Docs for pull request 1869

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

pulls/1869/_modules/dpctl/tensor/_manipulation_functions.html

@@ -1164,7 +1164,7 @@ <h1>Source code for dpctl.tensor._manipulation_functions</h1><div class="highlig
         <span class="n">res</span> <span class="o">=</span> <span class="n">dpt</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span>
             <span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">x</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">usm_type</span><span class="o">=</span><span class="n">x</span><span class="o">.</span><span class="n">usm_type</span><span class="p">,</span> <span class="n">sycl_queue</span><span class="o">=</span><span class="n">exec_q</span>
         <span class="p">)</span>
-        <span class="n">sz</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">size</span>
+        <span class="n">sz</span> <span class="o">=</span> <span class="n">operator</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">size</span><span class="p">)</span>
         <span class="n">shift</span> <span class="o">=</span> <span class="p">(</span><span class="n">shift</span> <span class="o">%</span> <span class="n">sz</span><span class="p">)</span> <span class="k">if</span> <span class="n">sz</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
         <span class="n">dep_evs</span> <span class="o">=</span> <span class="n">_manager</span><span class="o">.</span><span class="n">submitted_events</span>
         <span class="n">hev</span><span class="p">,</span> <span class="n">roll_ev</span> <span class="o">=</span> <span class="n">ti</span><span class="o">.</span><span class="n">_copy_usm_ndarray_for_roll_1d</span><span class="p">(</span>
@@ -1185,8 +1185,9 @@ <h1>Source code for dpctl.tensor._manipulation_functions</h1><div class="highlig
     <span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="o">.</span><span class="n">ndim</span>
     <span class="n">shape</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">shape</span>
     <span class="k">for</span> <span class="n">sh</span><span class="p">,</span> <span class="n">ax</span> <span class="ow">in</span> <span class="n">broadcasted</span><span class="p">:</span>
-        <span class="n">n_i</span> <span class="o">=</span> <span class="n">shape</span><span class="p">[</span><span class="n">ax</span><span class="p">]</span>
-        <span class="n">shifts</span><span class="p">[</span><span class="n">ax</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">shifts</span><span class="p">[</span><span class="n">ax</span><span class="p">]</span> <span class="o">+</span> <span class="n">sh</span><span class="p">)</span> <span class="o">%</span> <span class="nb">int</span><span class="p">(</span><span class="n">n_i</span><span class="p">))</span> <span class="k">if</span> <span class="n">n_i</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
+        <span class="n">n_i</span> <span class="o">=</span> <span class="n">operator</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">shape</span><span class="p">[</span><span class="n">ax</span><span class="p">])</span>
+        <span class="n">shifted</span> <span class="o">=</span> <span class="n">shifts</span><span class="p">[</span><span class="n">ax</span><span class="p">]</span> <span class="o">+</span> <span class="n">operator</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">sh</span><span class="p">)</span>
+        <span class="n">shifts</span><span class="p">[</span><span class="n">ax</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">shifted</span> <span class="o">%</span> <span class="n">n_i</span><span class="p">)</span> <span class="k">if</span> <span class="n">n_i</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
     <span class="n">res</span> <span class="o">=</span> <span class="n">dpt</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span>
         <span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">x</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">usm_type</span><span class="o">=</span><span class="n">x</span><span class="o">.</span><span class="n">usm_type</span><span class="p">,</span> <span class="n">sycl_queue</span><span class="o">=</span><span class="n">exec_q</span>
     <span class="p">)</span>

pulls/1869/beginners_guides/installation.html

@@ -881,7 +881,7 @@ <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 v0.17.0dev0+55.ga374258727)"><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 v0.17.0dev0+56.ga42a87f89f7)"><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>