title: CuDNN version does not match
body: <p>I am very close to configuring a gpu enabled environment using the keras/tensorflow python library.  When I try to train my model I get a long error message:</p>
  
  <pre><code>2018-11-27 18:34:47.776387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
  2018-11-27 18:34:48.769258: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
  2018-11-27 18:34:48.769471: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988]      0 
  2018-11-27 18:34:48.769595: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0:   N 
  2018-11-27 18:34:48.769825: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3024 MB memory) -&gt; physical GPU (device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
  2018-11-27 18:34:50.405201: E tensorflow/stream_executor/cuda/cuda_dnn.cc:363] Loaded runtime CuDNN library: 7.1.4 but source was compiled with: 7.2.1.  CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library.  If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
  </code></pre>
  
  <p>I've looked at a couple similar stack overflow posts and it appears that I need to either adjust the CuDNN version or the tensorflow-gpu version.  I downloaded the correct version of CuDNN from Nvidia's website but it did not appear to do anything.  I have also found several posts about changing my tensorflow-gpu version, but WHICH version should I download and HOW.  I am using WIndows 10.</p>