Docs for pull request 2118

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

pulls/2118/_modules/dpctl/tensor/_copy_utils.html

@@ -166,14 +166,27 @@ A full list of available SYCL alias targets is available in the
 CUDA build
 ~~~~~~~~~~
 
-``dpctl`` can be built for CUDA devices using the ``DPCTL_TARGET_CUDA`` CMake option,
-which accepts a specific compute architecture string:
+``dpctl`` can be built for CUDA devices using the  ``--target-cuda`` argument.
+
+To target a specific architecture (e.g., ``sm_80``):
+
+.. code-block:: bash
+
+    python scripts/build_locally.py --verbose --target-cuda=sm_80
+
+To use the default architecture (``sm_50``), omit the value:
+
+.. code-block:: bash
+
+    python scripts/build_locally.py --verbose --target-cuda
+
+Alternatively, you can use the ``DPCTL_TARGET_CUDA`` CMake option:
 
 .. code-block:: bash
 
     python scripts/build_locally.py --verbose --cmake-opts="-DDPCTL_TARGET_CUDA=sm_80"
 
-To use the default architecture (``sm_50``),
+To use the default architecture (``sm_50``) with CMake options,
 set ``DPCTL_TARGET_CUDA`` to a value such as ``ON``, ``TRUE``, ``YES``, ``Y``, or ``1``:
 
 .. code-block:: bash
@@ -192,12 +205,11 @@ Compute Capabilities can be found in the official
 AMD build
 ~~~~~~~~~
 
-``dpctl`` can be built for AMD devices using the ``DPCTL_TARGET_HIP`` CMake option,
-which requires specifying a compute architecture string:
+``dpctl`` can be built for AMD devices using the  ``--target-hip`` argument.
 
 .. code-block:: bash
 
-    python scripts/build_locally.py --verbose --cmake-opts="-DDPCTL_TARGET_HIP=<arch>"
+    python scripts/build_locally.py --verbose --target-hip=<arch>
 
 Note that the `oneAPI for AMD GPUs` plugin requires the architecture be specified and only
 one architecture can be specified at a time.
@@ -208,11 +220,17 @@ To determine the architecture code (``<arch>``) for your AMD GPU, run:
     rocminfo | grep 'Name: *gfx.*'
 
 This will print names like ``gfx90a``, ``gfx1030``, etc.
-You can then use one of them as the argument to ``-DDPCTL_TARGET_HIP``.
+You can then use one of them as the argument to ``--target-hip``.
 
 For example:
 
 .. code-block:: bash
+    python scripts/build_locally.py --verbose --target-hip=gfx1030
+
+Alternatively, you can use the ``DPCTL_TARGET_HIP`` CMake option:
+
+.. code-block:: bash
+
     python scripts/build_locally.py --verbose --cmake-opts="-DDPCTL_TARGET_HIP=gfx1030"
 
 Multi-target build
@@ -225,8 +243,7 @@ devices at the same time:
 
 .. code-block:: bash
 
-    python scripts/build_locally.py --verbose --cmake-opts="-DDPCTL_TARGET_CUDA=ON \
-    -DDPCTL_TARGET_HIP=gfx1030"
+    python scripts/build_locally.py --verbose --target-cuda --target-hip=gfx1030
 
 Running Examples and Tests
 ==========================

pulls/2118/_sources/beginners_guides/installation.rst.txt

@@ -807,8 +807,8 @@ <h1>dpctl.tensor.usm_ndarray.__dlpack_device__<a class="headerlink" href="#dpctl
 <p>The tuple describes the non-partitioned device where the array has been
 allocated, or the non-partitioned parent device of the allocation
 device.</p>
-<p>See <code class="docutils literal notranslate"><span class="pre">DLDeviceType</span></code> for a list of devices supported by the DLPack
-protocol.</p>
+<p>See <a class="reference internal" href="../../tensor.constants.html#dpctl.tensor.DLDeviceType" title="dpctl.tensor.DLDeviceType"><code class="xref py py-class docutils literal notranslate"><span class="pre">dpctl.tensor.DLDeviceType</span></code></a> for a list of devices supported
+by the DLPack protocol.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Raises<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>DLPackCreationError</strong> – when the <code class="docutils literal notranslate"><span class="pre">device_id</span></code> could not be determined.</p>

pulls/2118/api_reference/dpctl/generated/generated/dpctl.tensor.usm_ndarray.__dlpack_device__.html

