On Wed, 2018-12-26 at 16:40 -0800, Ralf Gommers wrote: > > > On Wed, Dec 26, 2018 at 3:29 PM Sebastian Berg < > sebast...@sipsolutions.net> wrote: > > Hi all, > > > > In https://github.com/numpy/numpy/pull/11897 I am looking into the > > addition of a `copy=np.never_copy` argument to: > > * np.array > > * arr.reshape/np.reshape > > * arr.astype > > > > Which would cause an error to be raised when numpy cannot guarantee > > that the returned array is a view of the input array. > > The motivation is to easier avoid accidental copies of large data, > > or > > ensure that in-place manipulation will be meaningful. > > > > The copy flag API would be: > > * `copy=True` forces a copy > > * `copy=False` allows numpy to copy if necessary > > * `copy=np.never_copy` will error if a copy would be necessary > > * (almost) all other input will be deprecated. > > > > Unfortunately using `copy="never"` is tricky, because currently > > `np.array(..., copy="never")` behaves exactly the same as > > `np.array(..., copy=bool("never"))`. So that the wrong result would > > be > > given on old numpy versions and it would be a behaviour change. > > I think np.never_copy is really ugly. I'd much rather simply use > 'never', and clearly document that if users start using this and they > critically rely on it really being never, then they should ensure > that their code is only used with numpy >= 1.17.0. > > Note also that this would not be a backwards compatibility break, > because `copy` is now clearly documented as bool, and not bool_like > or some such thing. So we do not need to worry about the very > improbable case that users now are using `copy='never'`. >
I agree that it is much nicer to pass "never" and that I am not too worried about people actually passing in strings. But, I am a bit worried of new code silently doing the exact opposite when run on an older version. Although, I guess we typically do not worry too much about such compatibilities and it is possible to make a note of it in the docs. - Sebastian > If others think `copy='never'` isn't acceptable now, there are two > other options: > 1. add code first to catch `copy='never'` in 1.17.x and raise on it, > then in a later numpy version introduce it. > 2. just do nothing. I'd prefer that over `np.never_copy`. > > Cheers, > Ralf > > > Some things that are a not so nice maybe: > > * adding/using `np.never_copy` is not very nice > > * Scalars need a copy and so will not be allowed > > * For rare array-likes numpy may not be able to guarantee no-copy, > > although it could happen (but should not). > > > > > > The history is that a long while ago I considered adding a copy > > flag to > > `reshape` so that it is possible to do `copy=np.never_copy` (or > > similar) to ensure that no copy is made. In these, you may want > > something like an assertion: > > > > ``` > > new_arr = arr.reshape(new_shape) > > assert np.may_share_memory(arr, new_arr) > > > > # Which is sometimes -- but should not be -- written as: > > arr.shape = new_shape # unnecessary container modification > > > > # Or: > > view = np.array(arr, order="F") > > assert np.may_share_memory(arr, new_arr) > > ``` > > > > but is more readable and will not cause an intermediate copy on > > error. > > > > > > So what do you think? Other variants would be to not expose this > > for > > `np.array` and probably limit `copy="never"` to the reshape method. > > Or > > just to not do it at all. Or to also accept "never" for `reshape`, > > although I think I would prefer to keep it in sync and wait for a > > few > > years to consider that. > > > > Best, > > > > Sebastian > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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