title: How to read Keras's model structure?
body: <p>For example:</p>
  
  <pre><code>BUFFER_SIZE = 10000
       BATCH_SIZE = 64
      train_dataset = train_dataset.shuffle(BUFFER_SIZE)
  train_dataset = train_dataset.padded_batch(BATCH_SIZE, tf.compat.v1.data.get_output_shapes(train_dataset))
  test_dataset = test_dataset.padded_batch(BATCH_SIZE, tf.compat.v1.data.get_output_shapes(test_dataset))
  
  def pad_to_size(vec, size):
    zeros = [0] * (size - len(vec))
    vec.extend(zeros)
    return vec
  ...
  
  model = tf.keras.Sequential([
      tf.keras.layers.Embedding(encoder.vocab_size, 64),
      tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(64, return_sequences=False)),
      tf.keras.layers.Dense(64, activation='relu'),
      tf.keras.layers.Dense(1, activation='sigmoid')
  ])
  
  print(model.summary())
  </code></pre>
  
  <p>The print reads as:</p>
  
  <pre><code>Model: "sequential"
  _________________________________________________________________
  Layer (type)                 Output Shape              Param #   
  =================================================================
  embedding (Embedding)        (None, None, 64)          523840    
  _________________________________________________________________
  bidirectional (Bidirectional (None, 128)               66048     
  _________________________________________________________________
  dense (Dense)                (None, 64)                8256      
  _________________________________________________________________
  dense_1 (Dense)              (None, 1)                 65        
  =================================================================
  Total params: 598,209
  Trainable params: 598,209
  Non-trainable params: 0
  </code></pre>
  
  <p>I have the following question:  </p>
  
  <p>1) For the embedding layer, why is the ouput shape is <code>(None, None, 64)</code>. I understand '64' is the vector length. Why are the <em>other two None</em>?</p>
  
  <p>2) How is the output shape of bidirectional layer is <code>(None, 128)</code>? Why is it <code>128</code>?</p>