mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2025-01-11 10:25:16 +00:00
Merge branch 'master' into ipex
This commit is contained in:
藍+85CD
GitHub
commit
05eeaa2de5
30
comfy/cli_args.py
Normal file
30
comfy/cli_args.py
Normal file
@ -0,0 +1,30 @@
|
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument("--listen", nargs="?", const="0.0.0.0", default="127.0.0.1", type=str, help="Specify the IP address to listen on (default: 127.0.0.1). If --listen is provided without an argument, it defaults to 0.0.0.0. (listens on all)")
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parser.add_argument("--port", type=int, default=8188, help="Set the listen port.")
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parser.add_argument("--enable-cors-header", default=None, nargs="?", const="*", help="Enable CORS (Cross-Origin Resource Sharing) with optional origin or allow all with default '*'.")
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parser.add_argument("--extra-model-paths-config", type=str, default=None, help="Load an extra_model_paths.yaml file.")
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parser.add_argument("--output-directory", type=str, default=None, help="Set the ComfyUI output directory.")
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parser.add_argument("--cuda-device", type=int, default=None, help="Set the id of the cuda device this instance will use.")
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parser.add_argument("--dont-upcast-attention", action="store_true", help="Disable upcasting of attention. Can boost speed but increase the chances of black images.")
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attn_group = parser.add_mutually_exclusive_group()
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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.")
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attn_group.add_argument("--use-pytorch-cross-attention", action="store_true", help="Use the new pytorch 2.0 cross attention function.")
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parser.add_argument("--disable-xformers", action="store_true", help="Disable xformers.")
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vram_group = parser.add_mutually_exclusive_group()
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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.")
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vram_group.add_argument("--normalvram", action="store_true", help="Used to force normal vram use if lowvram gets automatically enabled.")
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vram_group.add_argument("--lowvram", action="store_true", help="Split the unet in parts to use less vram.")
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vram_group.add_argument("--novram", action="store_true", help="When lowvram isn't enough.")
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vram_group.add_argument("--cpu", action="store_true", help="To use the CPU for everything (slow).")
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parser.add_argument("--dont-print-server", action="store_true", help="Don't print server output.")
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parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI.")
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parser.add_argument("--windows-standalone-build", action="store_true", help="Windows standalone build.")
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args = parser.parse_args()
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@ -21,6 +21,8 @@ if model_management.xformers_enabled():
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import os
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_ATTN_PRECISION = os.environ.get("ATTN_PRECISION", "fp32")
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from cli_args import args
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def exists(val):
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return val is not None
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@ -474,7 +476,6 @@ class CrossAttentionPytorch(nn.Module):
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return self.to_out(out)
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import sys
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if model_management.xformers_enabled():
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print("Using xformers cross attention")
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CrossAttention = MemoryEfficientCrossAttention
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@ -482,7 +483,7 @@ elif model_management.pytorch_attention_enabled():
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print("Using pytorch cross attention")
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CrossAttention = CrossAttentionPytorch
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else:
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if "--use-split-cross-attention" in sys.argv:
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if args.use_split_cross_attention:
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print("Using split optimization for cross attention")
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CrossAttention = CrossAttentionDoggettx
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else:
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@ -1,4 +1,8 @@
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import psutil
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from enum import Enum
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from cli_args import args
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class VRAMState(Enum):
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CPU = 0
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NO_VRAM = 1
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LOW_VRAM = 2
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@ -6,19 +10,15 @@ NORMAL_VRAM = 3
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HIGH_VRAM = 4
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MPS = 5
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accelerate_enabled = False
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xpu_available = False
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vram_state = NORMAL_VRAM
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# Determine VRAM State
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vram_state = VRAMState.NORMAL_VRAM
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set_vram_to = VRAMState.NORMAL_VRAM
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total_vram = 0
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total_vram_available_mb = -1
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import sys
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import psutil
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forced_cpu = "--cpu" in sys.argv
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set_vram_to = NORMAL_VRAM
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accelerate_enabled = False
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xpu_available = False
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try:
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import torch
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@ -30,14 +30,13 @@ try:
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except:
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total_vram = torch.cuda.mem_get_info(torch.cuda.current_device())[1] / (1024 * 1024)
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total_ram = psutil.virtual_memory().total / (1024 * 1024)
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forced_normal_vram = "--normalvram" in sys.argv
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if not forced_normal_vram and not forced_cpu:
