title: Shape Erorr when using Bidirectional instead of standard LSTM layer
body: <p>When switching to a Bidirectional layer my code gives an error. The model works when using the standard LSTM layers. The error I got is:</p>
  
  <pre><code>File "&lt;ipython-input-22-1e9000cb0bf6&gt;", line 12, in &lt;module&gt;
  model.build(input_shape)
  ValueError: Input 0 is incompatible with layer bidirectional_11: expected ndim=3, found ndim=2
  </code></pre>
  
  <p>My code looks like this:</p>
  
  <pre><code>input_shape = (lengtharray,1)
  model = Sequential()
  model.add(Bidirectional(CuDNNLSTM(128, input_shape=input_shape, return_sequences=True)))
  model.add(Dropout(0.5))
  model.add(Dense(64))
  model.add(Bidirectional(CuDNNLSTM(128)))
  model.add(Dropout(0.5))
  model.add(Dense(64))
  model.add(Dropout(0.5))
  model.add(Dense(1, activation='sigmoid'))
  model.build(input_shape)
  
  opt = keras.optimizers.Adam(lr=0.01, decay=0.0001)
  model.compile(loss='binary_crossentropy',
                optimizer=opt,
                metrics=['accuracy'])
  callbacks = [EarlyStopping(monitor='val_loss'),
               ModelCheckpoint(filepath='best_model.h5', monitor='val_loss', save_best_only=True)]
  model.summary()
  
  </code></pre>
  
  <p>Why does it return a shape error when using a Bidirectional instead of standard LSTM?</p>