smoothed_energy_guidance import SmoothedEnergyGuidance
+from diffusers.models.attention import Attention
+from diffusers.models.attention_processor import AttnProcessor
+
+
+class DummyBlock(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.attn1 = Attention(
+            query_dim=4,
+            cross_attention_dim=None,
+            heads=1,
+            dim_head=4,
+            processor=AttnProcessor(),
+        )
+
+    def forward(self, hidden_states):
+        return self.attn1(hidden_states)
+
+
+class DummyTransformer(torch.nn.Module):
+    def __init__(self, num_blocks=10):
+        super().__init__()
+        self.transformer_blocks = torch.nn.ModuleList([DummyBlock() for _ in range(num_blocks)])
+
+
+def test_seg_shorthand_layers_builds_list_indices():
+    guider = SmoothedEnergyGuidance(
+        guidance_scale=7.5,
+        seg_guidance_scale=2.8,
+        seg_guidance_layers=[7, 8, 9],
+    )
+    assert guider.seg_guidance_config[0].indices == [7]
+    assert guider.seg_guidance_config[1].indices == [8]
+    assert guider.seg_guidance_config[2].indices == [9]
+
+
+def test_seg_prepare_models_increments_count_and_installs_hooks_on_third_pass():
+    guider = SmoothedEnergyGuidance(
+        guidance_scale=7.5,
+        seg_guidance_scale=2.8,
+        seg_guidance_layers=[7],
+    )
+    guider.set_state(step=10, num_inference_steps=50, timestep=torch.tensor([500]))
+
+    denoiser = DummyTransformer(num_blocks=10)
+
+    guider.prepare_models(denoiser)
+    assert guider._count_prepared == 1
+
+    guider.prepare_models(denoiser)
+    assert guider._count_prepared == 2
+
+    with patch("diffusers.guiders.smoothed_energy_guidance._apply_smoothed_energy_guidance_hook") as mock_apply:
+        guider.prepare_models(denoiser)
+        assert guider._count_prepared == 3
+        mock_apply.assert_called_once()

tests/hooks/test_faster_cache.py

@@ -0,0 +1,44 @@
+# Copyright 2025 HuggingFace Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+
+from diffusers.hooks import HookRegistry
+from diffusers.hooks.faster_cache import FasterCacheBlockHook
+
+
+class DummyAttention(torch.nn.Module):
+    def forward(self, hidden_states):
+        return hidden_states * 2.0
+
+
+def test_guidance_distilled_first_forward_in_skip_range_does_not_crash():
+    module = DummyAttention()
+    hook = FasterCacheBlockHook(
+        block_skip_range=2,
+        timestep_skip_range=(0, 1000),
+        is_guidance_distilled=True,
+        weight_callback=lambda _: 0.5,
+        current_timestep_callback=lambda: 500,
+    )
+    registry = HookRegistry.check_if_exists_or_initialize(module)
+    registry.register_hook(hook, "faster_cache_block")
+    hook.initialize_hook(module)
+
+    hidden_states = torch.randn(2, 4)
+    output = module(hidden_states)
+    assert output.shape == hidden_states.shape
+
+    output = module(hidden_states)
+    assert output.shape == hidden_states.shape

utils/check_copies.py

@@ -18,6 +18,7 @@
 import os
 import re
 import subprocess
+import sys
 
 
 # All paths are set with the intent you should run this script from the root of the repo with the command
@@ -94,7 +95,7 @@ def get_indent(code):
 
 
 def run_ruff(code):
-    command = ["ruff", "format", "-", "--config", "pyproject.toml", "--silent"]
+    command = [sys.executable, "-m", "ruff", "format", "-", "--config", "pyproject.toml", "--silent"]
     process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
     stdout, _ = process.communicate(input=code.encode())
     return stdout.decode()