I filed issue 9714 https://github.com/numpy/numpy/issues/9714 and wrote
a mail in September trying to get some feedback on what to do with
updateifcopy semantics and user-exposed nditer.
It garnered no response, so I am trying again.
For those who are unfamiliar with the issue see below for a short
summary and issue 7054 for a lengthy discussion.
Note that pull request 9639 which should be merged very soon changes the
magical UPDATEIFCOPY into WRITEBACKIFCOPY, and hopefully will appear in
NumPy 1.14.
As I mention in the issue, there is a magical update done in this
snippet in the next-to-the-last line:
|a = np.arange(24, dtype='f8').reshape(2, 3, 4).T i = np.nditer(a, [],
[['readwrite', 'updateifcopy']], casting='same_kind',
op_dtypes=[np.dtype('f4')]) # Check that UPDATEIFCOPY is activated
i.operands[0][2, 1, 1] = -12.5 assert a[2, 1, 1] != -12.5 i = None #
magic!!! assert a[2, 1, 1] == -12.5|
Not only is this magic very implicit, it relies on refcount semantics
and thus does not work on PyPy.
Possible solutions:
1. nditer is rarely used, just deprecate updateifcopy use on operands
2. make nditer into a context manager, so the code would become explicit
|a = np.arange(24, dtype='f8').reshape(2, 3, 4).T with np.nditer(a, [],
[['readwrite', 'updateifcopy']], casting='same_kind',
op_dtypes=[np.dtype('f4')]) as i: # Check that WRITEBACKIFCOPY is
activated i.operands[0][2, 1, 1] = -12.5 assert a[2, 1, 1] != -12.5
assert a[2, 1, 1] == -12.5 # a is modified in i.__exit__|
3. something else?
Any opinions? Does anyone use nditer in production code?
Matti
-------------------------
what are updateifcopy semantics? When a temporary copy or work buffer is
required, NumPy can (ab)use the base attribute of an ndarray by
- creating a copy of the data from the base array
- mark the base array read-only
Then when the temporary buffer is "no longer needed"
- the data is copied back
- the original base array is marked read-write
The trigger for the "no longer needed" decision before pull request 9639
is in the dealloc function.
That is not generally a place to do useful work, especially on PyPy
which can call dealloc much later.
Pull request 9639 adds an explicit PyArray_ResolveWritebackIfCopy api
function, and recommends calling it explicitly before dealloc.
The only place this change is visible to the python-level user is in
nditer.
C-API users will need to adapt their code to use the new API function,
with a deprecation cycle that is backwardly compatible on CPython.
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