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if not args.normalvram and not args.cpu:
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if total_vram <= 4096:
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print("Trying to enable lowvram mode because your GPU seems to have 4GB or less. If you don't want this use: --normalvram")
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set_vram_to = LOW_VRAM
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set_vram_to = VRAMState.LOW_VRAM
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elif total_vram > total_ram * 1.1 and total_vram > 14336:
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print("Enabling highvram mode because your GPU has more vram than your computer has ram. If you don't want this use: --normalvram")
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vram_state = HIGH_VRAM
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vram_state = VRAMState.HIGH_VRAM
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except:
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pass
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@ -46,34 +45,32 @@ try:
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except:
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OOM_EXCEPTION = Exception
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if "--disable-xformers" in sys.argv:
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XFORMERS_IS_AVAILBLE = False
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if args.disable_xformers:
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XFORMERS_IS_AVAILABLE = False
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else:
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try:
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import xformers
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import xformers.ops
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XFORMERS_IS_AVAILBLE = True
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XFORMERS_IS_AVAILABLE = True
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except:
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XFORMERS_IS_AVAILBLE = False
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XFORMERS_IS_AVAILABLE = False
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ENABLE_PYTORCH_ATTENTION = False
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if "--use-pytorch-cross-attention" in sys.argv:
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ENABLE_PYTORCH_ATTENTION = args.use_pytorch_cross_attention
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if ENABLE_PYTORCH_ATTENTION:
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torch.backends.cuda.enable_math_sdp(True)
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torch.backends.cuda.enable_flash_sdp(True)
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torch.backends.cuda.enable_mem_efficient_sdp(True)
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ENABLE_PYTORCH_ATTENTION = True
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XFORMERS_IS_AVAILBLE = False
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XFORMERS_IS_AVAILABLE = False
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if args.lowvram:
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set_vram_to = VRAMState.LOW_VRAM
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elif args.novram:
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set_vram_to = VRAMState.NO_VRAM
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elif args.highvram:
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vram_state = VRAMState.HIGH_VRAM
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if "--lowvram" in sys.argv:
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set_vram_to = LOW_VRAM
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if "--novram" in sys.argv:
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set_vram_to = NO_VRAM
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if "--highvram" in sys.argv:
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vram_state = HIGH_VRAM
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if set_vram_to == LOW_VRAM or set_vram_to == NO_VRAM:
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if set_vram_to in (VRAMState.LOW_VRAM, VRAMState.NO_VRAM):
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try:
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import accelerate
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accelerate_enabled = True
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@ -88,14 +85,14 @@ if set_vram_to == LOW_VRAM or set_vram_to == NO_VRAM:
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try:
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if torch.backends.mps.is_available():
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vram_state = MPS
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vram_state = VRAMState.MPS
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except:
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pass
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if forced_cpu:
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vram_state = CPU
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if args.cpu:
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vram_state = VRAMState.CPU
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print("Set vram state to:", ["CPU", "NO VRAM", "LOW VRAM", "NORMAL VRAM", "HIGH VRAM", "MPS"][vram_state])
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print(f"Set vram state to: {vram_state.name}")
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current_loaded_model = None
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@ -116,12 +113,12 @@ def unload_model():
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model_accelerated = False
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#never unload models from GPU on high vram
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if vram_state != HIGH_VRAM:
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if vram_state != VRAMState.HIGH_VRAM:
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current_loaded_model.model.cpu()
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current_loaded_model.unpatch_model()
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current_loaded_model = None
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if vram_state != HIGH_VRAM:
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if vram_state != VRAMState.HIGH_VRAM:
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if len(current_gpu_controlnets) > 0:
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for n in current_gpu_controlnets:
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n.cpu()
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@ -143,22 +140,22 @@ def load_model_gpu(model):
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model.unpatch_model()
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raise e
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current_loaded_model = model
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if vram_state == CPU:
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if vram_state == VRAMState.CPU:
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pass
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elif vram_state == MPS:
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elif vram_state == VRAMState.MPS:
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mps_device = torch.device("mps")
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real_model.to(mps_device)
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pass
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elif vram_state == NORMAL_VRAM or vram_state == HIGH_VRAM:
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elif vram_state == VRAMState.NORMAL_VRAM or vram_state == VRAMState.HIGH_VRAM:
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model_accelerated = False
