(hparams)
return optimizer
Creates optimized based on the specified flags.
Creates optimized based on the specified flags.
Creates optimized based on the specified flags .
def create_optimizer(hparams):
  """Creates optimized based on the specified flags."""
  if hparams.optimizer == 'momentum':
    optimizer = tf.train.MomentumOptimizer(
        hparams.learning_rate, momentum=hparams.momentum)
  elif hparams.optimizer == 'adam':
    optimizer = tf.train.AdamOptimizer(hparams.learning_rate)
  elif hparams.optimizer == 'adadelta':
    optimizer = tf.train.AdadeltaOptimizer(hparams.learning_rate)
  elif hparams.optimizer == 'adagrad':
    optimizer = tf.train.AdagradOptimizer(hparams.learning_rate)
  elif hparams.optimizer == 'rmsprop':
    optimizer = tf.train.RMSPropOptimizer(
        hparams.learning_rate, momentum=hparams.momentum)
  return optimizer
def create_optimizer ( hparams ) : if hparams . optimizer == 'momentum' : optimizer = tf . train . MomentumOptimizer ( hparams . learning_rate , momentum = hparams . momentum ) elif hparams . optimizer == 'adam' : optimizer = tf . train . AdamOptimizer ( hparams . learning_rate ) elif hparams . optimizer == 'adadelta' : optimizer = tf . train . AdadeltaOptimizer ( hparams . learning_rate ) elif hparams . optimizer == 'adagrad' : optimizer = tf . train . AdagradOptimizer ( hparams . learning_rate ) elif hparams . optimizer == 'rmsprop' : optimizer = tf . train . RMSPropOptimizer ( hparams . learning_rate , momentum = hparams . momentum ) return optimizer