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fix: prevent --cpu flag from allocating GPU memory
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Browse Source 
Two root causes fixed:

1. soft_empty_cache() and synchronize() in model_management.py lacked a
   cpu_state == CPUState.CPU guard. They fell through to torch.cuda calls
   that initialize a CUDA context (150-500MB VRAM) even in CPU-only mode.

2. comfy_kitchen is imported unconditionally at startup via quant_ops.py.
   The import chain triggers torch.cuda.is_available() -> cuInit, which
   initializes the CUDA driver. Now gated behind args.cpu check.

Also adds missing QuantizedLayout and register_layout_op fallback stubs
that were absent from the original ImportError handler.

Amp-Thread-ID: https://ampcode.com/threads/T-019cbd03-433e-7601-93ff-3887227496b4
This commit is contained in:
bymyself 2026-03-05 01:35:58 -08:00
parent 43c64b6308
commit cffeebfa01
1 changed files with 30 additions and 25 deletions
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5
comfy/quant_ops.py
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@ -1,6 +1,10 @@
import torch import torch
import logging import logging
from comfy.cli_args import args
if args.cpu:
_CK_AVAILABLE = False
else:
try: try:
import comfy_kitchen as ck import comfy_kitchen as ck
from comfy_kitchen.tensor import ( from comfy_kitchen.tensor import (
@ -28,6 +32,7 @@ except ImportError as e:
logging.error(f"Failed to import comfy_kitchen, Error: {e}, fp8 and fp4 support will not be available.") logging.error(f"Failed to import comfy_kitchen, Error: {e}, fp8 and fp4 support will not be available.")
_CK_AVAILABLE = False _CK_AVAILABLE = False
if not _CK_AVAILABLE:
class QuantizedTensor: class QuantizedTensor:
pass pass