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if xpu_available:
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real_model.to("xpu")
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else:
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real_model.cuda()
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else:
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if vram_state == NO_VRAM:
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if vram_state == VRAMState.NO_VRAM:
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device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "256MiB", "cpu": "16GiB"})
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elif vram_state == LOW_VRAM:
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elif vram_state == VRAMState.LOW_VRAM:
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device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "{}MiB".format(total_vram_available_mb), "cpu": "16GiB"})
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accelerate.dispatch_model(real_model, device_map=device_map, main_device="xpu" if xpu_available else "cuda")
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@ -168,10 +165,10 @@ def load_model_gpu(model):
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def load_controlnet_gpu(models):
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global current_gpu_controlnets
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global vram_state
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if vram_state == CPU:
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if vram_state == VRAMState.CPU:
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return
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if vram_state == LOW_VRAM or vram_state == NO_VRAM:
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if vram_state == VRAMState.LOW_VRAM or vram_state == VRAMState.NO_VRAM:
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#don't load controlnets like this if low vram because they will be loaded right before running and unloaded right after
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return
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@ -188,7 +185,7 @@ def load_controlnet_gpu(models):
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def load_if_low_vram(model):
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global vram_state
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global xpu_available
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if vram_state == LOW_VRAM or vram_state == NO_VRAM:
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if vram_state == VRAMState.LOW_VRAM or vram_state == VRAMState.NO_VRAM:
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if xpu_available:
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return model.to("xpu")
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else:
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@ -197,15 +194,15 @@ def load_if_low_vram(model):
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def unload_if_low_vram(model):
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global vram_state
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if vram_state == LOW_VRAM or vram_state == NO_VRAM:
|
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if vram_state == VRAMState.LOW_VRAM or vram_state == VRAMState.NO_VRAM:
|
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return model.cpu()
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return model
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|
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def get_torch_device():
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global xpu_available
|
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if vram_state == MPS:
|
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if vram_state == VRAMState.MPS:
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return torch.device("mps")
|
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if vram_state == CPU:
|
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if vram_state == VRAMState.CPU:
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return torch.device("cpu")
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else:
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if xpu_available:
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@ -220,9 +217,9 @@ def get_autocast_device(dev):
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def xformers_enabled():
|
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if vram_state == CPU:
|
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if vram_state == VRAMState.CPU:
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return False
|
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return XFORMERS_IS_AVAILBLE
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return XFORMERS_IS_AVAILABLE
|
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|
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def xformers_enabled_vae():
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@ -267,7 +264,7 @@ def get_free_memory(dev=None, torch_free_too=False):
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def maximum_batch_area():
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global vram_state
|
||||
if vram_state == NO_VRAM:
|
||||
if vram_state == VRAMState.NO_VRAM:
|
||||
return 0
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||||
|
||||
memory_free = get_free_memory() / (1024 * 1024)
|
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@ -276,11 +273,11 @@ def maximum_batch_area():
|
||||
|
||||
def cpu_mode():
|
||||
global vram_state
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||||
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():
|
||||
global xpu_available
|
||||
|
||||
@ -27,6 +27,40 @@ folder_names_and_paths["embeddings"] = ([os.path.join(models_dir, "embeddings")]
|
||||
folder_names_and_paths["controlnet"] = ([os.path.join(models_dir, "controlnet"), os.path.join(models_dir, "t2i_adapter")], supported_pt_extensions)
|
||||
folder_names_and_paths["upscale_models"] = ([os.path.join(models_dir, "upscale_models")], supported_pt_extensions)
|
||||
|
||||
output_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), "output")
|
||||
temp_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), "temp")
|
||||
input_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), "input")
|
||||
|
||||
if not os.path.exists(input_directory):
|
||||
os.makedirs(input_directory)
|
||||
|
||||
def set_output_directory(output_dir):
|
||||
global output_directory
|
||||
output_directory = output_dir
|
||||
|
||||
def get_output_directory():
|
||||
global output_directory
|
||||
return output_directory
|
||||
|
||||
def get_temp_directory():
|
||||
global temp_directory
|
||||
return temp_directory
|
||||
|
||||
def get_input_directory():
|
||||
global input_directory
|
||||
return input_directory
|
||||
|
||||
|
||||
#NOTE: used in http server so don't put folders that should not be accessed remotely
|
||||
def get_directory_by_type(type_name):
|
||||
if type_name == "output":
|
||||
return get_output_directory()
|
||||
if type_name == "temp":
|
||||
return get_temp_directory()
|
||||
if type_name == "input":
|
||||
return get_input_directory()
|
||||
return None
|
||||
|
||||
|
||||
def add_model_folder_path(folder_name, full_folder_path):
|
||||
global folder_names_and_paths
|
||||
|
||||
94
main.py
94
main.py
@ -1,56 +1,31 @@
|
||||
import os
|
||||
import sys
|
||||
import shutil
|
||||
|
||||
import threading
|
||||
import asyncio
|
||||
import os
|
||||
import shutil
|
||||
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__":
|
||||
if '--help' in sys.argv:
|
||||
print()
|
||||
print("Valid Command line Arguments:")
|
||||
print("\t--listen [ip]\t\t\tListen on ip or 0.0.0.0 if none given so the UI can be accessed from other computers.")
