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@@ -402,7 +402,7 @@ <h1>Source code for torch_xla.core.xla_model</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span> <span class="nf">parse_xla_device</span><span class="p">(</span><span class="n">device</span><span class="p">):</span>
-  <span class="n">m</span> <span class="o">=</span> <span class="n">re</span><span class="o">.</span><span class="n">match</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;(CPU|TPU|GPU|ROCM|CUDA|XPU|NEURON):(\d+)$&#39;</span><span class="p">,</span> <span class="n">device</span><span class="p">)</span>
+  <span class="n">m</span> <span class="o">=</span> <span class="n">re</span><span class="o">.</span><span class="n">match</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;([A-Z]+):(\d+)$&#39;</span><span class="p">,</span> <span class="n">device</span><span class="p">)</span>
   <span class="k">if</span> <span class="n">m</span><span class="p">:</span>
     <span class="k">return</span> <span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">group</span><span class="p">(</span><span class="mi">1</span><span class="p">),</span> <span class="nb">int</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">group</span><span class="p">(</span><span class="mi">2</span><span class="p">)))</span>
 
@@ -411,32 +411,33 @@ <h1>Source code for torch_xla.core.xla_model</h1><div class="highlight"><pre>
 <span class="w">  </span><span class="sd">&quot;&quot;&quot;Returns a list of supported devices of a given kind.</span>
 
 <span class="sd">  Args:</span>
-<span class="sd">    devkind (string..., optional): If specified, one of `TPU`, `GPU`, `XPU`,</span>
-<span class="sd">      `NEURON` or `CPU` (the &#39;GPU&#39; XLA device is currently not implemented).</span>
+<span class="sd">    devkind (string..., optional): If specified, a device type such as `TPU`,</span>
+<span class="sd">      `CUDA`, `CPU`, or name of custom PJRT device.</span>
 <span class="sd">    max_devices (int, optional): The maximum number of devices to be returned of</span>
 <span class="sd">      that kind.</span>
 
 <span class="sd">  Returns:</span>
 <span class="sd">    The list of device strings.</span>
 <span class="sd">  &quot;&quot;&quot;</span>
-  <span class="c1"># TODO(xiowei replace gpu with cuda): Remove the below if statement after r2.2 release.</span>
-  <span class="k">if</span> <span class="n">devkind</span> <span class="ow">and</span> <span class="n">devkind</span><span class="o">.</span><span class="n">casefold</span><span class="p">()</span> <span class="o">==</span> <span class="s1">&#39;gpu&#39;</span><span class="p">:</span>
-    <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
-        <span class="s2">&quot;GPU as a device name is being deprecate. Please replace it with CUDA such as get_xla_supported_devices(devkind=&#39;CUDA&#39;). Similarly, please replace PJRT_DEVICE=GPU with PJRT_DEVICE=CUDA.&quot;</span>
-    <span class="p">)</span>
-    <span class="n">devkind</span> <span class="o">=</span> <span class="s1">&#39;CUDA&#39;</span>
+  <span class="c1"># TODO(wcromar): Remove `devkind` after 2.3 release cut. We no longer support</span>
+  <span class="c1"># multiple device types.</span>
+  <span class="k">if</span> <span class="ow">not</span> <span class="n">devkind</span><span class="p">:</span>
+    <span class="n">devices</span> <span class="o">=</span> <span class="n">torch_xla</span><span class="o">.</span><span class="n">_XLAC</span><span class="o">.</span><span class="n">_xla_get_devices</span><span class="p">()</span>
+    <span class="k">return</span> <span class="p">[</span>
+        <span class="sa">f</span><span class="s1">&#39;xla:</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s1">&#39;</span>
+        <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">devices</span><span class="p">[:</span><span class="n">max_devices</span><span class="p">]</span> <span class="k">if</span> <span class="n">max_devices</span> <span class="k">else</span> <span class="n">devices</span><span class="p">)</span>
+    <span class="p">]</span>
+  <span class="k">else</span><span class="p">:</span>
+    <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s2">&quot;`devkind` argument is deprecated and will be removed in a &quot;</span>
+                  <span class="s2">&quot;future release.&quot;</span><span class="p">)</span>
 
