title: Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
body: <p>I am doing a Docker build in mt computer where NVDIA GPU is not available. I use tensorflow/tensorflow Docker image as the base image with CPU.</p>
  
  <p>Dockerfile</p>
  
  <pre><code>FROM tensorflow/tensorflow 
  WORKDIR /project
  COPY /app .
  RUN python3 main.py
  </code></pre>
  
  <p>But it shows an error</p>
  
  <pre><code>2020-06-12 20:06:56.822576: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
  2020-06-12 20:06:56.825090: E tensorflow/stream_executor/cuda/cuda_driver.cc:313] failed call to cuInit: UNKNOWN ERROR (303)
  2020-06-12 20:06:56.827746: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (735abddf4141): /proc/driver/nvidia/version does not exist
  2020-06-12 20:06:56.837312: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
  2020-06-12 20:06:57.040593: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 2400000000 Hz
  2020-06-12 20:06:57.045853: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f377c000b20 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
  2020-06-12 20:06:57.045913: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
  2020-06-12 20:07:07.017642: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 614400000 exceeds 10% of free system memory.
  Killed
  </code></pre>
  
  <p>at running this code</p>
  
  <pre><code>model = tf.keras.models.Sequential([
                          tf.keras.layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)),
                          tf.keras.layers.MaxPooling2D(2, 2),
                          tf.keras.layers.Conv2D(64, (3, 3), activation='relu'),
                          tf.keras.layers.MaxPooling2D(2, 2),
                          tf.keras.layers.Conv2D(64, (3, 3), activation='relu'),
                          tf.keras.layers.Flatten(),
                          tf.keras.layers.Dense(128, activation='relu'),
                          tf.keras.layers.Dense(10, activation='softmax')])
  </code></pre>
  
  <p>I don't want to use GPU version. I need to run this with CPU.</p>