|
||||
print("\t--port 8188\t\t\tSet the listen port.")
|
||||
print()
|
||||
print("\t--extra-model-paths-config file.yaml\tload an extra_model_paths.yaml file.")
|
||||
print()
|
||||
print()
|
||||
print("\t--dont-upcast-attention\t\tDisable upcasting of attention \n\t\t\t\t\tcan boost speed but increase the chances of black images.\n")
|
||||
print("\t--use-split-cross-attention\tUse the split cross attention optimization instead of the sub-quadratic one.\n\t\t\t\t\tIgnored when xformers is used.")
|
||||
print("\t--use-pytorch-cross-attention\tUse the new pytorch 2.0 cross attention function.")
|
||||
print("\t--disable-xformers\t\tdisables xformers")
|
||||
print("\t--cuda-device 1\t\tSet the id of the cuda device this instance will use.")
|
||||
print()
|
||||
print("\t--highvram\t\t\tBy default models will be unloaded to CPU memory after being used.\n\t\t\t\t\tThis option keeps them in GPU memory.\n")
|
||||
print("\t--normalvram\t\t\tUsed to force normal vram use if lowvram gets automatically enabled.")
|
||||
print("\t--lowvram\t\t\tSplit the unet in parts to use less vram.")
|
||||
print("\t--novram\t\t\tWhen lowvram isn't enough.")
|
||||
print()
|
||||
print("\t--cpu\t\t\tTo use the CPU for everything (slow).")
|
||||
exit()
|
||||
|
||||
if '--dont-upcast-attention' in sys.argv:
|
||||
if args.dont_upcast_attention:
|
||||
print("disabling upcasting of attention")
|
||||
os.environ['ATTN_PRECISION'] = "fp16"
|
||||
|
||||
try:
|
||||
index = sys.argv.index('--cuda-device')
|
||||
device = sys.argv[index + 1]
|
||||
os.environ['CUDA_VISIBLE_DEVICES'] = device
|
||||
print("Set cuda device to:", device)
|
||||
except:
|
||||
pass
|
||||
if args.cuda_device is not None:
|
||||
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
|
||||
print("Set cuda device to:", args.cuda_device)
|
||||
|
||||
|
||||
from nodes import init_custom_nodes
|
||||
import execution
|
||||
import server
|
||||
import folder_paths
|
||||
import yaml
|
||||
|
||||
import execution
|
||||
import folder_paths
|
||||
import server
|
||||
from nodes import init_custom_nodes
|
||||
|
||||
|
||||
def prompt_worker(q, server):
|
||||
e = execution.PromptExecutor(server)
|
||||
while True:
|
||||
@ -109,43 +84,30 @@ if __name__ == "__main__":
|
||||
hijack_progress(server)
|
||||
|
||||
threading.Thread(target=prompt_worker, daemon=True, args=(q,server,)).start()
|
||||
try:
|
||||
address = '0.0.0.0'
|
||||
p_index = sys.argv.index('--listen')
|
||||
try:
|
||||
ip = sys.argv[p_index + 1]
|
||||
if ip[:2] != '--':
|
||||
address = ip
|
||||
except:
|
||||
pass
|
||||
except:
|
||||
address = '127.0.0.1'
|
||||
|
||||
dont_print = False
|
||||
if '--dont-print-server' in sys.argv:
|
||||
dont_print = True
|
||||
address = args.listen
|
||||
|
||||
dont_print = args.dont_print_server
|
||||
|
||||
extra_model_paths_config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "extra_model_paths.yaml")
|
||||
if os.path.isfile(extra_model_paths_config_path):
|
||||
load_extra_path_config(extra_model_paths_config_path)
|
||||
|
||||
if '--extra-model-paths-config' in sys.argv:
|
||||
indices = [(i + 1) for i in range(len(sys.argv) - 1) if sys.argv[i] == '--extra-model-paths-config']
|
||||
for i in indices:
|
||||
load_extra_path_config(sys.argv[i])
|
||||
if args.extra_model_paths_config:
|
||||
load_extra_path_config(args.extra_model_paths_config)
|
||||
|
||||
port = 8188
|
||||
try:
|
||||
p_index = sys.argv.index('--port')
|
||||
port = int(sys.argv[p_index + 1])
|
||||
except:
|
||||
pass
