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Force safe loading of files in torch format on pytorch 2.4+

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comfyanonymous 2025-01-15 03:50:27 -05:00
parent 5b657f8c15
commit 2feb8d0b77
1 changed files with 17 additions and 5 deletions
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22
comfy/utils.py
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@ -29,17 +29,29 @@ import itertools
from torch.nn.functional import interpolate
from einops import rearrange
ALWAYS_SAFE_LOAD = False
if hasattr(torch.serialization, "add_safe_globals"): # TODO: this was added in pytorch 2.4, the unsafe path should be removed once earlier versions are deprecated
class ModelCheckpoint:
pass
ModelCheckpoint.__module__ = "pytorch_lightning.callbacks.model_checkpoint"
from numpy.core.multiarray import scalar
from numpy import dtype
from numpy.dtypes import Float64DType
from _codecs import encode
torch.serialization.add_safe_globals([ModelCheckpoint, scalar, dtype, Float64DType, encode])
ALWAYS_SAFE_LOAD = True
logging.info("Checkpoint files will always be loaded safely.")
def load_torch_file(ckpt, safe_load=False, device=None):
if device is None:
device = torch.device("cpu")
if ckpt.lower().endswith(".safetensors") or ckpt.lower().endswith(".sft"):
sd = safetensors.torch.load_file(ckpt, device=device.type)
else:
if safe_load:
if not 'weights_only' in torch.load.__code__.co_varnames:
logging.warning("Warning torch.load doesn't support weights_only on this pytorch version, loading unsafely.")
safe_load = False
if safe_load:
if safe_load or ALWAYS_SAFE_LOAD:
pl_sd = torch.load(ckpt, map_location=device, weights_only=True)
else:
pl_sd = torch.load(ckpt, map_location=device, pickle_module=comfy.checkpoint_pickle)