我们从Python开源项目中，提取了以下4个代码示例，用于说明如何使用base.Model()。
def __init__(self, sess, reader, dataset="ptb", batch_size=20, num_steps=3, embed_dim=500, h_dim=50, learning_rate=0.01, epoch=50, checkpoint_dir="checkpoint"): """Initialize Neural Varational Document Model. params: sess: TensorFlow Session object. reader: TextReader object for training and test. dataset: The name of dataset to use. h_dim: The dimension of document representations (h). [50, 200] """ self.sess = sess self.reader = reader self.h_dim = h_dim self.embed_dim = embed_dim self.epoch = epoch self.batch_size = batch_size self.learning_rate = learning_rate self.checkpoint_dir = checkpoint_dir self.dataset="ptb" self._attrs=["batch_size", "num_steps", "embed_dim", "h_dim", "learning_rate"] raise Exception(" [!] Working in progress") self.build_model()
def __init__(self, sess, reader, dataset="ptb", decay_rate=0.96, decay_step=10000, embed_dim=500, h_dim=50, learning_rate=0.001, max_iter=450000, checkpoint_dir="checkpoint"): """Initialize Neural Varational Document Model. params: sess: TensorFlow Session object. reader: TextReader object for training and test. dataset: The name of dataset to use. h_dim: The dimension of document representations (h). [50, 200] """ self.sess = sess self.reader = reader self.h_dim = h_dim self.embed_dim = embed_dim self.max_iter = max_iter self.decay_rate = decay_rate self.decay_step = decay_step self.checkpoint_dir = checkpoint_dir self.step = tf.Variable(0, trainable=False) self.lr = tf.train.exponential_decay( learning_rate, self.step, 10000, decay_rate, staircase=True, name="lr") _ = tf.scalar_summary("learning rate", self.lr) self.dataset = dataset self._attrs = ["h_dim", "embed_dim", "max_iter", "dataset", "learning_rate", "decay_rate", "decay_step"] self.build_model()
