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Docs for pull request 1923
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pulls/1923/_modules/dpctl/tensor/_copy_utils.html

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@@ -1484,9 +1484,13 @@ <h1>Source code for dpctl.tensor._copy_utils</h1><div class="highlight"><pre>
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<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>
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<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>
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<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>
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<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>
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<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>
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<span class="p">)</span>
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<span class="c1"># ensure that order=&quot;F&quot; for C-contig input triggers copy,</span>
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<span class="c1"># and order=&quot;C&quot; for F-contig input triggers copy too.</span>
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<span class="c1"># 1D arrays which are both C- and F- contig should not</span>
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<span class="c1"># force copying for neither order=&quot;F&quot;, nor order=&quot;C&quot;, see gh-1926</span>
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<span class="n">needs_copy</span> <span class="o">=</span> <span class="p">(</span>
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<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>
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<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>
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<span class="k">if</span> <span class="ow">not</span> <span class="n">needs_copy</span><span class="p">:</span>
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<span class="k">return</span> <span class="n">usm_ary</span>
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<span class="n">copy_order</span> <span class="o">=</span> <span class="s2">&quot;C&quot;</span>

pulls/1923/beginners_guides/installation.html

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@@ -881,7 +881,7 @@ <h2>Installation using pip<a class="headerlink" href="#installation-using-pip" t
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<section id="installation-via-intel-r-distribution-for-python">
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<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>
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<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
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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+8.g0bfe1e370e1)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpnp</span></code></a>
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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+11.g48babd065d9)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpnp</span></code></a>
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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>
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<p>Once the installed environment is activated, <code class="docutils literal notranslate"><span class="pre">dpctl</span></code> should be ready to use.</p>
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</section>

pulls/1923/objects.inv

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