8.4.2节预测正弦函数的疑惑 about tensorflow-tutorial HOT 6 CLOSED

def generate_data(seq):
    X = []
    y = []
    for i in range(len(seq) - TIMESTEPS - 1):
        X.append([[x] for x in seq[i: i + TIMESTEPS]]) # 此处将输入修改为[batch_size, 10, 1]
        y.append([seq[i + TIMESTEPS]])
    return np.array(X, dtype=np.float32), np.array(y, dtype=np.float32)

def lstm_model(X, y):
    lstm_cell = tf.contrib.rnn.BasicLSTMCell(HIDDEN_SIZE, state_is_tuple=True)
    cell = tf.contrib.rnn.MultiRNNCell([lstm_cell] * NUM_LAYERS)
    
    output, _ = tf.nn.dynamic_rnn(cell, X, dtype=tf.float32)
    output = tf.unstack(output, axis=1)[-1] # 此处修改为最后时刻的输出
    
    # 通过无激活函数的全联接层计算线性回归，并将数据压缩成一维数组的结构。
    predictions = tf.contrib.layers.fully_connected(output, 1, None)
    
    # 将predictions和labels调整统一的shape
    labels = tf.reshape(y, [-1])
    predictions=tf.reshape(predictions, [-1])
    
    loss = tf.losses.mean_squared_error(predictions, labels)
    
    train_op = tf.contrib.layers.optimize_loss(
        loss, tf.contrib.framework.get_global_step(),
        optimizer="Adagrad", learning_rate=0.1)

    return predictions, loss, train_op