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pytorch · Oct 30, 2024 · c8545d4 · c8545d4
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@@ -1722,9 +1722,10 @@ <h1>Source code for torch_xla.core.xla_model</h1><div class="highlight"><pre>
         <span class="k">if</span> <span class="n">sharding</span> <span class="ow">and</span> <span class="n">tensor</span><span class="o">.</span><span class="n">dim</span><span class="p">()</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="p">(</span><span class="n">tensor</span><span class="o">.</span><span class="n">size</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span> <span class="o">%</span>
                                               <span class="n">local_runtime_device_count</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
           <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
-              <span class="s2">&quot;When minibatch is configured, the per-host batch size must be divisible &quot;</span>
-              <span class="o">+</span> <span class="s2">&quot;by local runtime device count. Per host input data shape &quot;</span> <span class="o">+</span>
-              <span class="sa">f</span><span class="s2">&quot;= </span><span class="si">{</span><span class="n">tensor</span><span class="o">.</span><span class="n">size</span><span class="p">()</span><span class="si">}</span><span class="s2">, local_runtime_device_count = </span><span class="si">{</span><span class="n">local_runtime_device_count</span><span class="si">}</span><span class="s2">&quot;</span>
+              <span class="s2">&quot;When minibatch is configured, batch dimension of the tensor &quot;</span> <span class="o">+</span>
+              <span class="s2">&quot;must be divisible by local runtime device count.input data shape &quot;</span>
+              <span class="o">+</span>
+              <span class="sa">f</span><span class="s2">&quot;=</span><span class="si">{</span><span class="n">tensor</span><span class="o">.</span><span class="n">size</span><span class="p">()</span><span class="si">}</span><span class="s2">, local_runtime_device_count = </span><span class="si">{</span><span class="n">local_runtime_device_count</span><span class="si">}</span><span class="s2">&quot;</span>
           <span class="p">)</span>
 
     <span class="n">xtensors</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_tensors_from_aten</span><span class="p">(</span><span class="n">tensors</span><span class="p">,</span> <span class="n">devices</span><span class="p">,</span>

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