Python tensorflow属性错误初始化所有变量
我是tensorflow的新手。下面是我试图运行的程序Python tensorflow属性错误初始化所有变量,python,machine-learning,neural-network,tensorflow,Python,Machine Learning,Neural Network,Tensorflow,我是tensorflow的新手。下面是我试图运行的程序 import numpy as np import tensorflow as tf with tf.Session() as sess: x=tf.placeholder("float",[1,3]) relu_out=x num_layers=2 for layer in range(num_layers): w=tf.Variable(tf.random_normal([3,3]))
import numpy as np
import tensorflow as tf
with tf.Session() as sess:
x=tf.placeholder("float",[1,3])
relu_out=x
num_layers=2
for layer in range(num_layers):
w=tf.Variable(tf.random_normal([3,3]))
b=tf.Variable(tf.zeros([1,3]))
relu_out=tf.nn.relu(tf.matmul(relu_out,w)+b)
softmax_w=tf.Variable(tf.random_normal([3,3]))
softmax_b=tf.Variable(tf.zeros([1,3]))
logit=tf.matmul(relu_out,softmax_w)+softmax_b
softmax=tf.nn.softmax(logit)
answer=np.array([[0.0,1.0,0.0]])
labels=tf.placeholder("float",[1,3])
cross_entropy=tf.nn.softmax_cross_entropy_with_logits(relu_out,labels,name='xentropy')
optimizer=tf.train.GradientDescentOptimizer(0.1)
train_op=optimizer.minimize(cross_entropy)
sess.run(tf.initialize_all_vraiables())
for step in range(10):
sess.run(train_op,feed_dict={x:np.array([[1.0,2.0,3.0]]),labels:answer})
它显示以下错误:
Traceback (most recent call last):
File "/home/nilay/gdrive/REU/summer_exp/tf_tut/tf_add_layers.py", line 20, in <module>
sess.run(tf.initialize_all_vraiables())
AttributeError: 'module' object has no attribute 'initialize_all_vraiables'
回溯(最近一次呼叫最后一次):
文件“/home/nilay/gdrive/REU/summer\u exp/tf\u tut/tf\u add\u layers.py”,第20行,在
sess.run(tf.initialize_all_vraiables())
AttributeError:“模块”对象没有“初始化所有可用文件”属性
请帮我解决它。您的代码中有一个输入错误: 是tf.初始化所有变量而不是tf.初始化所有变量