|
||||
if args.output_directory:
|
||||
output_dir = os.path.abspath(args.output_directory)
|
||||
print(f"Setting output directory to: {output_dir}")
|
||||
folder_paths.set_output_directory(output_dir)
|
||||
|
||||
if '--quick-test-for-ci' in sys.argv:
|
||||
port = args.port
|
||||
|
||||
if args.quick_test_for_ci:
|
||||
exit(0)
|
||||
|
||||
call_on_start = None
|
||||
if "--windows-standalone-build" in sys.argv:
|
||||
if args.windows_standalone_build:
|
||||
def startup_server(address, port):
|
||||
import webbrowser
|
||||
webbrowser.open("http://{}:{}".format(address, port))
|
||||
|
||||
29
nodes.py
29
nodes.py
@ -777,7 +777,7 @@ class KSamplerAdvanced:
|
||||
|
||||
class SaveImage:
|
||||
def __init__(self):
|
||||
self.output_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "output")
|
||||
self.output_dir = folder_paths.get_output_directory()
|
||||
self.type = "output"
|
||||
|
||||
@classmethod
|
||||
@ -829,9 +829,6 @@ class SaveImage:
|
||||
os.makedirs(full_output_folder, exist_ok=True)
|
||||
counter = 1
|
||||
|
||||
if not os.path.exists(self.output_dir):
|
||||
os.makedirs(self.output_dir)
|
||||
|
||||
results = list()
|
||||
for image in images:
|
||||
i = 255. * image.cpu().numpy()
|
||||
@ -856,7 +853,7 @@ class SaveImage:
|
||||
|
||||
class PreviewImage(SaveImage):
|
||||
def __init__(self):
|
||||
self.output_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "temp")
|
||||
self.output_dir = folder_paths.get_temp_directory()
|
||||
self.type = "temp"
|
||||
|
||||
@classmethod
|
||||
@ -867,13 +864,11 @@ class PreviewImage(SaveImage):
|
||||
}
|
||||
|
||||
class LoadImage:
|
||||
input_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "input")
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
if not os.path.exists(s.input_dir):
|
||||
os.makedirs(s.input_dir)
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
return {"required":
|
||||
{"image": (sorted(os.listdir(s.input_dir)), )},
|
||||
{"image": (sorted(os.listdir(input_dir)), )},
|
||||
}
|
||||
|
||||
CATEGORY = "image"
|
||||
@ -881,7 +876,8 @@ class LoadImage:
|
||||
RETURN_TYPES = ("IMAGE", "MASK")
|
||||
FUNCTION = "load_image"
|
||||
def load_image(self, image):
|
||||
image_path = os.path.join(self.input_dir, image)
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
image_path = os.path.join(input_dir, image)
|
||||
i = Image.open(image_path)
|
||||
image = i.convert("RGB")
|
||||
image = np.array(image).astype(np.float32) / 255.0
|
||||
@ -895,18 +891,19 @@ class LoadImage:
|
||||
|
||||
@classmethod
|
||||
def IS_CHANGED(s, image):
|
||||
image_path = os.path.join(s.input_dir, image)
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
image_path = os.path.join(input_dir, image)
|
||||
m = hashlib.sha256()
|
||||
with open(image_path, 'rb') as f:
|
||||
m.update(f.read())
|
||||
return m.digest().hex()
|
||||
|
||||
class LoadImageMask:
|
||||
input_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "input")
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
return {"required":
|
||||
{"image": (sorted(os.listdir(s.input_dir)), ),
|
||||
{"image": (sorted(os.listdir(input_dir)), ),
|
||||
"channel": (["alpha", "red", "green", "blue"], ),}
|
||||
}
|
||||
|
||||
@ -915,7 +912,8 @@ class LoadImageMask:
|
||||
RETURN_TYPES = ("MASK",)
|
||||
FUNCTION = "load_image"
|
||||
def load_image(self, image, channel):
|
||||
image_path = os.path.join(self.input_dir, image)
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
image_path = os.path.join(input_dir, image)