@@ -867,7 +867,7 @@ <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 v0.19.0dev1+15.g876e9403a7e)"><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 v0.19.0dev2+1.g30918e48741)"><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>
@@ -937,12 +937,20 @@ <h3>Building for custom SYCL targets<a class="headerlink" href="#building-for-cu
 <a class="reference external" href="https://intel.github.io/llvm/UsersManual.html">DPC++ Compiler User Manual</a>.</p>
 <section id="cuda-build">
 <h4>CUDA build<a class="headerlink" href="#cuda-build" title="Permalink to this heading">¶</a></h4>
-<p><code class="docutils literal notranslate"><span class="pre">dpctl</span></code> can be built for CUDA devices using the <code class="docutils literal notranslate"><span class="pre">DPCTL_TARGET_CUDA</span></code> CMake option,
-which accepts a specific compute architecture string:</p>
+<p><code class="docutils literal notranslate"><span class="pre">dpctl</span></code> can be built for CUDA devices using the  <code class="docutils literal notranslate"><span class="pre">--target-cuda</span></code> argument.</p>
+<p>To target a specific architecture (e.g., <code class="docutils literal notranslate"><span class="pre">sm_80</span></code>):</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--target-cuda<span class="o">=</span>sm_80
+</pre></div>
+</div>
+<p>To use the default architecture (<code class="docutils literal notranslate"><span class="pre">sm_50</span></code>), omit the value:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--target-cuda
+</pre></div>
+</div>
+<p>Alternatively, you can use the <code class="docutils literal notranslate"><span class="pre">DPCTL_TARGET_CUDA</span></code> CMake option:</p>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_CUDA=sm_80&quot;</span>
 </pre></div>
 </div>
-<p>To use the default architecture (<code class="docutils literal notranslate"><span class="pre">sm_50</span></code>),
+<p>To use the default architecture (<code class="docutils literal notranslate"><span class="pre">sm_50</span></code>) with CMake options,
 set <code class="docutils literal notranslate"><span class="pre">DPCTL_TARGET_CUDA</span></code> to a value such as <code class="docutils literal notranslate"><span class="pre">ON</span></code>, <code class="docutils literal notranslate"><span class="pre">TRUE</span></code>, <code class="docutils literal notranslate"><span class="pre">YES</span></code>, <code class="docutils literal notranslate"><span class="pre">Y</span></code>, or <code class="docutils literal notranslate"><span class="pre">1</span></code>:</p>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_CUDA=ON&quot;</span>
 </pre></div>
@@ -957,26 +965,28 @@ <h4>CUDA build<a class="headerlink" href="#cuda-build" title="Permalink to this
 </section>
 <section id="amd-build">
 <h4>AMD build<a class="headerlink" href="#amd-build" title="Permalink to this heading">¶</a></h4>
-<p><code class="docutils literal notranslate"><span class="pre">dpctl</span></code> can be built for AMD devices using the <code class="docutils literal notranslate"><span class="pre">DPCTL_TARGET_HIP</span></code> CMake option,
-which requires specifying a compute architecture string:</p>
-<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_HIP=&lt;arch&gt;&quot;</span>
+<p><code class="docutils literal notranslate"><span class="pre">dpctl</span></code> can be built for AMD devices using the  <code class="docutils literal notranslate"><span class="pre">--target-hip</span></code> argument.</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--target-hip<span class="o">=</span>&lt;arch&gt;
 </pre></div>
 </div>
 <p>Note that the <cite>oneAPI for AMD GPUs</cite> plugin requires the architecture be specified and only
 one architecture can be specified at a time.</p>
 <p>To determine the architecture code (<code class="docutils literal notranslate"><span class="pre">&lt;arch&gt;</span></code>) for your AMD GPU, run:</p>
 <p>This will print names like <code class="docutils literal notranslate"><span class="pre">gfx90a</span></code>, <code class="docutils literal notranslate"><span class="pre">gfx1030</span></code>, etc.
-You can then use one of them as the argument to <code class="docutils literal notranslate"><span class="pre">-DDPCTL_TARGET_HIP</span></code>.</p>
+You can then use one of them as the argument to <code class="docutils literal notranslate"><span class="pre">--target-hip</span></code>.</p>
 <p>For example:</p>
+<p>Alternatively, you can use the <code class="docutils literal notranslate"><span class="pre">DPCTL_TARGET_HIP</span></code> CMake option:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_HIP=gfx1030&quot;</span>
+</pre></div>
+</div>
 </section>
 <section id="multi-target-build">
 <h4>Multi-target build<a class="headerlink" href="#multi-target-build" title="Permalink to this heading">¶</a></h4>
 <p>The default <code class="docutils literal notranslate"><span class="pre">dpctl</span></code> build from the source enables support of Intel devices only.
 Extending the build with a custom SYCL target additionally enables support of CUDA or AMD
 device in <code class="docutils literal notranslate"><span class="pre">dpctl</span></code>. Besides, the support can be also extended to enable both CUDA and AMD
 devices at the same time:</p>
-<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_CUDA=ON \</span>
-<span class="s2">-DDPCTL_TARGET_HIP=gfx1030&quot;</span>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--target-cuda<span class="w"> </span>--target-hip<span class="o">=</span>gfx1030
 </pre></div>
 </div>
 </section>