hybrid_model.py 文件源码

def __init__(self,
               params,
               device_assigner=None,
               optimizer_class=adagrad.AdagradOptimizer,
               **kwargs):

    self.device_assigner = (
        device_assigner or tensor_forest.RandomForestDeviceAssigner())

    self.params = params

    self.optimizer = optimizer_class(self.params.learning_rate)

    self.is_regression = params.regression

    self.regularizer = None
    if params.regularization == "l1":
      self.regularizer = layers.l1_regularizer(
          self.params.regularization_strength)
    elif params.regularization == "l2":
      self.regularizer = layers.l2_regularizer(
          self.params.regularization_strength)