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nep-0015-merge-multiarray-umath.html
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nep-0015-merge-multiarray-umath.html
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<section id="nep-15-merging-multiarray-and-umath">
<span id="nep15"></span><h1>NEP 15 — Merging multiarray and umath<a class="headerlink" href="#nep-15-merging-multiarray-and-umath" title="Link to this heading">#</a></h1>
<dl class="field-list simple">
<dt class="field-odd">Author<span class="colon">:</span></dt>
<dd class="field-odd"><p>Nathaniel J. Smith <<a class="reference external" href="mailto:njs%40pobox.com">njs<span>@</span>pobox<span>.</span>com</a>></p>
</dd>
<dt class="field-even">Status<span class="colon">:</span></dt>
<dd class="field-even"><p>Final</p>
</dd>
<dt class="field-odd">Type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Standards Track</p>
</dd>
<dt class="field-even">Created<span class="colon">:</span></dt>
<dd class="field-even"><p>2018-02-22</p>
</dd>
<dt class="field-odd">Resolution<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://mail.python.org/pipermail/numpy-discussion/2018-June/078345.html">https://mail.python.org/pipermail/numpy-discussion/2018-June/078345.html</a></p>
</dd>
</dl>
<section id="abstract">
<h2>Abstract<a class="headerlink" href="#abstract" title="Link to this heading">#</a></h2>
<p>Let’s merge <code class="docutils literal notranslate"><span class="pre">numpy.core.multiarray</span></code> and <code class="docutils literal notranslate"><span class="pre">numpy.core.umath</span></code> into a
single extension module, and deprecate <code class="docutils literal notranslate"><span class="pre">np.set_numeric_ops</span></code>.</p>
</section>
<section id="background">
<h2>Background<a class="headerlink" href="#background" title="Link to this heading">#</a></h2>
<p>Currently, numpy’s core C code is split between two separate extension
modules.</p>
<p><code class="docutils literal notranslate"><span class="pre">numpy.core.multiarray</span></code> is built from
<code class="docutils literal notranslate"><span class="pre">numpy/core/src/multiarray/*.c</span></code>, and contains the core array
functionality (in particular, the <code class="docutils literal notranslate"><span class="pre">ndarray</span></code> object).</p>
<p><code class="docutils literal notranslate"><span class="pre">numpy.core.umath</span></code> is built from <code class="docutils literal notranslate"><span class="pre">numpy/core/src/umath/*.c</span></code>, and
contains the ufunc machinery.</p>
<p>These two modules each expose their own separate C API, accessed via
<code class="docutils literal notranslate"><span class="pre">import_multiarray()</span></code> and <code class="docutils literal notranslate"><span class="pre">import_umath()</span></code> respectively. The idea
is that they’re supposed to be independent modules, with
<code class="docutils literal notranslate"><span class="pre">multiarray</span></code> as a lower-level layer with <code class="docutils literal notranslate"><span class="pre">umath</span></code> built on top. In
practice this has turned out to be problematic.</p>
<p>First, the layering isn’t perfect: when you write <code class="docutils literal notranslate"><span class="pre">ndarray</span> <span class="pre">+</span>
<span class="pre">ndarray</span></code>, this invokes <code class="docutils literal notranslate"><span class="pre">ndarray.__add__</span></code>, which then calls the
ufunc <code class="docutils literal notranslate"><span class="pre">np.add</span></code>. This means that <code class="docutils literal notranslate"><span class="pre">ndarray</span></code> needs to know about
ufuncs – so instead of a clean layering, we have a circular
dependency. To solve this, <code class="docutils literal notranslate"><span class="pre">multiarray</span></code> exports a somewhat
terrifying function called <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code>. The bootstrap
procedure each time you <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">numpy</span></code> is:</p>
<ol class="arabic simple">
<li><p><code class="docutils literal notranslate"><span class="pre">multiarray</span></code> and its <code class="docutils literal notranslate"><span class="pre">ndarray</span></code> object are loaded, but
arithmetic operations on ndarrays are broken.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">umath</span></code> is loaded.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code> is used to monkeypatch all the methods like
<code class="docutils literal notranslate"><span class="pre">ndarray.__add__</span></code> with objects from <code class="docutils literal notranslate"><span class="pre">umath</span></code>.</p></li>
</ol>
<p>In addition, <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code> is exposed as a public API,
<code class="docutils literal notranslate"><span class="pre">np.set_numeric_ops</span></code>.</p>
<p>Furthermore, even when this layering does work, it ends up distorting
the shape of our public ABI. In recent years, the most common reason
for adding new functions to <code class="docutils literal notranslate"><span class="pre">multiarray</span></code>'s “public” ABI is not that
they really need to be public or that we expect other projects to use
them, but rather just that we need to call them from <code class="docutils literal notranslate"><span class="pre">umath</span></code>. This
is extremely unfortunate, because it makes our public ABI
unnecessarily large, and since we can never remove things from it then
this creates an ongoing maintenance burden. The way C works, you can
have internal API that’s visible to everything inside the same
extension module, or you can have a public API that everyone can use;
you can’t (easily) have an API that’s visible to multiple extension
modules inside numpy, but not to external users.</p>
<p>We’ve also increasingly been putting utility code into
<code class="docutils literal notranslate"><span class="pre">numpy/core/src/private/</span></code>, which now contains a bunch of files which
are <code class="docutils literal notranslate"><span class="pre">#include</span></code>d twice, once into <code class="docutils literal notranslate"><span class="pre">multiarray</span></code> and once into
<code class="docutils literal notranslate"><span class="pre">umath</span></code>. This is pretty gross, and is purely a workaround for these
being separate C extensions. The <code class="docutils literal notranslate"><span class="pre">npymath</span></code> library is also
