title: How to deal with the size of images and filters if we use Covolutional LSTM + Conv2D?
body: <p>I am working on Convolutional LSTM + convolutional neural Network. Instead of getting my data in image format i have been given flattened images matrix which is [10000x784].</p>
  
  <p>Means 10000 images of size 28x28</p>
  
  <p>Considering one image size is 28x28, i am trying the following for CLSTM</p>
  
  <p>My model is:</p>
  
  <pre><code>model = models.Sequential()
  model.add(layers.Reshape((None,28, 28,1 ), input_shape=(784,)))
  model.add(layers.ConvLSTM2D(filters=64, kernel_size=(3, 3),
                     input_shape=(None, 28, 28, 1),
                     padding='same', return_sequences=True))
  model.add(layers.Conv2D(32, (3, 3), activation='relu'))
  model.add(layers.Conv2D(32, (3, 3), activation='relu'))
  model.add(layers.MaxPooling2D((2, 2)))
  model.add(layers.Flatten())
  model.add(layers.Dense(2500, activation='relu'))
  model.add(layers.Dense(1, activation='linear'))
  </code></pre>
  
  <p>but i am getting the subjected error. What can i do to make ndims=5?</p>