seperates out arg parser and imports args

comfy/cli_args.py

+import argparse
+
+parser = argparse.ArgumentParser()
+
+parser.add_argument("--listen", type=str, default="127.0.0.1", help="Listen on IP or 127.0.0.1 if none given so the UI can be accessed from other computers.")
+parser.add_argument("--port", type=int, default=8188, help="Set the listen port.")
+parser.add_argument("--extra-model-paths-config", type=str, default=None, help="Load an extra_model_paths.yaml file.")
+parser.add_argument("--output-directory", type=str, default=None, help="Set the ComfyUI output directory.")
+parser.add_argument("--dont-upcast-attention", action="store_true", help="Disable upcasting of attention. Can boost speed but increase the chances of black images.")
+
+attn_group = parser.add_mutually_exclusive_group()
+attn_group.add_argument("--use-split-cross-attention", action="store_true", help="Use the split cross attention optimization instead of the sub-quadratic one. Ignored when xformers is used.")
+attn_group.add_argument("--use-pytorch-cross-attention", action="store_true", help="Use the new pytorch 2.0 cross attention function.")
+
+parser.add_argument("--disable-xformers", action="store_true", help="Disable xformers.")
+parser.add_argument("--cuda-device", type=int, default=None, help="Set the id of the cuda device this instance will use.")
+
+vram_group = parser.add_mutually_exclusive_group()
+vram_group.add_argument("--highvram", action="store_true", help="By default models will be unloaded to CPU memory after being used. This option keeps them in GPU memory.")
+vram_group.add_argument("--normalvram", action="store_true", help="Used to force normal vram use if lowvram gets automatically enabled.")
+vram_group.add_argument("--lowvram", action="store_true", help="Split the unet in parts to use less vram.")
+vram_group.add_argument("--novram", action="store_true", help="When lowvram isn't enough.")
+vram_group.add_argument("--cpu", action="store_true", help="To use the CPU for everything (slow).")
+
+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.")
+parser.add_argument("--windows-standalone-build", action="store_true", help="Windows standalone build.")
+
+args = parser.parse_args()

comfy/ldm/modules/attention.py

@@ -21,6 +21,8 @@ if model_management.xformers_enabled():
 import os
 _ATTN_PRECISION = os.environ.get("ATTN_PRECISION", "fp32")
 
+from cli_args import args
+
 def exists(val):
     return val is not None
 
@@ -474,7 +476,6 @@ class CrossAttentionPytorch(nn.Module):
 
         return self.to_out(out)
 
-import sys
 if model_management.xformers_enabled():
     print("Using xformers cross attention")
     CrossAttention = MemoryEfficientCrossAttention
@@ -482,7 +483,7 @@ elif model_management.pytorch_attention_enabled():
     print("Using pytorch cross attention")
     CrossAttention = CrossAttentionPytorch
 else:
-    if "--use-split-cross-attention" in sys.argv:
+    if args.use_split_cross_attention:
         print("Using split optimization for cross attention")
         CrossAttention = CrossAttentionDoggettx
     else:

comfy/model_management.py

+import psutil
+from enum import Enum
+from cli_args import args
 
-CPU = 0
-NO_VRAM = 1
-LOW_VRAM = 2
-NORMAL_VRAM = 3
-HIGH_VRAM = 4
-MPS = 5
+class VRAMState(Enum):
+    CPU = 0
+    NO_VRAM = 1
+    LOW_VRAM = 2
+    NORMAL_VRAM = 3
+    HIGH_VRAM = 4
+    MPS = 5
 
-accelerate_enabled = False
-vram_state = NORMAL_VRAM
+# Determine VRAM State
+vram_state = VRAMState.NORMAL_VRAM
+set_vram_to = VRAMState.NORMAL_VRAM
 
 total_vram = 0
 total_vram_available_mb = -1
 
-import sys
-import psutil
-
-forced_cpu = "--cpu" in sys.argv
-
-set_vram_to = NORMAL_VRAM
+accelerate_enabled = False
 
 try:
     import torch
     total_vram = torch.cuda.mem_get_info(torch.cuda.current_device())[1] / (1024 * 1024)
     total_ram = psutil.virtual_memory().total / (1024 * 1024)
-    forced_normal_vram = "--normalvram" in sys.argv
-    if not forced_normal_vram and not forced_cpu:
+    if not args.normalvram and not args.cpu:
         if total_vram <= 4096:
             print("Trying to enable lowvram mode because your GPU seems to have 4GB or less. If you don't want this use: --normalvram")
-            set_vram_to = LOW_VRAM
+            set_vram_to = VRAMState.LOW_VRAM
         elif total_vram > total_ram * 1.1 and total_vram > 14336:
             print("Enabling highvram mode because your GPU has more vram than your computer has ram. If you don't want this use: --normalvram")
-            vram_state = HIGH_VRAM
+            vram_state = VRAMState.HIGH_VRAM
 except:
     pass
 