|
||||
i = Image.open(image_path)
|
||||
mask = None
|
||||
c = channel[0].upper()
|
||||
@ -930,7 +928,8 @@ class LoadImageMask:
|
||||
|
||||
@classmethod
|
||||
def IS_CHANGED(s, image, channel):
|
||||
image_path = os.path.join(s.input_dir, image)
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
image_path = os.path.join(input_dir, image)
|
||||
m = hashlib.sha256()
|
||||
with open(image_path, 'rb') as f:
|
||||
m.update(f.read())
|
||||
|
||||
31
server.py
31
server.py
@ -18,6 +18,7 @@ except ImportError:
|
||||
sys.exit()
|
||||
|
||||
import mimetypes
|
||||
from comfy.cli_args import args
|
||||
|
||||
|
||||
@web.middleware
|
||||
@ -27,6 +28,23 @@ async def cache_control(request: web.Request, handler):
|
||||
response.headers.setdefault('Cache-Control', 'no-cache')
|
||||
return response
|
||||
|
||||
def create_cors_middleware(allowed_origin: str):
|
||||
@web.middleware
|
||||
async def cors_middleware(request: web.Request, handler):
|
||||
if request.method == "OPTIONS":
|
||||
# Pre-flight request. Reply successfully:
|
||||
response = web.Response()
|
||||
else:
|
||||
response = await handler(request)
|
||||
|
||||
response.headers['Access-Control-Allow-Origin'] = allowed_origin
|
||||
response.headers['Access-Control-Allow-Methods'] = 'POST, GET, DELETE, PUT, OPTIONS'
|
||||
response.headers['Access-Control-Allow-Headers'] = 'Content-Type, Authorization'
|
||||
response.headers['Access-Control-Allow-Credentials'] = 'true'
|
||||
return response
|
||||
|
||||
return cors_middleware
|
||||
|
||||
class PromptServer():
|
||||
def __init__(self, loop):
|
||||
PromptServer.instance = self
|
||||
@ -37,7 +55,12 @@ class PromptServer():
|
||||
self.loop = loop
|
||||
self.messages = asyncio.Queue()
|
||||
self.number = 0
|
||||
self.app = web.Application(client_max_size=20971520, middlewares=[cache_control])
|
||||
|
||||
middlewares = [cache_control]
|
||||
if args.enable_cors_header:
|
||||
middlewares.append(create_cors_middleware(args.enable_cors_header))
|
||||
|
||||
self.app = web.Application(client_max_size=20971520, middlewares=middlewares)
|
||||
self.sockets = dict()
|
||||
self.web_root = os.path.join(os.path.dirname(
|
||||
os.path.realpath(__file__)), "web")
|
||||
@ -89,7 +112,7 @@ class PromptServer():
|
||||
|
||||
@routes.post("/upload/image")
|
||||
async def upload_image(request):
|
||||
upload_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "input")
|
||||
upload_dir = folder_paths.get_input_directory()
|
||||
|
||||
if not os.path.exists(upload_dir):
|
||||
os.makedirs(upload_dir)
|
||||
@ -122,10 +145,10 @@ class PromptServer():
|
||||
async def view_image(request):
|
||||
if "filename" in request.rel_url.query:
|
||||
type = request.rel_url.query.get("type", "output")
|
||||
if type not in ["output", "input", "temp"]:
|
||||
output_dir = folder_paths.get_directory_by_type(type)
|
||||
if output_dir is None:
|
||||
return web.Response(status=400)
|
||||
|
||||
output_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), type)
|
||||
if "subfolder" in request.rel_url.query:
|
||||
full_output_dir = os.path.join(output_dir, request.rel_url.query["subfolder"])
|
||||
if os.path.commonpath((os.path.abspath(full_output_dir), output_dir)) != output_dir:
|
||||
|
||||
@ -112,6 +112,46 @@ class ComfyApp {
|
||||
};
|
||||
}
|
||||
|
||||
#addNodeKeyHandler(node) {
|
||||
const app = this;
|
||||
const origNodeOnKeyDown = node.prototype.onKeyDown;
|
||||
|
||||
node.prototype.onKeyDown = function(e) {
|
||||
if (origNodeOnKeyDown && origNodeOnKeyDown.apply(this, e) === false) {
|
||||
return false;
|
||||
}
|
||||
|
||||
if (this.flags.collapsed || !this.imgs || this.imageIndex === null) {
|
||||
return;
|
||||
}
|
||||
|
||||
let handled = false;
|
||||
|
||||
if (e.key === "ArrowLeft" || e.key === "ArrowRight") {
|
||||
if (e.key === "ArrowLeft") {
|
||||
this.imageIndex -= 1;
|
||||
} else if (e.key === "ArrowRight") {
|
||||
this.imageIndex += 1;
|
||||
}
|
||||
this.imageIndex %= this.imgs.length;
|
||||
|
||||
if (this.imageIndex < 0) {
|
||||
this.imageIndex = this.imgs.length + this.imageIndex;
|
||||
}
|
||||
handled = true;
|
||||
} else if (e.key === "Escape") {
|
||||
this.imageIndex = null;
|
||||
handled = true;
|
||||
}
|
||||
|
||||
if (handled === true) {
|
||||
e.preventDefault();
|
||||
e.stopImmediatePropagation();
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Adds Custom drawing logic for nodes
|
||||
* e.g. Draws images and handles thumbnail navigation on nodes that output images
|
||||
@ -803,6 +843,7 @@ class ComfyApp {
|
||||
|
||||
this.#addNodeContextMenuHandler(node);
|
||||
this.#addDrawBackgroundHandler(node, app);
|
||||
this.#addNodeKeyHandler(node);
|
||||
|
||||
await this.#invokeExtensionsAsync("beforeRegisterNodeDef", node, nodeData);
|
||||
LiteGraph.registerNodeType(nodeId, node);
|
||||
|
||||
@ -115,14 +115,6 @@ function dragElement(dragEl, settings) {
|
||||
savePos = value;
|
||||
},
|
||||
});
|
||||
|
||||
settings.addSetting({
|
||||
id: "Comfy.ConfirmClear",
|
||||
name: "Require confirmation when clearing workflow",
|
||||
type: "boolean",
|
||||
defaultValue: true,
|
||||
});
|
||||
|
||||
function dragMouseDown(e) {
|
||||
e = e || window.event;
|
||||
e.preventDefault();
|
||||
@ -170,7 +162,7 @@ class ComfyDialog {
|
||||
$el("p", { $: (p) => (this.textElement = p) }),
|
||||
$el("button", {
|
||||
type: "button",
|
||||
textContent: "CLOSE",
|
||||
textContent: "Close",
|
||||
onclick: () => this.close(),
|
||||
}),
|
||||
]),
|
||||
@ -233,6 +225,7 @@ class ComfySettingsDialog extends ComfyDialog {
|
||||
};
|
||||
|
||||
let element;
|
||||
value = this.getSettingValue(id, defaultValue);
|
||||
|
||||
if (typeof type === "function") {
|
||||
element = type(name, setter, value, attrs);
|
||||
@ -289,6 +282,16 @@ class ComfySettingsDialog extends ComfyDialog {
|
||||
return element;
|
||||
},
|
||||
});
|
||||
|
||||
const self = this;
|
||||
return {
|
||||
get value() {
|
||||
return self.getSettingValue(id, defaultValue);
|
||||
},
|
||||
set value(v) {
|
||||
self.setSettingValue(id, v);
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
show() {
|
||||
@ -410,6 +413,13 @@ export class ComfyUI {
|
||||
this.history.update();
|
||||
});
|
||||
|
||||
const confirmClear = this.settings.addSetting({
|
||||
id: "Comfy.ConfirmClear",
|
||||
name: "Require confirmation when clearing workflow",
|
||||
type: "boolean",
|
||||
defaultValue: true,
|
||||
});
|
||||
|
||||
const fileInput = $el("input", {
|
||||
type: "file",
|
||||
accept: ".json,image/png",
|
||||
@ -421,7 +431,7 @@ export class ComfyUI {
|
||||
});
|
||||
|
||||
this.menuContainer = $el("div.comfy-menu", { parent: document.body }, [
|
||||
$el("div", { style: { overflow: "hidden", position: "relative", width: "100%" } }, [
|
||||
$el("div.drag-handle", { style: { overflow: "hidden", position: "relative", width: "100%", cursor: "default" } }, [
|
||||
$el("span.drag-handle"),
|
||||
$el("span", { $: (q) => (this.queueSize = q) }),
|
||||
