Docs for pull request 1921

Author: github-actions[doc-deploy-bot]

pulls/1921/_modules/dpctl.html

@@ -839,6 +839,7 @@ <h1>Source code for dpctl</h1><div class="highlight"><pre>
 <span class="kn">import</span> <span class="nn">os</span>
 <span class="kn">import</span> <span class="nn">os.path</span>
 
+<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">_init_helper</span>
 <span class="kn">from</span> <span class="nn">._device_selection</span> <span class="kn">import</span> <span class="n">select_device_with_aspects</span>
 <span class="kn">from</span> <span class="nn">._sycl_context</span> <span class="kn">import</span> <span class="n">SyclContext</span><span class="p">,</span> <span class="n">SyclContextCreationError</span>
 <span class="kn">from</span> <span class="nn">._sycl_device</span> <span class="kn">import</span> <span class="p">(</span>
@@ -950,6 +951,7 @@ <h1>Source code for dpctl</h1><div class="highlight"><pre>
 
 <span class="n">__version__</span> <span class="o">=</span> <span class="n">get_versions</span><span class="p">()[</span><span class="s2">&quot;version&quot;</span><span class="p">]</span>
 <span class="k">del</span> <span class="n">get_versions</span>
+<span class="k">del</span> <span class="n">_init_helper</span>
 </pre></div>
         </article>
       </div>

pulls/1921/_modules/dpctl/tensor/_copy_utils.html

@@ -1485,9 +1485,13 @@ <h1>Source code for dpctl.tensor._copy_utils</h1><div class="highlight"><pre>
     <span class="n">f_contig</span> <span class="o">=</span> <span class="n">usm_ary</span><span class="o">.</span><span class="n">flags</span><span class="o">.</span><span class="n">f_contiguous</span>
     <span class="n">needs_copy</span> <span class="o">=</span> <span class="n">copy</span> <span class="ow">or</span> <span class="ow">not</span> <span class="n">ary_dtype</span> <span class="o">==</span> <span class="n">target_dtype</span>
     <span class="k">if</span> <span class="ow">not</span> <span class="n">needs_copy</span> <span class="ow">and</span> <span class="p">(</span><span class="n">order</span> <span class="o">!=</span> <span class="s2">&quot;K&quot;</span><span class="p">):</span>
-        <span class="n">needs_copy</span> <span class="o">=</span> <span class="p">(</span><span class="n">c_contig</span> <span class="ow">and</span> <span class="n">order</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;A&quot;</span><span class="p">,</span> <span class="s2">&quot;C&quot;</span><span class="p">])</span> <span class="ow">or</span> <span class="p">(</span>
-            <span class="n">f_contig</span> <span class="ow">and</span> <span class="n">order</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;A&quot;</span><span class="p">,</span> <span class="s2">&quot;F&quot;</span><span class="p">]</span>
-        <span class="p">)</span>
+        <span class="c1"># ensure that order=&quot;F&quot; for C-contig input triggers copy,</span>
+        <span class="c1"># and order=&quot;C&quot; for F-contig input triggers copy too.</span>
+        <span class="c1"># 1D arrays which are both C- and F- contig should not</span>
+        <span class="c1"># force copying for neither order=&quot;F&quot;, nor order=&quot;C&quot;, see gh-1926</span>
+        <span class="n">needs_copy</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="n">c_contig</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">f_contig</span> <span class="ow">and</span> <span class="n">order</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;A&quot;</span><span class="p">,</span> <span class="s2">&quot;C&quot;</span><span class="p">]</span>
+        <span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="ow">not</span> <span class="n">c_contig</span> <span class="ow">and</span> <span class="n">f_contig</span> <span class="ow">and</span> <span class="n">order</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;A&quot;</span><span class="p">,</span> <span class="s2">&quot;F&quot;</span><span class="p">])</span>
     <span class="k">if</span> <span class="ow">not</span> <span class="n">needs_copy</span><span class="p">:</span>
         <span class="k">return</span> <span class="n">usm_ary</span>
     <span class="n">copy_order</span> <span class="o">=</span> <span class="s2">&quot;C&quot;</span>

pulls/1921/beginners_guides/installation.html

@@ -882,7 +882,7 @@ <h2>Installation using pip<a class="headerlink" href="#installation-using-pip" t
 <section id="installation-via-intel-r-distribution-for-python">
 <h2>Installation via Intel(R) Distribution for Python<a class="headerlink" href="#installation-via-intel-r-distribution-for-python" title="Permalink to this heading">¶</a></h2>
 <p><a class="reference external" href="https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html">Intel(R) Distribution for Python*</a> is distributed as a conda-based installer
-and includes <a class="reference internal" href="../api_reference/dpctl/index.html#module-dpctl" title="dpctl"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpctl</span></code></a> along with its dependencies and sister projects <a class="reference external" href="https://intelpython.github.io/dpnp/overview.html#module-dpnp" title="(in Data Parallel Extension for NumPy v0.17.0dev3+1.ge53fa72c543)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpnp</span></code></a>
+and includes <a class="reference internal" href="../api_reference/dpctl/index.html#module-dpctl" title="dpctl"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpctl</span></code></a> along with its dependencies and sister projects <a class="reference external" href="https://intelpython.github.io/dpnp/overview.html#module-dpnp" title="(in Data Parallel Extension for NumPy v0.17.0dev3+19.gd83ea3daf8)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpnp</span></code></a>
 and <a class="reference external" href="https://intelpython.github.io/numba-dpex/latest/index.html#module-numba_dpex" title="(in numba-dpex)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">numba_dpex</span></code></a>.</p>
 <p>Once the installed environment is activated, <code class="docutils literal notranslate"><span class="pre">dpctl</span></code> should be ready to use.</p>
 </section>