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      <h1 data-toc-skip>Troubleshooting</h1>
            
      
      <small class="dont-index">Source: <a href="https://github.com/fdavidcl/ruta/blob/HEAD/vignettes/troubleshooting.Rmd" class="external-link"><code>vignettes/troubleshooting.Rmd</code></a></small>
      <div class="hidden name"><code>troubleshooting.Rmd</code></div>

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<p>This article gathers some common problems users may encounter while
installing or using Ruta.</p>
<div class="section level2">
<h2 id="using-ruta-with-condaenvs">Using Ruta with condaenvs<a class="anchor" aria-label="anchor" href="#using-ruta-with-condaenvs"></a>
</h2>
<p>If you are using Ruta over an Anaconda installation, you will need to
choose the correct conda environment where Tensorflow and Keras are
installed. To do this, you can try asking reticulate to use it (replace
<code>"deeplearning"</code> with the name of your condaenv):</p>
<pre><code><span><span class="fu">reticulate</span><span class="fu">::</span><span class="fu"><a href="https://rstudio.github.io/reticulate/reference/use_python.html" class="external-link">use_condaenv</a></span><span class="op">(</span><span class="st">"deeplearning"</span>, required <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre>
<p>If reticulate still uses a different Python installation, you can opt
to set the <code>RETICULATE_PYTHON</code> environment variable
<strong>before</strong> reticulate is initialized. That is, in a new R
session, execute the following command:</p>
<pre><code><span><span class="fu"><a href="https://rdrr.io/r/base/Sys.setenv.html" class="external-link">Sys.setenv</a></span><span class="op">(</span>RETICULATE_PYTHON <span class="op">=</span> <span class="va">PATH</span><span class="op">)</span></span></code></pre>
<p>where <code>PATH</code> is the path to the convenient Python
executable (you can discover this path by looking at available versions
in <code><a href="https://rstudio.github.io/reticulate/reference/py_config.html" class="external-link">reticulate::py_config()</a></code>).</p>
</div>
<div class="section level2">
<h2 id="cuda-error-cublas_status_not_initialized">CUDA error: <code>CUBLAS_STATUS_NOT_INITIALIZED</code><a class="anchor" aria-label="anchor" href="#cuda-error-cublas_status_not_initialized"></a>
</h2>
<p>Reset your R session and try allowing Tensorflow to grow the size of
allocated memory:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">config</span> <span class="op">=</span> <span class="fu">tensorflow</span><span class="fu">::</span><span class="va"><a href="https://rdrr.io/pkg/tensorflow/man/tf.html" class="external-link">tf</a></span><span class="op">$</span><span class="fu">ConfigProto</span><span class="op">(</span>gpu_options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>allow_growth <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="va">sess</span> <span class="op">=</span> <span class="fu">tensorflow</span><span class="fu">::</span><span class="va"><a href="https://rdrr.io/pkg/tensorflow/man/tf.html" class="external-link">tf</a></span><span class="op">$</span><span class="fu">Session</span><span class="op">(</span>config <span class="op">=</span> <span class="va">config</span><span class="op">)</span></span>
<span><span class="fu">keras</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/keras/man/k_get_session.html" class="external-link">k_set_session</a></span><span class="op">(</span>session <span class="op">=</span> <span class="va">sess</span><span class="op">)</span></span></code></pre></div>
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