矩阵乘法不起作用 - Tensorflow

Question

我在使用tensorflow并且正在用于学校项目。在这里，我试图创建一个房屋标识符，我在一张Excel表格上创建了​​一些数据，将其转换为一个csv文件，然后测试数据是否会被读取。数据被读取，但是当我进行矩阵乘法并且说...时，它会产生多个错误。“ValueError：形状必须是等级2，但是'MatMul'（op：'MatMul'）的等级为0，输入形状为：[] ，[1,1]。“非常感谢！

import tensorflow as tf 
import os 
dir_path = os.path.dirname(os.path.realpath(__file__)) 
filename = dir_path+ "\House Price Data .csv" 
w1=tf.Variable(tf.zeros([1,1])) 
w2=tf.Variable(tf.zeros([1,1])) #Feature 1's weight 
w3=tf.Variable(tf.zeros([1,1])) #Feature 1's weight 
b=tf.Variable(tf.zeros([1])) #bias for various features 
x1= tf.placeholder(tf.float32,[None, 1]) 
x2= tf.placeholder(tf.float32,[None, 1]) 
x3= tf.placeholder(tf.float32,[None, 1]) 
Y= tf.placeholder(tf.float32,[None, 1]) 
y_=tf.placeholder(tf.float32,[None,1]) 
with tf.Session() as sess: 
    sess.run(tf.global_variables_initializer()) 
    with open(filename) as inf: 
     # Skip header 
     next(inf) 
     for line in inf: 
      # Read data, using python, into our features 
      housenumber, x1, x2, x3, y_ = line.strip().split(",") 
      x1 = float(x1) 
      product = tf.matmul(x1, w1) 
      y = product + b 

Answer 1

@Aaron是对的，你从csv文件加载数据时覆盖变量。

您需要将加载的值保存到一个单独的变量中，例如_x1而不是x1，然后使用feed_dict将值提供给占位符。并且因为x1的形状为[None,1]，所以需要将字符串标量_x1转换为具有相同形状的浮动，在这种情况下为[1,1]。

import tensorflow as tf 
import os 
dir_path = os.path.dirname(os.path.realpath(__file__)) 
filename = dir_path+ "\House Price Data .csv" 
w1=tf.Variable(tf.zeros([1,1])) 
b=tf.Variable(tf.zeros([1])) #bias for various features 
x1= tf.placeholder(tf.float32,[None, 1]) 

y_pred = tf.matmul(x1, w1) + b 

with tf.Session() as sess: 
    sess.run(tf.global_variables_initializer()) 
    with open(filename) as inf: 
     # Skip header 
     next(inf) 
     for line in inf: 
      # Read data, using python, into our features 
      housenumber, _x1, _x2, _x3, _y_ = line.strip().split(",") 
      sess.run(y_pred, feed_dict={x1:[[float(_x1)]]})