如何初始化slim.fully_connected變量？

Question

代碼：

tf.reset_default_graph() 
init = tf.global_variables_initializer() 

with tf.Session() as sess: 
    states = np.array(range(3)) 
    oneh = slim.one_hot_encoding(states, len(states)) 
    x = slim.fully_connected(oneh,2, \ 
            biases_initializer=None,activation_fn=tf.nn.sigmoid,weights_initializer=tf.ones_initializer()) 

    sess.run(init) 
    print(sess.run(x)) 

例外：

FailedPreconditionError (see above for traceback): Attempting to use uninitialized value fully_connected/weights 
    [[Node: fully_connected/weights/read = Identity[T=DT_FLOAT, _class=["loc:@fully_connected/weights"], _device="/job:localhost/replica:0/task:0/cpu:0"](fully_connected/weights)]] 

Answer 1

您需要定義變量之後定義初始化運算。

states = np.array(range(3)) 
oneh = slim.one_hot_encoding(states, len(states)) 
x = slim.fully_connected(oneh,2,biases_initializer=None,activation_fn=tf.nn.sigmoid,weights_initializer=tf.ones_initializer()) 
init = tf.global_variables_initializer() 
with tf.Session() as sess: 
    sess.run(init) 
    print(sess.run(x))