   <span class="n">xla_devices</span> <span class="o">=</span> <span class="n">_DEVICES</span><span class="o">.</span><span class="n">value</span>
-  <span class="n">devkind</span> <span class="o">=</span> <span class="p">[</span><span class="n">devkind</span><span class="p">]</span> <span class="k">if</span> <span class="n">devkind</span> <span class="k">else</span> <span class="p">[</span>
-      <span class="s1">&#39;TPU&#39;</span><span class="p">,</span> <span class="s1">&#39;GPU&#39;</span><span class="p">,</span> <span class="s1">&#39;XPU&#39;</span><span class="p">,</span> <span class="s1">&#39;NEURON&#39;</span><span class="p">,</span> <span class="s1">&#39;CPU&#39;</span><span class="p">,</span> <span class="s1">&#39;CUDA&#39;</span><span class="p">,</span> <span class="s1">&#39;ROCM&#39;</span>
-  <span class="p">]</span>
-  <span class="k">for</span> <span class="n">kind</span> <span class="ow">in</span> <span class="n">devkind</span><span class="p">:</span>
-    <span class="n">kind_devices</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">device</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">xla_devices</span><span class="p">):</span>
-      <span class="k">if</span> <span class="n">re</span><span class="o">.</span><span class="n">match</span><span class="p">(</span><span class="n">kind</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;:\d+$&#39;</span><span class="p">,</span> <span class="n">device</span><span class="p">):</span>
-        <span class="n">kind_devices</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;xla:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">i</span><span class="p">))</span>
-    <span class="k">if</span> <span class="n">kind_devices</span><span class="p">:</span>
-      <span class="k">return</span> <span class="n">kind_devices</span><span class="p">[:</span><span class="n">max_devices</span><span class="p">]</span> <span class="k">if</span> <span class="n">max_devices</span> <span class="k">else</span> <span class="n">kind_devices</span></div>
+  <span class="n">kind_devices</span> <span class="o">=</span> <span class="p">[]</span>
+  <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">device</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">xla_devices</span><span class="p">):</span>
+    <span class="k">if</span> <span class="n">re</span><span class="o">.</span><span class="n">match</span><span class="p">(</span><span class="n">devkind</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;:\d+$&#39;</span><span class="p">,</span> <span class="n">device</span><span class="p">):</span>
+      <span class="n">kind_devices</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s1">&#39;xla:</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">i</span><span class="p">))</span>
+  <span class="k">if</span> <span class="n">kind_devices</span><span class="p">:</span>
+    <span class="k">return</span> <span class="n">kind_devices</span><span class="p">[:</span><span class="n">max_devices</span><span class="p">]</span> <span class="k">if</span> <span class="n">max_devices</span> <span class="k">else</span> <span class="n">kind_devices</span></div>
 
 
 <div class="viewcode-block" id="xrt_world_size"><a class="viewcode-back" href="../../../index.html#torch_xla.core.xla_model.xrt_world_size">[docs]</a><span class="k">def</span> <span class="nf">xrt_world_size</span><span class="p">(</span><span class="n">defval</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
@@ -521,8 +522,8 @@ <h1>Source code for torch_xla.core.xla_model</h1><div class="highlight"><pre>
 <span class="sd">    n (int, optional): The specific instance (ordinal) to be returned. If</span>
 <span class="sd">      specified, the specific XLA device instance will be returned. Otherwise</span>
 <span class="sd">      the first device of `devkind` will be returned.</span>
-<span class="sd">    devkind (string..., optional): If specified, one of `TPU`, `CUDA`, `XPU`</span>
-<span class="sd">      `NEURON`, `ROCM` or `CPU`.</span>
+<span class="sd">    devkind (string..., optional): If specified, device type such as `TPU`,</span>
+<span class="sd">      `CUDA`, `CPU`, or custom PJRT device. Deprecated.</span>
 
 <span class="sd">  Returns:</span>
 <span class="sd">    A `torch.device` with the requested instance.</span>
@@ -560,8 +561,7 @@ <h1>Source code for torch_xla.core.xla_model</h1><div class="highlight"><pre>
 <span class="sd">      real device.</span>
 
