wangbo/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2026-05-06 15:22:31 +08:00
Code Issues Actions 27 Packages Projects Releases Wiki Activity

fix: resolve ruff linting errors in nodes_inference_scaling

Browse Source 
- Remove unused imports: Optional, Callable, Dict, PIL.Image, traceback
- Remove trailing whitespace on blank lines (W293)
- Remove unused local variable: device
This commit is contained in:
unknown 2026-04-18 15:31:56 +09:00
parent 74442533da
commit c5ce3e1375
1 changed files with 47 additions and 49 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
comfy_api_nodes/nodes_inference_scaling.py
View File

@ -6,12 +6,11 @@ The system monitors image quality during the generation loop and adjusts samplin
parameters dynamically based on quality metrics. parameters dynamically based on quality metrics.
""" """
from typing import Optional, Callable, Dict, Any from typing import Any
from typing_extensions import override from typing_extensions import override
from inspect import cleandoc from inspect import cleandoc
import torch import torch
import numpy as np import numpy as np
from PIL import Image
from comfy_api.latest import IO, ComfyExtension from comfy_api.latest import IO, ComfyExtension
from comfy.samplers import KSampler from comfy.samplers import KSampler
@ -304,7 +303,7 @@ class InferenceScalingNode(IO.ComfyNode):
verifier = mod._verifier_registry[verifier_id] verifier = mod._verifier_registry[verifier_id]
# Prepare sampling parameters # Prepare sampling parameters
device = model_management.get_torch_device() model_management.get_torch_device()
# Extract latent_image tensor from dict # Extract latent_image tensor from dict
latent_image_tensor = latent_image["samples"] latent_image_tensor = latent_image["samples"]
@ -379,7 +378,6 @@ class InferenceScalingNode(IO.ComfyNode):
except Exception as e: except Exception as e:
# If decoding fails, continue sampling (don't break the generation) # If decoding fails, continue sampling (don't break the generation)
import logging import logging
import traceback
logging.warning(f"Inference Scaling: Quality check failed at step {step}: {e}") logging.warning(f"Inference Scaling: Quality check failed at step {step}: {e}")
# Don't log full traceback in production to avoid spam # Don't log full traceback in production to avoid spam
# logging.debug(traceback.format_exc()) # logging.debug(traceback.format_exc())