title: Is it possible to run tensorflow-gpu on a computer without a GPU or CUDA?
body: <p>I have two Windows computers, one with and one without a GPU. </p>
  
  <p>I would like to deploy the same python script on both (TensorFlow 1.8 Object Detection), without changing the packaged version of TensorFlow. In other words, I want to run tensorflow-gpu on a CPU. </p>
  
  <p>In the event where my script cannot detect <code>nvcuda.dll</code>, I've tried using a Session config to disable the GPU, like so:</p>
  
  <pre><code>config = tf.ConfigProto(
      device_count = {'GPU': 0}
  )
  </code></pre>
  
  <p>and:</p>
  
  <pre><code>with tf.Session(graph=detection_graph, config=config) as sess:
  </code></pre>
  
  <p>However, this is not sufficient, as TensorFlow still returns the error:</p>
  
  <pre><code>ImportError: Could not find 'nvcuda.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable.
  Typically it is installed in 'C:\Windows\System32'. If it is not present, ensure that you have a CUDA-capable GPU with the correct driver installed.
  </code></pre>
  
  <p>Is there any way to disable checking for a GPU/CUDA entirely and default to CPU?</p>
  
  <p><strong>EDIT:</strong> I have read the year-old answer regarding tensorflow-gpu==1.0 on Linux <a href="https://stackoverflow.com/a/42287754/9291214">posted here</a>, which suggests this is impossible. I'm interested to know if this is still how tensorflow-gpu is compiled, 9 versions later.</p>