title: Keras/TF: Time Distributed CNN+LSTM for visual recognition
body: <p><a href="https://i.stack.imgur.com/FuxJA.png" rel="noreferrer"><img src="https://i.stack.imgur.com/FuxJA.png" alt="enter image description here"></a></p>
  
  <p>I am trying to implement the Model from the article (<a href="https://arxiv.org/abs/1411.4389" rel="noreferrer">https://arxiv.org/abs/1411.4389</a>) that basically consists of time-distributed CNNs followed by a sequence of LSTMs using Keras with TF.</p>
  
  <p>However, I am having a problem trying to figure out if I should include the <code>TimeDirstibuted</code> function just for my Convolutional &amp; Pooling Layers or also for the LSTMs?</p>
  
  <p>Is there a way to run the CNN Layers in parallel (Based on the number of frames in the sequence that I want to process and based on the number of cores that I have)?</p>
  
  <p>And Last, suppose that each entry is composed of "n" frames (in sequence) where n varies based on the current data entry, what is the best suitable input dimension? and would "n" be the batch size? Is there a way to limit the number of CNNs in // to for example 4 (so that you get an output Y after 4 frames are processed)?</p>
  
  <p>P.S.: The inputs are small videos (i.e. a sequence of frames)</p>
  
  <p>P.S.: The output dimension is irrelevant to my question, so it is not discussed here</p>
  
  <p>Thank you</p>