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fix bytes2tensor error in torch version == 2.6.0. #950

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Jul 1, 2025
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fix bytes2tensor error in torch version == 2.6.0. #950

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2 changes: 1 addition & 1 deletion lightllm/server/embed_cache/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ def tensor2bytes(t: torch.Tensor):

def bytes2tensor(b):
# return torch.from_numpy(np.frombuffer(b, dtype=np.float16)).cuda()
return torch.load(BytesIO(b))
return torch.load(BytesIO(b), weights_only=False)
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high

Explicitly setting weights_only=False is the correct fix for the breaking change in upcoming PyTorch versions where this argument will default to True. However, this setting can introduce a security vulnerability if the serialized data comes from an untrusted source, as it can lead to arbitrary code execution during deserialization.

In this specific case, the data is generated internally by the tensor2bytes function and passed via shared memory, so it can be considered trusted. To improve code clarity and prevent future misuse by developers who may not be aware of the context, I recommend adding a comment explaining why weights_only=False is necessary and why it's considered safe here.

Suggested change
return torch.load(BytesIO(b), weights_only=False)
return torch.load(BytesIO(b), weights_only=False) # Required for unpickling tensor objects; safe as data is generated internally.



def create_shm(name, data):
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