 <span class="sd">  Returns:</span>
-<span class="sd">    A string representation of the hardware type (`CPU`, `TPU`, `XPU`, `NEURON`, `GPU`, `CUDA`, `ROCM`)</span>
-<span class="sd">    of the given device.</span>
+<span class="sd">    A string representation of the hardware type of the given device.</span>
 <span class="sd">  &quot;&quot;&quot;</span>
   <span class="n">real_device</span> <span class="o">=</span> <span class="n">_xla_real_device</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
   <span class="k">return</span> <span class="n">real_device</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;:&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span></div>
@@ -888,8 +888,8 @@ <h1>Source code for torch_xla.core.xla_model</h1><div class="highlight"><pre>
 <span class="sd">  &quot;&quot;&quot;</span>
   <span class="c1"># _all_gather_using_all_reduce does not support list of tensors as input</span>
   <span class="k">if</span> <span class="n">pin_layout</span> <span class="ow">and</span> <span class="n">output</span> <span class="o">==</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span>
-    <span class="c1"># There is not an easy way to pin the all_gather layout on TPU, GPU and NEURON,</span>
-    <span class="c1"># use all_reduce based all_gather for this purpose.</span>
+    <span class="c1"># There is not an easy way to pin the all_gather layout, so use all_reduce</span>
+    <span class="c1"># based all_gather for this purpose.</span>
     <span class="k">return</span> <span class="n">_all_gather_using_all_reduce</span><span class="p">(</span>
         <span class="n">value</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="n">dim</span><span class="p">,</span> <span class="n">groups</span><span class="o">=</span><span class="n">groups</span><span class="p">,</span> <span class="n">pin_layout</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 

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@@ -826,8 +826,8 @@ <h1>PyTorch/XLA API<a class="headerlink" href="#pytorch-xla-api" title="Permalin
 <li><p><strong>n</strong> (<em>python:int</em><em>, </em><em>optional</em>) – The specific instance (ordinal) to be returned. If
 specified, the specific XLA device instance will be returned. Otherwise
 the first device of <cite>devkind</cite> will be returned.</p></li>
-<li><p><strong>devkind</strong> (<em>string...</em><em>, </em><em>optional</em>) – If specified, one of <cite>TPU</cite>, <cite>CUDA</cite>, <cite>XPU</cite>
-<cite>NEURON</cite>, <cite>ROCM</cite> or <cite>CPU</cite>.</p></li>
+<li><p><strong>devkind</strong> (<em>string...</em><em>, </em><em>optional</em>) – If specified, device type such as <cite>TPU</cite>,
+<cite>CUDA</cite>, <cite>CPU</cite>, or custom PJRT device. Deprecated.</p></li>
 </ul>
 </dd>
 <dt class="field-even">Returns</dt>
@@ -843,8 +843,8 @@ <h1>PyTorch/XLA API<a class="headerlink" href="#pytorch-xla-api" title="Permalin
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>devkind</strong> (<em>string...</em><em>, </em><em>optional</em>) – If specified, one of <cite>TPU</cite>, <cite>GPU</cite>, <cite>XPU</cite>,
-<cite>NEURON</cite> or <cite>CPU</cite> (the ‘GPU’ XLA device is currently not implemented).</p></li>
+<li><p><strong>devkind</strong> (<em>string...</em><em>, </em><em>optional</em>) – If specified, a device type such as <cite>TPU</cite>,
+<cite>CUDA</cite>, <cite>CPU</cite>, or name of custom PJRT device.</p></li>
 <li><p><strong>max_devices</strong> (<em>python:int</em><em>, </em><em>optional</em>) – The maximum number of devices to be returned of
 that kind.</p></li>
 </ul>
@@ -865,8 +865,7 @@ <h1>PyTorch/XLA API<a class="headerlink" href="#pytorch-xla-api" title="Permalin
 real device.</p>
 </dd>
 <dt class="field-even">Returns</dt>
-<dd class="field-even"><p>A string representation of the hardware type (<cite>CPU</cite>, <cite>TPU</cite>, <cite>XPU</cite>, <cite>NEURON</cite>, <cite>GPU</cite>, <cite>CUDA</cite>, <cite>ROCM</cite>)
-of the given device.</p>
+<dd class="field-even"><p>A string representation of the hardware type of the given device.</p>
 </dd>
 </dl>
 </dd></dl>

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