添加层add_layer()

import tensorflow as tf
import numpy as np

def add_layer(inputs, input_size, output_size, activation_function = None):
    Weights = tf.Variable(tf.random_normal([input_size, output_size]))
    biases = tf.Variable(tf.zeros([1, output_size]) + 0.1) #biases初始化为0.1的列向量
    Wx_plus_b = tf.matmul(inputs, Weights) + biases
    if activation_function is None:
        outputs = Wx_plus_b
    else:
        outputs = activation_function(Wx_plus_b)
    return outputs

这里的inputs是行向量，代表原始数据中的属性个数