title: Tensorflow adam optimizer in Keras
body: <p>I have a net in Tensorflow and I am trying to reimplement it in Keras. Currently compared to the Tensorflow model the Keras model completly underperforms. The loss is much higher and decreases slower compared to the original model. My best guess is that I am using the wrong Optimizer. In the Tensorflow code the Optimizer looks like this:</p>
  
  <pre><code>global_step = tf.Variable(0, trainable=False)
  learning_rate = tf.train.exponential_decay(0.0001,
                                             global_step,
                                             decay_steps=10000,
                                             decay_rate=0.33,   
                                             staircase=True)
  optimizer = tf.train.AdamOptimizer(learning_rate, epsilon=1e-8)
  train_op = optimizer.minimize(total_loss, global_step)
  </code></pre>
  
  <p>In Keras it looks like this:</p>
  
  <pre><code>adam = keras.optimizers.Adam(lr=0.0001, beta_1=0.9, beta_2=0.999, epsilon=1e-8)
  model.compile(loss=get_loss_funcs(), optimizer=adam)
  </code></pre>
  
  <p>Is there a way to implement the Tensorflow optimizer in Keras?</p>