$el("button.comfy-settings-btn", { textContent: "⚙️", onclick: () => this.settings.show() }),
|
||||
@ -517,13 +527,13 @@ export class ComfyUI {
|
||||
$el("button", { textContent: "Load", onclick: () => fileInput.click() }),
|
||||
$el("button", { textContent: "Refresh", onclick: () => app.refreshComboInNodes() }),
|
||||
$el("button", { textContent: "Clear", onclick: () => {
|
||||
if (localStorage.getItem("Comfy.Settings.Comfy.ConfirmClear") == "false" || confirm("Clear workflow?")) {
|
||||
if (!confirmClear.value || confirm("Clear workflow?")) {
|
||||
app.clean();
|
||||
app.graph.clear();
|
||||
}
|
||||
}}),
|
||||
$el("button", { textContent: "Load Default", onclick: () => {
|
||||
if (localStorage.getItem("Comfy.Settings.Comfy.ConfirmClear") == "false" || confirm("Load default workflow?")) {
|
||||
if (!confirmClear.value || confirm("Load default workflow?")) {
|
||||
app.loadGraphData()
|
||||
}
|
||||
}}),
|
||||
|
||||
@ -39,18 +39,19 @@ body {
|
||||
position: fixed; /* Stay in place */
|
||||
z-index: 100; /* Sit on top */
|
||||
padding: 30px 30px 10px 30px;
|
||||
background-color: #ff0000; /* Modal background */
|
||||
background-color: #353535; /* Modal background */
|
||||
color: #ff4444;
|
||||
box-shadow: 0px 0px 20px #888888;
|
||||
border-radius: 10px;
|
||||
text-align: center;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
max-width: 80vw;
|
||||
max-height: 80vh;
|
||||
transform: translate(-50%, -50%);
|
||||
overflow: hidden;
|
||||
min-width: 60%;
|
||||
justify-content: center;
|
||||
font-family: monospace;
|
||||
font-size: 15px;
|
||||
}
|
||||
|
||||
.comfy-modal-content {
|
||||
@ -70,31 +71,11 @@ body {
|
||||
margin: 3px 3px 3px 4px;
|
||||
}
|
||||
|
||||
.comfy-modal button {
|
||||
cursor: pointer;
|
||||
color: #aaaaaa;
|
||||
border: none;
|
||||
background-color: transparent;
|
||||
font-size: 24px;
|
||||
font-weight: bold;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.comfy-modal button:hover,
|
||||
.comfy-modal button:focus {
|
||||
color: #000;
|
||||
text-decoration: none;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.comfy-menu {
|
||||
width: 200px;
|
||||
font-size: 15px;
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
right: 0%;
|
||||
background-color: white;
|
||||
color: #000;
|
||||
text-align: center;
|
||||
z-index: 100;
|
||||
width: 170px;
|
||||
@ -109,7 +90,8 @@ body {
|
||||
box-shadow: 3px 3px 8px rgba(0, 0, 0, 0.4);
|
||||
}
|
||||
|
||||
.comfy-menu button {
|
||||
.comfy-menu button,
|
||||
.comfy-modal button {
|
||||
font-size: 20px;
|
||||
}
|
||||
|
||||
@ -130,7 +112,8 @@ body {
|
||||
|
||||
.comfy-menu > button,
|
||||
.comfy-menu-btns button,
|
||||
.comfy-menu .comfy-list button {
|
||||
.comfy-menu .comfy-list button,
|
||||
.comfy-modal button{
|
||||
color: #ddd;
|
||||
background-color: #222;
|
||||
border-radius: 8px;
|
||||
@ -220,11 +203,22 @@ button.comfy-queue-btn {
|
||||
}
|
||||
|
||||
.comfy-modal.comfy-settings {
|
||||
background-color: var(--bg-color);
|
||||
color: var(--fg-color);
|
||||
text-align: center;
|
||||
font-family: sans-serif;
|
||||
color: #999;
|
||||
z-index: 99;
|
||||
}
|
||||
|
||||
.comfy-modal input,
|
||||
.comfy-modal select {
|
||||
color: #ddd;
|
||||
background-color: #222;
|
||||
border-radius: 8px;
|
||||
border-color: #4e4e4e;
|
||||
border-style: solid;
|
||||
font-size: inherit;
|
||||
}
|
||||
|
||||
@media only screen and (max-height: 850px) {
|
||||
.comfy-menu {
|
||||
top: 0 !important;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user