Disable cuda malloc by default.
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e60e19b175
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@ -51,8 +51,8 @@ parser.add_argument("--auto-launch", action="store_true", help="Automatically la
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parser.add_argument("--disable-auto-launch", action="store_true", help="Disable auto launching the browser.")
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parser.add_argument("--cuda-device", type=int, default=None, metavar="DEVICE_ID", help="Set the id of the cuda device this instance will use.")
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cm_group = parser.add_mutually_exclusive_group()
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cm_group.add_argument("--cuda-malloc", action="store_true", help="Enable cudaMallocAsync (enabled by default for torch 2.0 and up).")
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cm_group.add_argument("--disable-cuda-malloc", action="store_true", help="Disable cudaMallocAsync.")
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cm_group.add_argument("--cuda-malloc", action="store_true", help="Enable cudaMallocAsync.")
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cm_group.add_argument("--disable-cuda-malloc", action="store_true", help="Disable cudaMallocAsync (The current default).")
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fp_group = parser.add_mutually_exclusive_group()
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@ -2,6 +2,7 @@ import os
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import importlib.util
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from comfy.cli_args import args
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import subprocess
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import logging
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#Can't use pytorch to get the GPU names because the cuda malloc has to be set before the first import.
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def get_gpu_names():
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@ -63,7 +64,7 @@ def cuda_malloc_supported():
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return True
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if not args.cuda_malloc:
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if args.cuda_malloc:
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try:
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version = ""
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torch_spec = importlib.util.find_spec("torch")
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@ -74,8 +75,11 @@ if not args.cuda_malloc:
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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version = module.__version__
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supported = False
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if int(version[0]) >= 2: #enable by default for torch version 2.0 and up
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args.cuda_malloc = cuda_malloc_supported()
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supported = cuda_malloc_supported()
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if not supported:
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logging.warning("WARNING: cuda malloc enabled but not supported.")
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except:
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pass
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