title: "Kernel appears to have died" error when I try to train my model. Is it too big? What could be the issue?
body: <p>None of the other solutions to this question on here have worked for me. </p>
  
  <p>I am trying to train a model on a Jupiter notebook on amazon Sagemaker instance ml.c4.8xlarge with 15,000GB memory. However, this error keeps coming up when I run train. The model is as follows:</p>
  
  <pre><code>model = Sequential()
  model.add(Embedding(vocab_size, 200, input_length=max_length))
  model.add(GRU(units=400,  dropout=0.2, recurrent_dropout=0.2))
  model.add(Dense(800, activation='sigmoid'))
  model.add(Dense(400, activation='sigmoid'))
  model.add(Dense(200, activation='sigmoid'))
  model.add(Dense(100, activation='sigmoid'))
  model.add(Dense(50, activation='sigmoid'))
  model.add(Dense(20, activation='sigmoid'))
  model.add(Dense(10, activation='sigmoid'))
  model.add(Dense(5, activation='sigmoid'))
  model.add(Dense(1, activation='sigmoid'))
  </code></pre>
  
  <p>With the following summary:
  <a href="https://i.stack.imgur.com/Swx1W.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Swx1W.png" alt="enter image description here"></a></p>
  
  <p>Is the model too big? Do I not have enough space to run it or could it be some other issue?</p>