298977887/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2025-03-15 05:57:20 +00:00
Code Issues Packages Projects Releases Wiki Activity

--fast now takes a number as argument to indicate how fast you want it.

Browse Source 
The idea is that you can indicate how much quality vs speed you want.

At the moment:

--fast 2 enables fp16 accumulation if your pytorch supports it.
--fast 5 enables fp8 matrix mult on fp8 models and the optimization above.

--fast without a number enables all optimizations.
This commit is contained in:
comfyanonymous 2025-02-28 02:48:20 -05:00
parent eb4543474b
commit cf0b549d48
3 changed files with 4 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
comfy/cli_args.py
View File

@ -130,7 +130,7 @@ parser.add_argument("--default-hashing-function", type=str, choices=['md5', 'sha
parser.add_argument("--disable-smart-memory", action="store_true", help="Force ComfyUI to agressively offload to regular ram instead of keeping models in vram when it can.")
parser.add_argument("--deterministic", action="store_true", help="Make pytorch use slower deterministic algorithms when it can. Note that this might not make images deterministic in all cases.")
parser.add_argument("--fast", action="store_true", help="Enable some untested and potentially quality deteriorating optimizations.")
parser.add_argument("--fast", metavar="number", type=int, const=99, default=0, nargs="?", help="Enable some untested and potentially quality deteriorating optimizations. You can pass a number from 0 to 10 for a bigger speed vs quality tradeoff. Using --fast with no number means maximum speed. 2 or larger enables fp16 accumulation, 5 or larger enables fp8 matrix multiplication.")
parser.add_argument("--dont-print-server", action="store_true", help="Don't print server output.")
parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI.")

3
comfy/model_management.py
View File

@ -280,9 +280,10 @@ if ENABLE_PYTORCH_ATTENTION:
PRIORITIZE_FP16 = False # TODO: remove and replace with something that shows exactly which dtype is faster than the other
try:
if is_nvidia() and args.fast:
if is_nvidia() and args.fast >= 2:
torch.backends.cuda.matmul.allow_fp16_accumulation = True
PRIORITIZE_FP16 = True # TODO: limit to cards where it actually boosts performance
logging.info("Enabled fp16 accumulation.")
except:
pass

2
comfy/ops.py
View File

@ -360,7 +360,7 @@ def pick_operations(weight_dtype, compute_dtype, load_device=None, disable_fast_
if scaled_fp8 is not None:
return scaled_fp8_ops(fp8_matrix_mult=fp8_compute, scale_input=True, override_dtype=scaled_fp8)
if fp8_compute and (fp8_optimizations or args.fast) and not disable_fast_fp8:
if fp8_compute and (fp8_optimizations or args.fast >= 5) and not disable_fast_fp8:
return fp8_ops
if compute_dtype is None or weight_dtype == compute_dtype: