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Added NotImplemented error to Array.concatenate #508

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Added NotImplemented error to Array.concatenate #508

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37ff455
Added NotImplemented error to Array.concatenate
panchoop Aug 5, 2021
940cfcf
fixed syntax error in Error message
panchoop Aug 11, 2021
33e83dd
fixed Flake8 errors
panchoop Aug 12, 2021
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9 changes: 9 additions & 0 deletions pyopencl/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2604,11 +2604,20 @@ def make_func_for_chunk_size(chunk_size):

def concatenate(arrays, axis=0, queue=None, allocator=None):
"""
Return a :class:`Array` that is a concatenation of the input tuple of
:class:`Array` along :arg axis:. **Warning** Only axis = 0 has been
implemented.

.. versionadded:: 2013.1
"""
# {{{ find properties of result array

shape = None
if axis != 0:
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@inducer inducer Aug 5, 2021

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This isn't correct. This should instead be based on contiguity. Column-major arrays for example allow concatenation along the last axis.

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@panchoop panchoop Aug 10, 2021 •
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I noticed that the code failed the tests because I missed a syntax error. Sorry for the noise.

About contiguity, I did some tests, and the function does not work in any axis for colum-major arrays. In line 2571 of the Array.concatenate function, the output array result is always a row-major array, leading to the same NotImlementedError due to miss-matching strides.

Simple example:

import pyopencl as cl
platform = cl.get_platforms()[0]
device = platform.get_devices()[0]
context = cl.create_some_context([device])
queue = cl.CommandQueue(context)

a = np.random.rand(2,2)
b = np.random.rand(2,2)

a_cl = clarray.to_device(queue, np.require(a, np.float64, 'F'))
b_cl = clarray.to_device(queue, np.require(b, np.float64, 'F'))

c_cl = clarray.concatenate( (a_cl, b_cl), axis=1)

It shouldn't be hard to allow column-major arrays, it is just a matter of initializing the result array with order="F" in these cases. The issue I see is that the Array class has no member that indicates the ordering. One could deduce the order by looking at the strides (if Array.strides[0] > Array.strides[-1]: row-major, else: column-major) but maybe it is too hacky. what do you think?

Another approach is the one taken in the Array.stack function, in which when the axis != 0, it is assumed that the input is column mayor. But it would also lead to unclear error messages.

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@inducer inducer Aug 10, 2021

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Thanks for pointing out the issue with concatenate and column-major arrays, we should look into fixing that. I agree with your assessment about inspection of the strides, it's not quite elegant.

FWIW, CI is still not passing on this branch.

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@panchoop panchoop Aug 11, 2021

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Oh yeah! I forgot to push. It should work now.

raise NotImplementedError("Axis != 0. "+
"To be implementedk when Array.setitems " +
"allows values with different stride".)


for i_ary, ary in enumerate(arrays):
queue = queue or ary.queue
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