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)