title: Tensorflow 2.3.0 CUDA Toolkit version 10.1 does not use GPU
body: <p>I had tensorflow 2.0 workig with my RTX2070 gpu. I did a windows update so I could use tf-nightly. Did not like it so uninstalled it and reinstalled tensorflow 2.3.0. Ran previous python code that ran fine with GPU previously but it did not use the GPU. Tried lots of stuff. Finally just started over. Reinstalled Anaconda, created new environment. Uninstalled Cuda toolkit 10.1 and reinstalled it. Installed cuDnn SDK 7.6 in directory c:\Tools. Checked path env variable to include</p>
  <pre><code>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin;
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\extras\CUPTI\lib64;
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include;
  C:\tools\cuda\bin;%PATH%
         #then ran this code:
  import tensorflow as tf
  from tensorflow.python.client import device_lib
  print(device_lib.list_local_devices())
  print(tf.__version__)
  print(&quot;Num GPUs Available: &quot;, len(tf.config.experimental.list_physical_devices('GPU')))
  tf.test.is_gpu_available()
       #I get the result
  [name: &quot;/device:CPU:0&quot;
  device_type: &quot;CPU&quot;
  memory_limit: 268435456
  locality {
  }
  incarnation: 15177607927005893519
  , name: &quot;/device:XLA_CPU:0&quot;
  device_type: &quot;XLA_CPU&quot;
  memory_limit: 17179869184
  locality {
  }
  incarnation: 4640072765546557805
  physical_device_desc: &quot;device: XLA_CPU device&quot;
  , name: &quot;/device:XLA_GPU:0&quot;
  device_type: &quot;XLA_GPU&quot;
  memory_limit: 17179869184
  locality {
  }
  incarnation: 16675502319763286567
  physical_device_desc: &quot;device: XLA_GPU device&quot;
  ]
  2.3.0
  Num GPUs Available:  0
  
  False
  
  tensorflow still does not use GPU. What an I missing? 
  
  also same problem using python 3.7.0 and same problem using tensorflow 2.0.0
  
  
  </code></pre>