小编Pan*_*ami的帖子

在Tensorflow中,我可以用两种方式初始化变量:

1. global_variable_intializer在声明变量之前调用:

   import tensorflow as tf
   
   # Initialize the global variable and session
   init = tf.global_variables_initializer()
   sess = tf.Session()
   sess.run(init)
   
   W = tf.Variable([.3], tf.float32)
   b = tf.Variable([-.3], tf.float32)
   b = tf.Variable([-.3], tf.float32)
   linear_model = W * x + b
   

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2. global_variable_intializer声明变量后调用:

   import tensorflow as tf
   
   W = tf.Variable([.3], tf.float32)
   b = tf.Variable([-.3], tf.float32)
   b = tf.Variable([-.3], tf.float32)
   linear_model = W * x + b 
   
   # Initialize the global variable and session
   init = tf.global_variables_initializer()
   sess = tf.Session()
   sess.run(init)
   

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两者有什么区别？哪个是初始化变量的最佳方法？ …