title: expected ndim=3, found ndim=2
body: <p>I'm new with Keras and I'm trying to implement a Sequence to Sequence LSTM. 
  Particularly, I have a dataset with 9 features and I want to predict 5 continuous values. </p>
  
  <p>I split the training and the test set and their shape are respectively:</p>
  
  <pre><code>X TRAIN (59010, 9)
  
  X TEST (25291, 9)
  
  Y TRAIN (59010, 5)
  
  Y TEST (25291, 5)
  </code></pre>
  
  <p>The LSTM is extremely simple at the moment:</p>
  
  <pre><code>model = Sequential()
  model.add(LSTM(100, input_shape=(9,), return_sequences=True))
  model.compile(loss="mean_absolute_error", optimizer="adam", metrics= ['accuracy'])
  
  history = model.fit(X_train,y_train,epochs=100, validation_data=(X_test,y_test))
  </code></pre>
  
  <p>But I have the following error:</p>
  
  <blockquote>
    <p>ValueError: Input 0 is incompatible with layer lstm_1: expected
    ndim=3, found ndim=2</p>
  </blockquote>
  
  <p>Can anyone help me?</p>