TypeError: Argument `fetch` = None

Question

使用tensorflow完成线性回归报错

import tensorflow as tf

tf.compat.v1.disable_eager_execution()


def linear_regression_demo():
    # 1）准备真实值,随机生成100行1列
    X = tf.compat.v1.random_normal(shape=[100, 1])
    y_true = tf.matmul(X, [[0.8]]) + 0.7
    # 2）构造模型,定义模型参数用变量
    weights = tf.Variable(initial_value=tf.compat.v1.random_normal(shape=[1, 1]))
    bias = tf.Variable(initial_value=tf.compat.v1.random_normal(shape=[1, 1]))
    y_predict = tf.matmul(X, weights) + bias
    # 3）损失函数
    error = tf.reduce_mean(tf.square(y_predict - y_true))
    # 4）优化损失
    optimizer = tf.compat.v1.train.GradientDescentOptimizer(learning_rate=0.01).minimize(error)
    # 2_收集变量
    tf.summary.scalar('error', error)
    tf.summary.histogram("weights", weights)
    tf.summary.histogram("bias", bias)
    # 3_合并变量
    merged = tf.compat.v1.summary.merge_all()
    # 开启会话
    init = tf.compat.v1.global_variables_initializer()
    with tf.compat.v1.Session() as sess:
        # 初始化变量
        sess.run(init)
        # 1_创建事件文件
        file_writer = tf.compat.v1.summary.FileWriter("./venv/Linear", graph=sess.graph)
        # 查看初始化后模型参数的值
        print("训练前模型参数为：权重%f,偏执%f,损失为%f" % (weights.eval(), bias.eval(), error.eval()))
        # 开始训练
        for i in range(100):
            sess.run(optimizer)
            print("第%d次训练后模型参数为：权重%f,偏执%f,损失为%f" % (i+1, weights.eval(), bias.eval(), error.eval()))
            # 合并变量操作
            summary = sess.run(merged)
            # 写入事件文件
            file_writer.add_summary(summary, i)
        # 若下面的print在循环体中，则可以看到每次迭代后的值，即看到训练的过程
    return None


if __name__ == "__main__":
    # 实现线性回归
    linear_regression_demo()

运行结果及报错内容

训练前模型参数为：权重1.473141,偏执-0.302616,损失为1.375756
第1次训练后模型参数为：权重1.458058,偏执-0.283769,损失为1.439239
Traceback (most recent call last):
  File "E:/pycharm2022/pythonproject/Linear_regression.py", line 50, in <module>
    linear_regression_demo()
  File "E:/pycharm2022/pythonproject/Linear_regression.py", line 41, in linear_regression_demo
    summary = sess.run(merged)
  File "E:\pycharm2022\pythonproject\venv\lib\site-packages\tensorflow\python\client\session.py", line 968, in run
    result = self._run(None, fetches, feed_dict, options_ptr,
  File "E:\pycharm2022\pythonproject\venv\lib\site-packages\tensorflow\python\client\session.py", line 1176, in _run
    fetch_handler = _FetchHandler(
  File "E:\pycharm2022\pythonproject\venv\lib\site-packages\tensorflow\python\client\session.py", line 485, in __init__
    self._fetch_mapper = _FetchMapper.for_fetch(fetches)
  File "E:\pycharm2022\pythonproject\venv\lib\site-packages\tensorflow\python\client\session.py", line 262, in for_fetch
    raise TypeError(f'Argument `fetch` = {fetch} has invalid type '
TypeError: Argument `fetch` = None has invalid type "NoneType". Cannot be None

Process finished with exit code 1

我的解答思路和尝试过的方法

还不知道为什么出错，求解

Answer 1

你把收集能量那边改一下：在summary前加上compat.v1
tf.compat.v1.summary.scalar("error", error)
tf.compat.v1.summary.histogram("weight", weights)
tf.compat.v1.summary.histogram("bias", bias)