title: Extract Cell State LSTM Keras
body: <p>I was wondering if it would be possible to extract the last cell state of an LSTM in Keras after training the model. For example, in this simple LSTM model:</p>
  
  <pre><code>number_of_dimensions = 128
  number_of_examples = 123456
  
  input_ = Input(shape = (10,100,))
  lstm, hidden, cell = CuDNNLSTM(units = number_of_dimensions, return_state=True)(input_)
  
  dense = Dense(num_of_classes, activation='softmax')(lstm)
  
  model = Model(inputs = input_, outputs = dense)
  parallel_model = multi_gpu_model(model, gpus=2)
  parallel_model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['acc'])
  
  # fit the model
  parallel_model.fit(X1, onehot_encoded, epochs=100, verbose=1, batch_size = 128, validation_split = 0.2)
  </code></pre>
  
  <p>I tried printing 'cell' but the result was </p>
  
  <pre><code>tf.Tensor 'cu_dnnlstm_2/strided_slice_17:0' shape=(?, 128) dtype=float32 
  </code></pre>
  
  <p>I would like to get the cell state as a numpy array of shape (number_of_examples, number_of_dimensions) or (123456, 128). Is it possible to do this keras? </p>
  
  <p>Thank you!</p>