Use enum list for --fast options (#7024)

comfy/cli_args.py

@@ -130,7 +130,12 @@ 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", 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.")
+
+class PerformanceFeature(enum.Enum):
+    Fp16Accumulation = "fp16_accumulation"
+    Fp8Optimization = "fp8_optimization"
+
+parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations.")
 
 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.")
@@ -194,3 +199,14 @@ if args.disable_auto_launch:
 
 if args.force_fp16:
     args.fp16_unet = True
+
+
+# '--fast' is not provided, use an empty set
+if args.fast is None:
+    args.fast = set()
+# '--fast' is provided with an empty list, enable all optimizations
+elif args.fast == []:
+    args.fast = set(PerformanceFeature)
+# '--fast' is provided with a list of performance features, use that list
+else:
+    args.fast = set(args.fast)

comfy/model_management.py

@@ -19,7 +19,7 @@
 import psutil
 import logging
 from enum import Enum
-from comfy.cli_args import args
+from comfy.cli_args import args, PerformanceFeature
 import torch
 import sys
 import platform
@@ -280,7 +280,7 @@ 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 >= 2:
+    if is_nvidia() and PerformanceFeature.Fp16Accumulation in args.fast:
         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.")

comfy/ops.py

@@ -18,7 +18,7 @@
 
 import torch
 import comfy.model_management
-from comfy.cli_args import args
+from comfy.cli_args import args, PerformanceFeature
 import comfy.float
 
 cast_to = comfy.model_management.cast_to #TODO: remove once no more references
@@ -360,7 +360,11 @@ 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 >= 5) and not disable_fast_fp8:
+    if (
+        fp8_compute and
+        (fp8_optimizations or PerformanceFeature.Fp8Optimization in args.fast) and
+        not disable_fast_fp8
+    ):
         return fp8_ops
 
     if compute_dtype is None or weight_dtype == compute_dtype: