title: Recurrent Convolutional Autoencoder in Tensorflow
body: <p>I am trying to build a recurrent convolutional autoencoder in Tensorflow, but I am having trouble linking the convolutional autoencoder with the recurrent layer.  </p>
  
  <p>From my understanding the a Tensorflow RNNCell takes in an input of shape (batch_size, time_steps, info_vector), but my 1D convolutional layer has an output shape of (batch_size, info_vector).  Is there a way to have tensorflow store the previous information vectors. Alternatively do I need to use a 2D convolution, add an extra time_step dimension to the input and then not convolve over that dimension?  </p>