In [1]:

    

# 変数の作成
import tensorflow as tf
import numpy as np
import tensorboard_jupyter as tb

my_var = tf.Variable(tf.zeros([2,3]))
# 変数は初期化しないとエラーになる
initialize_op = tf.global_variables_initializer()

with tf.Session() as sess:
    sess.run(initialize_op)
    sess.run(my_var)
    tf.summary.FileWriter('./log/', sess.graph)
tb.show_graph(tf.get_default_graph().as_graph_def())


    

In [2]:

    

sess = tf.Session()
x = tf.placeholder(tf.float32, shape=[2,2])
# yはxの恒等関数
y = tf.identity(x)
x_vals = np.random.rand(2,2)
sess.run(y, feed_dict = {x: x_vals})

with tf.Session() as sess:
    result = sess.run(y, feed_dict = {x: x_vals})
    print(result)
    tf.summary.FileWriter('./log/', sess.graph)
tb.show_graph(tf.get_default_graph().as_graph_def())


    

    




[[ 0.43564174  0.37655979]
 [ 0.58525461  0.10683782]]






    






        
    

In [3]:

    

with tf.Session() as sess:
    first_var = tf.Variable(tf.zeros([2,3]))
    sess.run(first_var.initializer)
    second_var = tf.Variable(tf.zeros_like([first_var]))
    # first_varに依存する
    sess.run(second_var.initializer)
    tf.summary.FileWriter('./log/', sess.graph)
tb.show_graph(tf.get_default_graph().as_graph_def())


    

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