fix failure

               activation_fn='ani',

               layer_structures=[128, 64],

               atom_number_cases=[1, 6, 7, 8, 16],

               dropout_prob=0.,

               penalty=0.,

               **kwargs):

    """

    Parameters

    self.activation_fn = activation_fn

    self.layer_structures = layer_structures

    self.atom_number_cases = atom_number_cases

    self.dropout_prob = dropout_prob

    self.penalty = penalty

    super(ANIRegression, self).__init__(**kwargs)

    # (ytz): this is really dirty but needed for restoring models

          self.atom_number_cases,

          activation=self.activation_fn,

          in_layers=[previous_layer, self.atom_numbers])

      dropout = Dropout(self.dropout_prob, in_layers=[Hidden])

      Hiddens.append(dropout)

      Hiddens.append(Hidden)

      previous_layer = Hiddens[-1]

    costs = []

    loss = WeightedError(in_layers=[all_cost, self.weights])

    if self.exp_loss:

      loss = Exp(in_layers=[loss])

    loss = WeightDecay(self.penalty, 'l2', in_layers=[loss])

    self.set_loss(loss)

  def default_generator(self,

        "learning_rate": 0.001,

        "use_queue": False,

        "mode": "regression",

        "model_dir": self.model_dir,

        "activation_fn": "relu"

        "model_dir": self.model_dir

    }

    model = ANIRegression(**self.kwargs)

      exp_loss=False,

      layer_structures=layer_structures,

      atom_number_cases=atom_number_cases,

      dropout=0.,

      penalty=0.,

      batch_size=batch_size,

      learning_rate=lr,

      use_queue=False,