def __init__(self, learning_rate=0.001, num_hidden_layers=1, num_inner_features=100):
    'Initializer for model class.\n\n        Args:\n            learning_rate: the learning rate of the model.\n            num_hidden_layers: number of hidden layers in the network.\n            num_inner_features: number of features in the hidden layers.\n        '
    super(NeuralNetworkModel, self).__init__()
    self.model = None
    self.optimizer = None
    self.criterion = nn.MSELoss()
    self.learning_rate = learning_rate
    self.num_hidden_layers = num_hidden_layers
    self.num_inner_features = num_inner_features
    self.id_str = '{}_{}_{}_{}'.format(self.name, learning_rate, num_hidden_layers, num_inner_features)
Initializer for model class.

Args:
    learning_rate: the learning rate of the model.
    num_hidden_layers: number of hidden layers in the network.
    num_inner_features: number of features in the hidden layers.
def __init__(self, learning_rate=0.001, num_hidden_layers=1, num_inner_features=100):
    'Initializer for model class.\n\n        Args:\n            learning_rate: the learning rate of the model.\n            num_hidden_layers: number of hidden layers in the network.\n            num_inner_features: number of features in the hidden layers.\n        '
    super(NeuralNetworkModel, self).__init__()
    self.model = None
    self.optimizer = None
    self.criterion = nn.MSELoss()
    self.learning_rate = learning_rate
    self.num_hidden_layers = num_hidden_layers
    self.num_inner_features = num_inner_features
    self.id_str = '{}_{}_{}_{}'.format(self.name, learning_rate, num_hidden_layers, num_inner_features)