@@ -39,34 +38,32 @@ try:
 except:
     OOM_EXCEPTION = Exception
 
-if "--disable-xformers" in sys.argv:
-    XFORMERS_IS_AVAILBLE = False
+if args.disable_xformers:
+    XFORMERS_IS_AVAILABLE = False
 else:
     try:
         import xformers
         import xformers.ops
-        XFORMERS_IS_AVAILBLE = True
+        XFORMERS_IS_AVAILABLE = True
     except:
-        XFORMERS_IS_AVAILBLE = False
+        XFORMERS_IS_AVAILABLE = False
 
-ENABLE_PYTORCH_ATTENTION = False
-if "--use-pytorch-cross-attention" in sys.argv:
+ENABLE_PYTORCH_ATTENTION = args.use_pytorch_cross_attention
+if ENABLE_PYTORCH_ATTENTION:
     torch.backends.cuda.enable_math_sdp(True)
     torch.backends.cuda.enable_flash_sdp(True)
     torch.backends.cuda.enable_mem_efficient_sdp(True)
-    ENABLE_PYTORCH_ATTENTION = True
-    XFORMERS_IS_AVAILBLE = False
-
+    XFORMERS_IS_AVAILABLE = False
 
-if "--lowvram" in sys.argv:
-    set_vram_to = LOW_VRAM
-if "--novram" in sys.argv:
-    set_vram_to = NO_VRAM
-if "--highvram" in sys.argv:
-    vram_state = HIGH_VRAM
+if args.lowvram:
+    set_vram_to = VRAMState.LOW_VRAM
+elif args.novram:
+    set_vram_to = VRAMState.NO_VRAM
+elif args.highvram:
+    vram_state = VRAMState.HIGH_VRAM
 
 
-if set_vram_to == LOW_VRAM or set_vram_to == NO_VRAM:
+if set_vram_to in (VRAMState.LOW_VRAM, VRAMState.NO_VRAM):
     try:
         import accelerate
         accelerate_enabled = True
@@ -81,14 +78,14 @@ if set_vram_to == LOW_VRAM or set_vram_to == NO_VRAM:
 
 try:
     if torch.backends.mps.is_available():
-        vram_state = MPS
+        vram_state = VRAMState.MPS
 except:
     pass
 
-if forced_cpu:
-    vram_state = CPU
+if args.cpu:
+    vram_state = VRAMState.CPU
 
-print("Set vram state to:", ["CPU", "NO VRAM", "LOW VRAM", "NORMAL VRAM", "HIGH VRAM", "MPS"][vram_state])
+print(f"Set vram state to: {vram_state.name}")
 
 
 current_loaded_model = None
@@ -109,12 +106,12 @@ def unload_model():
             model_accelerated = False
 
         #never unload models from GPU on high vram
-        if vram_state != HIGH_VRAM:
+        if vram_state != VRAMState.HIGH_VRAM:
             current_loaded_model.model.cpu()
         current_loaded_model.unpatch_model()
         current_loaded_model = None
 
-    if vram_state != HIGH_VRAM:
+    if vram_state != VRAMState.HIGH_VRAM:
         if len(current_gpu_controlnets) > 0:
             for n in current_gpu_controlnets:
                 n.cpu()
@@ -135,19 +132,19 @@ def load_model_gpu(model):
         model.unpatch_model()
         raise e
     current_loaded_model = model
-    if vram_state == CPU:
+    if vram_state == VRAMState.CPU:
         pass
-    elif vram_state == MPS:
+    elif vram_state == VRAMState.MPS:
         mps_device = torch.device("mps")
         real_model.to(mps_device)
         pass
-    elif vram_state == NORMAL_VRAM or vram_state == HIGH_VRAM:
+    elif vram_state == VRAMState.NORMAL_VRAM or vram_state == VRAMState.HIGH_VRAM:
         model_accelerated = False
         real_model.cuda()
     else:
-        if vram_state == NO_VRAM:
+        if vram_state == VRAMState.NO_VRAM:
             device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "256MiB", "cpu": "16GiB"})
-        elif vram_state == LOW_VRAM:
+        elif vram_state == VRAMState.LOW_VRAM:
             device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "{}MiB".format(total_vram_available_mb), "cpu": "16GiB"})
 
         accelerate.dispatch_model(real_model, device_map=device_map, main_device="cuda")
@@ -157,10 +154,10 @@ def load_model_gpu(model):
 def load_controlnet_gpu(models):
     global current_gpu_controlnets
     global vram_state
-    if vram_state == CPU:
+    if vram_state == VRAMState.CPU:
         return
 
