[docs] Unclear if to_pil_image / to_tensor copy or zero-copy for CPU<->CPU

[vadimkantorov]

It currently uses a vague language "convert". It's not sure if "conversion" incurs a copy or not

cc @vfdev-5

[datumbox]

I believe these two methods copy. This is because they go from one backend to a completely different one (say from PIL to PyTorch Tensor stored on GPU or vice-versa).

[NicolasHug]

This is worth double-checking but in theory a no-copy should be possible, and I agree it would be valuable info to explicitly document this. PIL images implement __array_interface__ (https://numpy.org/doc/stable/reference/arrays.interface.html) so one can make no-copy conversions PIL <-> numpy, and there are ongoing efforts regarding tensor <-> numpy too: pytorch/pytorch#22402

[vadimkantorov]

I'm meaning CPU<-> CPU conversions of course, where zero-copy conversion theoretically is possible, e.g. identically to NumPy <-> PyTorch conversion

If PIL implements __array_interface__, could the conversion be in essence torch.as_tensor and a permute?

[fmassa]

Those functions could be zero-copy, except that we perform multiplication / division by 255, which means there will be overhead involved.

If you want zero-overhead, I would recommend using pil_to_tensor

[datumbox]

Some relevant discussion about copying or not here: #3813 (review)