def __init__(self, sess, layers_sizes, lambda_=1.0, error=1.0e-5):
self.lambda_ = lambda_
self.layers_sizes = layers_sizes
self.error = error
self.errors = []
self.AE = DAE.Deep_Autoencoder(sess=sess,
input_dim_list=self.layers_sizes)
def __init__(self, sess, layers_sizes, lambda_=1.0, error = 1.0e-7):
"""
sess: a Tensorflow tf.Session object
layers_sizes: a list that contain the deep ae layer sizes, including the input layer
lambda_: tuning the weight of l1 penalty of S
error: converge criterior for jump out training iteration
"""
self.lambda_ = lambda_
self.layers_sizes = layers_sizes
self.error = error
self.errors=[]
self.AE = DAE.Deep_Autoencoder( sess = sess, input_dim_list = self.layers_sizes)