autoencoder.py 文件源码

def __init__(self, layers, batch_size, activation_func=tf.nn.sigmoid, saved_graph=None, sess=None, learning_rate=0.0001, batch_norm=False):
        """
        @param layers is a list of integers, determining the amount of layers and their size
            starting with the input size
        """
        if len(layers) < 2:
            print("Amount of layers must be greater than 1")
            exit(0)

        self.batch_size = batch_size
        self.learning_rate = learning_rate
        self.activation_func = activation_func
        self.batch_norm = batch_norm

        self.is_training = True

        # Use this in data preprocessing
        self.layers = layers

        self._make_graph(layers)

        if saved_graph is not None and sess is not None:
            self.import_from_file(sess, saved_graph)