title: Tensorflow 2.0: Optimizer.minimize ('Adam' object has no attribute 'minimize')
body: <p>For my Reinforcement Learning application, I need to be able to apply custom gradients / minimize changing loss function. According to <a href="https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/optimizers/Optimizer" rel="noreferrer">documentation</a>, it should be possible with Optimizer.minimize() function. However, my pip-installed version appears not to have this feature at all.</p>
  
  <p>My code:</p>
  
  <pre><code>from tensorflow.python.keras.optimizers import Adam, SGD
  print(tf.version.VERSION)
  optim = Adam()
  optim.minimize(loss, var_list=network.weights)
  </code></pre>
  
  <p>output:</p>
  
  <pre><code>2.0.0-alpha0
  Traceback (most recent call last):
    File "/Users/ikkamens/Library/Preferences/PyCharmCE2018.3/scratches/testo.py", line 18, in &lt;module&gt;
      optim.minimize(loss, var_list=network.weights)
  AttributeError: 'Adam' object has no attribute 'minimize'
  </code></pre>