-    if vram_state == LOW_VRAM or vram_state == NO_VRAM:
+    if vram_state == VRAMState.LOW_VRAM or vram_state == VRAMState.NO_VRAM:
         #don't load controlnets like this if low vram because they will be loaded right before running and unloaded right after
         return
 
@@ -176,20 +173,20 @@ def load_controlnet_gpu(models):
 
 def load_if_low_vram(model):
     global vram_state
-    if vram_state == LOW_VRAM or vram_state == NO_VRAM:
+    if vram_state == VRAMState.LOW_VRAM or vram_state == VRAMState.NO_VRAM:
         return model.cuda()
     return model
 
 def unload_if_low_vram(model):
     global vram_state
-    if vram_state == LOW_VRAM or vram_state == NO_VRAM:
+    if vram_state == VRAMState.LOW_VRAM or vram_state == VRAMState.NO_VRAM:
         return model.cpu()
     return model
 
 def get_torch_device():
-    if vram_state == MPS:
+    if vram_state == VRAMState.MPS:
         return torch.device("mps")
-    if vram_state == CPU:
+    if vram_state == VRAMState.CPU:
         return torch.device("cpu")
     else:
         return torch.cuda.current_device()
@@ -201,9 +198,9 @@ def get_autocast_device(dev):
 
 
 def xformers_enabled():
-    if vram_state == CPU:
+    if vram_state == VRAMState.CPU:
         return False
-    return XFORMERS_IS_AVAILBLE
+    return XFORMERS_IS_AVAILABLE
 
 
 def xformers_enabled_vae():
@@ -243,7 +240,7 @@ def get_free_memory(dev=None, torch_free_too=False):
 
 def maximum_batch_area():
     global vram_state
-    if vram_state == NO_VRAM:
+    if vram_state == VRAMState.NO_VRAM:
         return 0
 
     memory_free = get_free_memory() / (1024 * 1024)
@@ -252,11 +249,11 @@ def maximum_batch_area():
 
 def cpu_mode():
     global vram_state
-    return vram_state == CPU
+    return vram_state == VRAMState.CPU
 
 def mps_mode():
     global vram_state
-    return vram_state == MPS
+    return vram_state == VRAMState.MPS
 
 def should_use_fp16():
     if cpu_mode() or mps_mode():

main.py

-import argparse
 import asyncio
 import os
 import shutil
-import sys
 import threading
+from comfy.cli_args import args
 
 if os.name == "nt":
     import logging
     logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Script Arguments")
-
-    parser.add_argument("--listen", type=str, default="127.0.0.1", help="Listen on IP or 0.0.0.0 if none given so the UI can be accessed from other computers.")
-    parser.add_argument("--port", type=int, default=8188, help="Set the listen port.")
-    parser.add_argument("--extra-model-paths-config", type=str, default=None, help="Load an extra_model_paths.yaml file.")
-    parser.add_argument("--output-directory", type=str, default=None, help="Set the ComfyUI output directory.")
-    parser.add_argument("--dont-upcast-attention", action="store_true", help="Disable upcasting of attention. Can boost speed but increase the chances of black images.")
-    parser.add_argument("--use-split-cross-attention", action="store_true", help="Use the split cross attention optimization instead of the sub-quadratic one. Ignored when xformers is used.")
-    parser.add_argument("--use-pytorch-cross-attention", action="store_true", help="Use the new pytorch 2.0 cross attention function.")
-    parser.add_argument("--disable-xformers", action="store_true", help="Disable xformers.")
-    parser.add_argument("--cuda-device", type=int, default=None, help="Set the id of the cuda device this instance will use.")
-    parser.add_argument("--highvram", action="store_true", help="By default models will be unloaded to CPU memory after being used. This option keeps them in GPU memory.")
-    parser.add_argument("--normalvram", action="store_true", help="Used to force normal vram use if lowvram gets automatically enabled.")
-    parser.add_argument("--lowvram", action="store_true", help="Split the unet in parts to use less vram.")
-    parser.add_argument("--novram", action="store_true", help="When lowvram isn't enough.")
-    parser.add_argument("--cpu", action="store_true", help="To use the CPU for everything (slow).")
-    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.")
-    parser.add_argument("--windows-standalone-build", action="store_true", help="Windows standalone build.")
-
-    args = parser.parse_args()
-
     if args.dont_upcast_attention:
         print("disabling upcasting of attention")
         os.environ['ATTN_PRECISION'] = "fp16"
@@ -121,7 +98,7 @@ if __name__ == "__main__":
 
     if args.output_directory:
         output_dir = os.path.abspath(args.output_directory)
-        print("setting output directory to:", output_dir)
+        print(f"Setting output directory to: {output_dir}")
         folder_paths.set_output_directory(output_dir)
 
     port = args.port