Running into "Some tensors share memory" `RuntimeError` when converting finetuned GPT2 about safetensors HOT 2 CLOSED

Thank you @mrshu for reporting this,

The reason for this error is that is we need to update transformers code for that.

In PyTorch you can do:

a = torch.zeros((2, 2))
b = a[:1, :]
torch.save({"a": a, "b": b})

And everything will work fine, and the tensors will be shared when loading the weights.
This is not possible in safetensors because it can lead to tricky issues where you allocate more than you need (when loading only "b" for instance, you will allocate the whole "a" tensor, and only slice into it). It also leads to more issues when doing things like distributed training/saving (where the weights cannot be shared).

You can use this script to convert existing weights: https://github.com/huggingface/safetensors/blob/main/bindings/python/convert.py . More specifically those lines: https://github.com/huggingface/safetensors/blob/main/bindings/python/convert.py#L91-L94
I'll open something in transformers to fix this. It's only a matter of skipping the decoder.weight weight while saving for it to work.

This won't cause any issues for transformers because the weight is automatically tied when you are loading with AutoModel.from_pretrained(...). Meaning the tensors will be correctly shared.

from safetensors.

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from safetensors.