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main: force cudnn.benchmark to false (#14390)

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Some custom nodes try to set this true globally. It messes with dynamic
VRAM with one-off spikes that can OOM but this is also very high risk
for windows where such allocations might get serviced by shared memory
fallback.

Trump it.
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rattus 2026-06-11 03:54:32 +10:00 committed by GitHub
parent 039ed38ed1
commit 6d18f4adac
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2 changed files with 9 additions and 2 deletions
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6
comfy/model_management.py
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@ -534,8 +534,10 @@ try:
except:
pass
if torch.cuda.is_available() and torch.backends.cudnn.is_available() and PerformanceFeature.AutoTune in args.fast:
torch.backends.cudnn.benchmark = True
def set_cudnn_benchmark():
if torch.cuda.is_available() and torch.backends.cudnn.is_available():
torch.backends.cudnn.benchmark = PerformanceFeature.AutoTune in args.fast
try:
if torch_version_numeric >= (2, 5):

5
main.py
View File

@ -490,6 +490,11 @@ def start_comfyui(asyncio_loop=None):
init_custom_nodes=(not args.disable_all_custom_nodes) or len(args.whitelist_custom_nodes) > 0,
init_api_nodes=not args.disable_api_nodes
))
# Re-apply Comfy's cuDNN benchmark policy after custom-node imports. Benchmark
# mode can request near-card-sized autotune workspaces, and some custom nodes set it at import time.
comfy.model_management.set_cudnn_benchmark()
hook_breaker_ac10a0.restore_functions()
cuda_malloc_warning()