style

src/diffusers/modular_pipelines/flux2/decoders.py

@@ -94,12 +94,10 @@ class Flux2UnpackLatentsStep(ModularPipelineBlocks):
 
         return torch.stack(x_list, dim=0)
 
-
     @torch.no_grad()
     def __call__(self, components, state: PipelineState) -> PipelineState:
         block_state = self.get_block_state(state)
 
-
         latents = block_state.latents
         latent_ids = block_state.latent_ids
 

src/diffusers/modular_pipelines/flux2/denoise.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import inspect
 from typing import Any, List, Tuple
 
 import torch

src/diffusers/modular_pipelines/flux2/encoders.py

@@ -17,9 +17,8 @@ from typing import List, Optional, Tuple, Union
 import torch
 from transformers import AutoProcessor, Mistral3ForConditionalGeneration, Qwen2TokenizerFast, Qwen3ForCausalLM
 
-from ...guiders import ClassifierFreeGuidance
 from ...configuration_utils import FrozenDict
-
+from ...guiders import ClassifierFreeGuidance
 from ...models import AutoencoderKLFlux2
 from ...utils import logging
 from ..modular_pipeline import ModularPipelineBlocks, PipelineState

src/diffusers/modular_pipelines/flux2/modular_blocks_flux2_klein.py

@@ -24,8 +24,8 @@ from .before_denoise import (
 from .decoders import Flux2DecodeStep, Flux2UnpackLatentsStep
 from .denoise import Flux2KleinBaseDenoiseStep, Flux2KleinDenoiseStep
 from .encoders import (
-    Flux2KleinTextEncoderStep,
     Flux2KleinBaseTextEncoderStep,
+    Flux2KleinTextEncoderStep,
     Flux2VaeEncoderStep,
 )
 from .inputs import (
@@ -72,6 +72,7 @@ class Flux2KleinAutoVaeEncoderStep(AutoPipelineBlocks):
             " - If `image` is not provided, step will be skipped."
         )
 
+
 ###
 ### Core denoise
 ###
@@ -142,6 +143,7 @@ class Flux2KleinBaseCoreDenoiseStep(SequentialPipelineBlocks):
             " - `Flux2UnpackLatentsStep` (after_denoise) unpacks the latents from the denoising step.\n"
         )
 
+
 ###
 ### Auto blocks
 ###