included in both extension modules.</p>
</section>
<section id="proposed-changes">
<h2>Proposed changes<a class="headerlink" href="#proposed-changes" title="Link to this heading">#</a></h2>
<p>This NEP proposes three changes:</p>
<ol class="arabic simple">
<li><p>We should start building <code class="docutils literal notranslate"><span class="pre">numpy/core/src/multiarray/*.c</span></code> and
<code class="docutils literal notranslate"><span class="pre">numpy/core/src/umath/*.c</span></code> together into a single extension
module.</p></li>
<li><p>Instead of <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code>, we should use some new, private API
to set up <code class="docutils literal notranslate"><span class="pre">ndarray.__add__</span></code> and friends.</p></li>
<li><p>We should deprecate, and eventually remove, <code class="docutils literal notranslate"><span class="pre">np.set_numeric_ops</span></code>.</p></li>
</ol>
</section>
<section id="non-proposed-changes">
<h2>Non-proposed changes<a class="headerlink" href="#non-proposed-changes" title="Link to this heading">#</a></h2>
<p>We don’t necessarily propose to throw away the distinction between
multiarray/ and umath/ in terms of our source code organization:
internal organization is useful! We just want to build them together
into a single extension module. Of course, this does open the door for
potential future refactorings, which we can then evaluate based on
their merits as they come up.</p>
<p>It also doesn’t propose that we break the public C ABI. We should
continue to provide <code class="docutils literal notranslate"><span class="pre">import_multiarray()</span></code> and <code class="docutils literal notranslate"><span class="pre">import_umath()</span></code>
functions – it’s just that now both ABIs will ultimately be loaded
from the same C library. Due to how <code class="docutils literal notranslate"><span class="pre">import_multiarray()</span></code> and
<code class="docutils literal notranslate"><span class="pre">import_umath()</span></code> are written, we’ll also still need to have modules
called <code class="docutils literal notranslate"><span class="pre">numpy.core.multiarray</span></code> and <code class="docutils literal notranslate"><span class="pre">numpy.core.umath</span></code>, and they’ll
need to continue to export <code class="docutils literal notranslate"><span class="pre">_ARRAY_API</span></code> and <code class="docutils literal notranslate"><span class="pre">_UFUNC_API</span></code> objects –
but we can make one or both of these modules be tiny shims that simply
re-export the magic API object from where-ever it’s actually defined.
(See <code class="docutils literal notranslate"><span class="pre">numpy/core/code_generators/generate_{numpy,ufunc}_api.py</span></code> for
details of how these imports work.)</p>
</section>
<section id="backward-compatibility">
<h2>Backward compatibility<a class="headerlink" href="#backward-compatibility" title="Link to this heading">#</a></h2>
<p>The only compatibility break is the deprecation of <code class="docutils literal notranslate"><span class="pre">np.set_numeric_ops</span></code>.</p>
</section>
<section id="rejected-alternatives">
<h2>Rejected alternatives<a class="headerlink" href="#rejected-alternatives" title="Link to this heading">#</a></h2>
<section id="preserve-set-numeric-ops-for-monkeypatching">
<h3>Preserve <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code> for monkeypatching<a class="headerlink" href="#preserve-set-numeric-ops-for-monkeypatching" title="Link to this heading">#</a></h3>
<p>In discussing this NEP, one additional use case was raised for
<code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code>: if you have an optimized vector math library
(e.g. Intel’s MKL VML, Sleef, or Yeppp), then <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code> can
be used to monkeypatch numpy to use these operations instead of
numpy’s built-in vector operations. But, even if we grant that this is
a great idea, using <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code> isn’t actually the best way to
do it. All <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code> allows you to do is take over Python’s
syntactic operators (<code class="docutils literal notranslate"><span class="pre">+</span></code>, <code class="docutils literal notranslate"><span class="pre">*</span></code>, etc.) on ndarrays; it doesn’t let
you affect operations called via other APIs (e.g., <code class="docutils literal notranslate"><span class="pre">np.add</span></code>), or
operations that don’t have built-in syntax (e.g., <code class="docutils literal notranslate"><span class="pre">np.exp</span></code>). Also,
you have to reimplement the whole ufunc machinery, instead of just the
core loop. On the other hand, the <a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/c-api.ufunc.html#c.PyUFunc_ReplaceLoopBySignature">PyUFunc_ReplaceLoopBySignature</a>
API – which was added in 2006 – allows replacement of the inner loops
of arbitrary ufuncs. This is both simpler and more powerful – e.g.
replacing the inner loop of <code class="docutils literal notranslate"><span class="pre">np.add</span></code> means your code will
automatically be used for both <code class="docutils literal notranslate"><span class="pre">ndarray</span> <span class="pre">+</span> <span class="pre">ndarray</span></code> as well as direct
calls to <code class="docutils literal notranslate"><span class="pre">np.add</span></code>. So this doesn’t seem like a good reason to not
deprecate <code class="docutils literal notranslate"><span class="pre">set_numeric_ops</span></code>.</p>
</section>
</section>
<section id="discussion">
<h2>Discussion<a class="headerlink" href="#discussion" title="Link to this heading">#</a></h2>
<ul class="simple">
<li><p><a class="reference external" href="https://mail.python.org/pipermail/numpy-discussion/2018-March/077764.html">https://mail.python.org/pipermail/numpy-discussion/2018-March/077764.html</a></p></li>
<li><p><a class="reference external" href="https://mail.python.org/pipermail/numpy-discussion/2018-June/078345.html">https://mail.python.org/pipermail/numpy-discussion/2018-June/078345.html</a></p></li>
</ul>
</section>
<section id="copyright">
<h2>Copyright<a class="headerlink" href="#copyright" title="Link to this heading">#</a></h2>
<p>This document has been placed in the public domain.</p>
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