title: How do I configure my jupyter notebook so that it uses the available GPU while working with keras?
body: <p>I searched for solutions and installed tensorflow-gpu with pip.</p>
  <pre><code>tf.config.list_physical_devices('GPU')
  </code></pre>
  <p>This code returns an empty list. <code>[]</code></p>
  <p><a href="https://i.stack.imgur.com/rPNBV.png" rel="nofollow noreferrer">You can see I have 2 GPUs but none of them are being used when I am doing image processing(CNN) with keras.</a></p>
  <p>I am new to things so don't understand exactly what is wrong. Please help me configure so that I can use my GPU for processing. I am working with Windows 10 64-bit, Python-3.8.7.
  As suggested, I tried importing tensorflow on python terminal, and got the following error:</p>
  <pre><code>import tensorflow as tf
  </code></pre>
  <blockquote>
  <p>2021-02-13 22:52:17.253841: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
  2021-02-13 22:52:17.266384: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.</p>
  </blockquote>
  <p>Followed by this when I tried listing the GPUs:
  <code>tf.config.list_physical_devices('GPU')</code></p>
  <blockquote>
  <p>2021-02-13 22:57:17.390319: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
  2021-02-13 22:57:17.749790: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
  2021-02-13 22:57:18.937838: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
  pciBusID: 0000:01:00.0 name: <strong>GeForce MX150</strong> computeCapability: 6.1
  coreClock: 1.5315GHz coreCount: 3 deviceMemorySize: 2.00GiB deviceMemoryBandwidth: 44.76GiB/s
  2021-02-13 22:57:18.966071: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
  2021-02-13 22:57:18.974209: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found
  2021-02-13 22:57:18.981154: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found
  2021-02-13 22:57:18.988826: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
  2021-02-13 22:57:18.996411: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
  2021-02-13 22:57:19.002563: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
  2021-02-13 22:57:19.009636: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found
  2021-02-13 22:57:19.018025: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
  2021-02-13 22:57:19.025064: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at <a href="https://www.tensorflow.org/install/gpu" rel="nofollow noreferrer">https://www.tensorflow.org/install/gpu</a> for how to download and setup the required libraries for your platform.
  Skipping registering GPU devices...
  []</p>
  </blockquote>